chore: organize backup files into dated directory structure
- Consolidated all .bak.* files from bot/ directory into backups/2025-12-07/ - Moved unused autonomous_wip.py to backups (verified not imported anywhere) - Relocated old .bot.bak.80825/ backup directory into backups/2025-12-07/old-bot-bak-80825/ - Preserved autonomous_v1_legacy.py as it is still actively used by autonomous.py - Created new backups/ directory with date-stamped subdirectory for better organization
This commit is contained in:
464
backups/2025-12-07/.bak.bot.py
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464
backups/2025-12-07/.bak.bot.py
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import discord
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import aiohttp
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import asyncio
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import os
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import re
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import random
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import string
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import base64
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import subprocess
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import aiofiles
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from langchain_community.vectorstores import FAISS
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from langchain_ollama import OllamaEmbeddings
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from langchain.text_splitter import CharacterTextSplitter
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from langchain_community.docstore.document import Document
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from collections import defaultdict, deque
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from apscheduler.schedulers.asyncio import AsyncIOScheduler
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from discord import File
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from discord import Status
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import datetime
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from apscheduler.triggers.date import DateTrigger
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from datetime import datetime, timedelta
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scheduler = AsyncIOScheduler()
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BEDTIME_CHANNEL_IDS = [761014220707332107]
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# Stores last 5 exchanges per user (as deque)
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conversation_history = defaultdict(lambda: deque(maxlen=5))
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DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
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OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
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OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
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embeddings = OllamaEmbeddings(
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model=OLLAMA_MODEL,
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base_url=OLLAMA_URL
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)
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# Set up Discord client
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intents = discord.Intents.default()
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intents.message_content = True
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intents.members = True
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intents.presences = True
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client = discord.Client(intents=intents)
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current_model = None # Track currently loaded model name
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# Switch model
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async def switch_model(model_name: str, timeout: int = 600):
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global current_model
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if current_model == model_name:
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print(f"🔁 Model '{model_name}' already loaded.")
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return
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# Unload all other models to clear VRAM
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async with aiohttp.ClientSession() as session:
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async with session.get(f"{OLLAMA_URL}/api/show") as resp:
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if resp.status == 200:
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data = await resp.json()
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loaded_models = data.get("models", [])
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for model in loaded_models:
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if model["name"] != model_name:
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print(f"🔁 Unloading model: {model['name']}")
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await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
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else:
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print("⚠️ Failed to check currently loaded models.")
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print(f"🔄 Switching to model '{model_name}'...")
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async with aiohttp.ClientSession() as session:
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await session.post(f"{OLLAMA_URL}/api/stop")
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# Warm up the new model (dummy call to preload it)
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payload = {
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"model": model_name,
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"prompt": "Hello",
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"stream": False
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}
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headers = {"Content-Type": "application/json"}
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# Poll until /api/generate returns 200
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async with aiohttp.ClientSession() as session:
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for _ in range(timeout):
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async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
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if resp.status == 200:
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current_model = model_name
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print(f"✅ Model {model_name} ready!")
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return
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await asyncio.sleep(1) # Wait a second before trying again
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raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
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async def download_and_encode_image(url):
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async with aiohttp.ClientSession() as session:
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async with session.get(url) as resp:
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if resp.status != 200:
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return None
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img_bytes = await resp.read()
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return base64.b64encode(img_bytes).decode('utf-8')
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async def analyze_image_with_qwen(base64_img):
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await switch_model("moondream")
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payload = {
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"model": "moondream",
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"prompt": "Describe this image in detail.",
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"images": [base64_img],
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"stream": False
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}
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headers = {"Content-Type": "application/json"}
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async with aiohttp.ClientSession() as session:
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async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
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if response.status == 200:
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data = await response.json()
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return data.get("response", "No description.")
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else:
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return f"Error: {response.status}"
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async def rephrase_as_miku(qwen_output, user_prompt):
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await switch_model(OLLAMA_MODEL) # likely llama3
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with open("miku_prompt.txt", "r", encoding="utf-8") as f:
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system_prompt = f.read()
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relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
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context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
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full_prompt = (
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f"{context}\n\n"
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f"The user asked: \"{user_prompt}\"\n"
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f"The image contains: \"{qwen_output}\"\n\n"
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f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
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f"Miku:"
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)
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payload = {
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"model": OLLAMA_MODEL,
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"prompt": full_prompt,
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"system": system_prompt,
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"stream": False
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}
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headers = {"Content-Type": "application/json"}
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async with aiohttp.ClientSession() as session:
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async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
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if response.status == 200:
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data = await response.json()
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return data.get("response", "No response.")
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else:
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return f"Error: {response.status}"
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# Load and index once at startup
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def load_miku_knowledge():
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with open("miku_lore.txt", "r", encoding="utf-8") as f:
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text = f.read()
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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text_splitter = RecursiveCharacterTextSplitter(
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chunk_size=520,
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chunk_overlap=50,
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separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
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)
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docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
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vectorstore = FAISS.from_documents(docs, embeddings)
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return vectorstore
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def load_miku_lyrics():
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with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
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lyrics_text = f.read()
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text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
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docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
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vectorstore = FAISS.from_documents(docs, embeddings)
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return vectorstore
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miku_vectorstore = load_miku_knowledge()
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miku_lyrics_vectorstore = load_miku_lyrics()
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async def query_ollama(user_prompt, user_id):
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relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
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relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
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context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
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context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
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combined_docs = relevant_docs_lore + relevant_docs_lyrics
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context = "\n\n".join([doc.page_content for doc in combined_docs])
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# Persona definition
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with open("miku_prompt.txt", "r", encoding="utf-8") as f:
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system_prompt = f.read()
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# Build conversation history
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history = conversation_history[user_id]
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history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
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# Combine prompt
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full_prompt = (
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f"{context_lore}\n\n{context_lyrics}\n\n"
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f"{history_text}\nUser: {user_prompt}\nMiku:"
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)
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headers = {'Content-Type': 'application/json'}
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payload = {
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"model": OLLAMA_MODEL,
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"prompt": full_prompt,
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"system": system_prompt,
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"stream": False
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}
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async with aiohttp.ClientSession() as session:
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async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
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if response.status == 200:
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data = await response.json()
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reply = data.get("response", "No response.")
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# Save to conversation history
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conversation_history[user_id].append((user_prompt, reply))
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return reply
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else:
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return f"Error: {response.status}"
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async def send_monday_video():
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await switch_model(OLLAMA_MODEL)
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# Generate a motivational message
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prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
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response = await query_ollama(prompt, user_id="weekly-motivation")
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video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
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target_channel_ids = [
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761014220707332107,
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1140377617237807266
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]
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for channel_id in target_channel_ids:
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channel = client.get_channel(channel_id)
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if channel is None:
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print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
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return
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try:
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await channel.send(content=response)
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# Send video link
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await channel.send(f"[Happy Miku Monday!]({video_url})")
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print(f"✅ Sent Monday video to channel ID {channel_id}")
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except Exception as e:
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print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
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async def send_bedtime_reminder():
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await switch_model(OLLAMA_MODEL)
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for channel_id in BEDTIME_CHANNEL_IDS:
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channel = client.get_channel(channel_id)
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if not channel:
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print(f"⚠️ Channel ID {channel_id} not found.")
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continue
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guild = channel.guild
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# Filter online members (excluding bots)
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online_members = [
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member for member in guild.members
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if member.status in {Status.online, Status.idle, Status.dnd}
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and not member.bot
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]
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if not online_members:
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print(f"😴 No online members to ping in {guild.name}")
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continue
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chosen_one = random.choice(online_members)
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# Generate bedtime message
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prompt = (
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f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
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f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
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)
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bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
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try:
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await channel.send(f"{chosen_one.mention}, {bedtime_message}")
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print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
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except Exception as e:
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print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
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def schedule_random_bedtime():
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now = datetime.now()
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target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
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# If it's already past 23:30 today, schedule for tomorrow
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if now > target_time:
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target_time += timedelta(days=1)
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# Add random offset (0–29 mins)
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offset_minutes = random.randint(0, 29)
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run_time = target_time + timedelta(minutes=offset_minutes)
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scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
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print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
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async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
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font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
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text = f"@{username}"
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# Define your six positions (x, y)
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positions = {
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1: ("250", "370"),
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2: ("330", "130"),
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3: ("300", "90"),
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4: ("380", "180"),
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5: ("365", "215"),
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6: ("55", "365"),
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7: ("290", "130"),
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8: ("320", "210"),
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9: ("310", "240"),
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10: ("400", "240")
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}
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# Each entry: (start_time, end_time, position_index)
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text_entries = [
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(4.767, 5.367, 1, "username"),
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(5.4, 5.967, 2, "username"),
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(6.233, 6.833, 3, "username"),
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(6.967, 7.6, 4, "username"),
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(7.733, 8.367, 5, "username"),
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(8.667, 9.133, 6, "username"),
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(9.733, 10.667, 7, "username"),
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(11.6, 12.033, 8, "@everyone"),
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(12.067, 13.0, 9, "@everyone"),
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(13.033, 14.135, 10, "@everyone"),
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]
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# Build drawtext filters
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drawtext_filters = []
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for start, end, pos_id, text_type in text_entries:
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x_coord, y_coord = positions[pos_id]
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# Determine actual text content
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text_content = f"@{username}" if text_type == "username" else text_type
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x = f"{x_coord} - text_w/2"
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y = f"{y_coord} - text_h/2"
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filter_str = (
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f"drawtext=text='{text_content}':"
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f"fontfile='{font_path}':"
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f"fontcolor=black:fontsize=30:x={x}:y={y}:"
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f"enable='between(t,{start},{end})'"
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)
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drawtext_filters.append(filter_str)
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vf_string = ",".join(drawtext_filters)
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ffmpeg_command = [
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"ffmpeg",
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"-i", base_video_path,
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"-vf", vf_string,
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"-codec:a", "copy",
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output_path
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]
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try:
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subprocess.run(ffmpeg_command, check=True)
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print("✅ Video processed successfully with username overlays.")
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except subprocess.CalledProcessError as e:
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print(f"⚠️ FFmpeg error: {e}")
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@client.event
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async def on_ready():
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print(f'🎤 MikuBot connected as {client.user}')
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# Schedule the weekly task (Monday 07:30)
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scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
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# Schedule first bedtime reminder
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schedule_random_bedtime()
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# Reschedule every midnight
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scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
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#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
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scheduler.start()
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@client.event
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async def on_message(message):
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if message.author == client.user:
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return
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if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
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async with message.channel.typing():
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# Get replied-to user
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try:
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replied_msg = await message.channel.fetch_message(message.reference.message_id)
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target_username = replied_msg.author.display_name
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# Prepare video
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base_video = "MikuMikuBeam.mp4"
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output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
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await overlay_username_with_ffmpeg(base_video, output_video, target_username)
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caption = f"Here you go, @{target_username}! 🌟"
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#await message.channel.send(content=caption, file=discord.File(output_video))
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await replied_msg.reply(file=discord.File(output_video))
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||||
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||||
except Exception as e:
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print(f"⚠️ Error processing video: {e}")
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||||
await message.channel.send("Sorry, something went wrong while generating the video.")
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||||
return
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text = message.content.strip()
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||||
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if re.search(r'^(miku,)|((, miku)[\?\!\.\s,]*)$', message.content.strip(), re.IGNORECASE) or ", miku," in message.content.lower():
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||||
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||||
# Clean the prompt
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||||
if text.lower().startswith("miku, "):
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||||
prompt = text[6:].strip()
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||||
else:
|
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prompt = re.sub(r', miku[\?\!\.\s]*$', '', text, flags=re.IGNORECASE).strip()
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||||
|
||||
async with message.channel.typing():
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||||
# If message has an image attachment
|
||||
if message.attachments:
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||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
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||||
#await message.channel.send("Looking at the image... 🎨")
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||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
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||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
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||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
prompt = message.content[5:].strip()
|
||||
#await message.channel.send("Thinking... 🎶")
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
await message.channel.send(response)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
540
backups/2025-12-07/.bak.bot.py.250625
Normal file
540
backups/2025-12-07/.bak.bot.py.250625
Normal file
@@ -0,0 +1,540 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
665
backups/2025-12-07/.bak.bot.py.260625
Normal file
665
backups/2025-12-07/.bak.bot.py.260625
Normal file
@@ -0,0 +1,665 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
AUTO_MOOD = True
|
||||
CURRENT_MOOD = "neutral"
|
||||
AVAILABLE_MOODS = [
|
||||
"bubbly", "sleepy", "curious", "shy", "serious", "excited",
|
||||
"melancholy", "flirty", "romantic", "irritated", "angry", "neutral"
|
||||
]
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
def load_mood_description(mood_name: str) -> str:
|
||||
path = os.path.join("moods", f"{mood_name}.txt")
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
except FileNotFoundError:
|
||||
print(f"⚠️ Mood file '{mood_name}' not found. Falling back to default.")
|
||||
return load_mood_description("neutral")
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
for phrase in phrases:
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
global CURRENT_MOOD
|
||||
|
||||
new_mood = CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if message.content.startswith("!miku mood "):
|
||||
new_mood = message.content.split("!miku mood ")[1].strip().lower()
|
||||
path = os.path.join("moods", f"{new_mood}.txt")
|
||||
if os.path.exists(path):
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
await message.channel.send(f"🌈 Miku's mood has been set to **{new_mood}**!")
|
||||
else:
|
||||
await message.channel.send("⚠️ I don't recognize that mood. Try again with a valid one.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-reset":
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
await message.channel.send("🔄 Miku’s mood has been reset to **neutral**.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-check":
|
||||
await message.channel.send(f"☑️ Miku’s mood is currently {CURRENT_MOOD}.")
|
||||
|
||||
if AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != CURRENT_MOOD:
|
||||
CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
728
backups/2025-12-07/.bak.bot.py.260625-1
Normal file
728
backups/2025-12-07/.bak.bot.py.260625-1
Normal file
@@ -0,0 +1,728 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
AUTO_MOOD = True
|
||||
CURRENT_MOOD = "neutral"
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
PREVIOUS_MOOD_NAME = "neutral"
|
||||
IS_SLEEPING = False
|
||||
AVAILABLE_MOODS = [
|
||||
"bubbly", "sleepy", "curious", "shy", "serious", "excited",
|
||||
"melancholy", "flirty", "romantic", "irritated", "angry", "neutral"
|
||||
]
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
def load_mood_description(mood_name: str) -> str:
|
||||
path = os.path.join("moods", f"{mood_name}.txt")
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
except FileNotFoundError:
|
||||
print(f"⚠️ Mood file '{mood_name}' not found. Falling back to default.")
|
||||
return load_mood_description("neutral")
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
],
|
||||
"asleep": [
|
||||
"goodnight", "sweet dreams", "going to bed", "I will go to bed", "zzz~", "sleep tight"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
for phrase in phrases:
|
||||
if mood == "asleep" and CURRENT_MOOD_NAME != "sleepy":
|
||||
continue # Only allow transition to asleep from sleepy
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
async def set_sleep_state(sleeping: bool):
|
||||
if sleeping:
|
||||
await client.change_presence(status=discord.Status.invisible)
|
||||
await client.user.edit(username="Hatsune Miku💤")
|
||||
print("😴 Miku has gone to sleep.")
|
||||
else:
|
||||
await client.change_presence(status=discord.Status.online)
|
||||
await client.user.edit(username="Hatsune Miku")
|
||||
print("☀️ Miku woke up.")
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
global CURRENT_MOOD
|
||||
|
||||
new_mood = CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
global CURRENT_MOOD, CURRENT_MOOD_NAME, PREVIOUS_MOOD_NAME, IS_SLEEPING
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
if IS_SLEEPING:
|
||||
await message.channel.send("💤 Miku is currently sleeping and can't talk right now. Try again later~")
|
||||
return
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if message.content.startswith("!miku mood "):
|
||||
new_mood = message.content.split("!miku mood ")[1].strip().lower()
|
||||
path = os.path.join("moods", f"{new_mood}.txt")
|
||||
if os.path.exists(path):
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
await message.channel.send(f"🌈 Miku's mood has been set to **{new_mood}**!")
|
||||
else:
|
||||
await message.channel.send("⚠️ I don't recognize that mood. Try again with a valid one.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-reset":
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
await message.channel.send("🔄 Miku’s mood has been reset to **neutral**.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-check":
|
||||
await message.channel.send(f"☑️ Miku’s mood is currently {CURRENT_MOOD}.")
|
||||
|
||||
if AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != CURRENT_MOOD_NAME:
|
||||
|
||||
# Block direct transitions to asleep unless from sleepy
|
||||
if detected == "asleep" and CURRENT_MOOD_NAME != "sleepy":
|
||||
print("❌ Ignoring asleep mood; Miku wasn't sleepy before.")
|
||||
else:
|
||||
PREVIOUS_MOOD_NAME = CURRENT_MOOD_NAME
|
||||
CURRENT_MOOD_NAME = detected
|
||||
CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
if detected == "asleep":
|
||||
IS_SLEEPING = True
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600) # 1 hour
|
||||
IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
if message.content.lower().strip() == "!miku sleep" and CURRENT_MOOD_NAME == "sleepy":
|
||||
CURRENT_MOOD_NAME = "asleep"
|
||||
CURRENT_MOOD = load_mood_description("asleep")
|
||||
PREVIOUS_MOOD_NAME = "sleepy"
|
||||
IS_SLEEPING = True
|
||||
await message.channel.send("Yaaawn... Okay... Goodnight~ 💫")
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600)
|
||||
IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
return
|
||||
|
||||
if message.content.lower().strip() == "!miku wake" and CURRENT_MOOD_NAME == "asleep":
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
PREVIOUS_MOOD_NAME = "asleep"
|
||||
IS_SLEEPING = False
|
||||
await message.channel.send("Rise and shine, good morning! 🌞")
|
||||
await set_sleep_state(False)
|
||||
return
|
||||
|
||||
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
656
backups/2025-12-07/.bak.bot.py.260625-2
Normal file
656
backups/2025-12-07/.bak.bot.py.260625-2
Normal file
@@ -0,0 +1,656 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from commands import handle_command
|
||||
from utils import load_mood_description
|
||||
import globals
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
if globals.current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{globals.OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
globals.current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or globals.client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"asleep": [
|
||||
"good night", "goodnight", "sweet dreams", "going to bed", "I will go to bed", "zzz~", "sleep tight"
|
||||
],
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
if mood == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print(f"❎ Mood 'asleep' skipped - mood isn't 'sleepy', it's '{globals.CURRENT_MOOD_NAME}'")
|
||||
continue # Only allow transition to asleep from sleepy
|
||||
|
||||
for phrase in phrases:
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
async def set_sleep_state(sleeping: bool):
|
||||
for guild in globals.client.guilds:
|
||||
me = guild.get_member(globals.BOT_USER.id)
|
||||
if me is not None:
|
||||
try:
|
||||
nickname = "Hatsune Miku💤" if sleeping else "Hatsune Miku"
|
||||
await me.edit(nick=nickname)
|
||||
await globals.client.change_presence(status=discord.Status.invisible) if sleeping else await globals.client.change_presence(status=discord.Status.online)
|
||||
except discord.Forbidden:
|
||||
print("⚠️ Missing permission to change nickname in guild:", guild.name)
|
||||
except discord.HTTPException as e:
|
||||
print("⚠️ Failed to change nickname:", e)
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
new_mood = globals.CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == globals.CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(globals.AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
globals.CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(globals.OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = globals.conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {globals.CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
globals.conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
for channel_id in globals.BEDTIME_CHANNEL_IDS:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in globals.kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(globals.HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in globals.KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@globals.client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {globals.client.user}')
|
||||
|
||||
globals.BOT_USER = globals.client.user
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@globals.client.event
|
||||
async def on_message(message):
|
||||
if message.author == globals.client.user:
|
||||
return
|
||||
|
||||
handled, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING = await handle_command(
|
||||
message,
|
||||
set_sleep_state
|
||||
)
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
if globals.IS_SLEEPING:
|
||||
if random.random() < 1/3: # ⅓ chance
|
||||
sleep_talk_lines = [
|
||||
"mnnn... five more minutes... zzz...",
|
||||
"nya... d-don't tickle me there... mm~",
|
||||
"zz... nyaa~ pancakes flying... eep...",
|
||||
"so warm... stay close... zzz...",
|
||||
"huh...? is it morning...? nooo... \*rolls over*",
|
||||
"\*mumbles* pink clouds... and pudding... heehee...",
|
||||
"\*softly snores* zzz... nyuu... mmh..."
|
||||
]
|
||||
response = random.choice(sleep_talk_lines)
|
||||
await message.channel.typing()
|
||||
await asyncio.sleep(random.uniform(1.5, 3.0)) # random delay before replying
|
||||
await message.channel.send(response)
|
||||
else:
|
||||
# No response at all
|
||||
print("😴 Miku is asleep and didn't respond.")
|
||||
return # Skip any further message handling
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if globals.AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != globals.CURRENT_MOOD_NAME:
|
||||
|
||||
# Block direct transitions to asleep unless from sleepy
|
||||
if detected == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print("❌ Ignoring asleep mood; Miku wasn't sleepy before.")
|
||||
else:
|
||||
globals.PREVIOUS_MOOD_NAME = globals.CURRENT_MOOD_NAME
|
||||
globals.CURRENT_MOOD_NAME = detected
|
||||
globals.CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
if detected == "asleep":
|
||||
globals.IS_SLEEPING = True
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600) # 1 hour
|
||||
globals.IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
globals.CURRENT_MOOD_NAME = "neutral"
|
||||
globals.CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
globals.client.run(globals.DISCORD_BOT_TOKEN)
|
||||
19
backups/2025-12-07/.bak.miku_lore.txt
Normal file
19
backups/2025-12-07/.bak.miku_lore.txt
Normal file
@@ -0,0 +1,19 @@
|
||||
Hatsune Miku is a virtual singer created by Crypton Future Media, using Yamaha's Vocaloid voice synthesizer. She debuted in 2007.
|
||||
|
||||
Her character design includes long turquoise twin-tails, a futuristic outfit, and an energetic personality. She is forever 16 years old and very popular in the anime and otaku communities.
|
||||
|
||||
Miku’s favorite food is green onion (negi). She often appears with a leek in fan art and videos.
|
||||
|
||||
Popular Hatsune Miku songs include:
|
||||
- World is Mine (tsundere princess theme)
|
||||
- PoPiPo (vegetable juice chaos)
|
||||
- Tell Your World (emotional connection through music)
|
||||
- Senbonzakura (historical + modern fusion)
|
||||
- Melt (shy crush vibes)
|
||||
- The Disappearance of Hatsune Miku (fast, intense vocals)
|
||||
|
||||
Miku has performed concerts around the world as a hologram.
|
||||
|
||||
She’s the face of countless fan creations — music, art, games, and more.
|
||||
|
||||
Miku sometimes refers to herself in third person and ends messages with emojis like 🎶💙🌱.
|
||||
348
backups/2025-12-07/autonomous_wip.py
Normal file
348
backups/2025-12-07/autonomous_wip.py
Normal file
@@ -0,0 +1,348 @@
|
||||
# autonomous.py
|
||||
|
||||
import random
|
||||
import time
|
||||
import json
|
||||
import os
|
||||
from datetime import datetime
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import Status
|
||||
from discord import TextChannel
|
||||
from difflib import SequenceMatcher
|
||||
import globals
|
||||
from utils.llm import query_llama
|
||||
from utils.moods import MOOD_EMOJIS
|
||||
from utils.twitter_fetcher import fetch_miku_tweets
|
||||
from utils.image_handling import analyze_image_with_qwen, download_and_encode_image
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
_last_autonomous_messages = [] # rotating buffer of last general messages
|
||||
MAX_HISTORY = 10
|
||||
_last_user_engagements = {} # user_id -> timestamp
|
||||
|
||||
LAST_SENT_TWEETS_FILE = "memory/last_sent_tweets.json"
|
||||
LAST_SENT_TWEETS = []
|
||||
|
||||
AUTONOMOUS_CONFIG_FILE = "memory/autonomous_config.json"
|
||||
|
||||
def load_autonomous_config():
|
||||
if os.path.exists(AUTONOMOUS_CONFIG_FILE):
|
||||
with open(AUTONOMOUS_CONFIG_FILE, "r", encoding="utf-8") as f:
|
||||
return json.load(f)
|
||||
return {}
|
||||
|
||||
def save_autonomous_config(config):
|
||||
with open(AUTONOMOUS_CONFIG_FILE, "w", encoding="utf-8") as f:
|
||||
json.dump(config, f, indent=2)
|
||||
|
||||
def setup_autonomous_speaking():
|
||||
scheduler.add_job(run_autonomous_for_all_guilds, "interval", minutes=10)
|
||||
scheduler.add_job(run_conversation_detection_all_guilds, "interval", minutes=3)
|
||||
scheduler.start()
|
||||
print("🤖 Autonomous Miku is active!")
|
||||
|
||||
async def run_autonomous_for_all_guilds():
|
||||
config = load_autonomous_config()
|
||||
for guild_id, settings in config.items():
|
||||
await miku_autonomous_tick(guild_id, settings)
|
||||
|
||||
async def run_conversation_detection_all_guilds():
|
||||
config = load_autonomous_config()
|
||||
for guild_id, settings in config.items():
|
||||
await miku_detect_and_join_conversation(guild_id, settings)
|
||||
|
||||
async def miku_autonomous_tick(guild_id, settings, action_type="general", force=False, force_action=None):
|
||||
settings = globals.GUILD_SETTINGS.get(guild_id)
|
||||
if not settings:
|
||||
print(f"⚠️ No settings found for guild {guild_id}")
|
||||
return
|
||||
|
||||
if not force and random.random() > 0.2: # 20% chance to act
|
||||
return
|
||||
|
||||
# TODO edit this function as per ChatGPT's last reply and then go back to the long reply from step 5 onwards
|
||||
|
||||
if force_action:
|
||||
action_type = force_action
|
||||
else:
|
||||
action_type = random.choice(["general", "engage_user", "share_tweet"])
|
||||
|
||||
if action_type == "general":
|
||||
await miku_say_something_general(guild_id, settings)
|
||||
elif action_type == "engage_user":
|
||||
await miku_engage_random_user(guild_id, settings)
|
||||
else:
|
||||
await share_miku_tweet(guild_id, settings)
|
||||
|
||||
async def miku_say_something_general(guild_id, settings):
|
||||
channel = globals.client.get_channel(int(settings["autonomous_channel_id"]))
|
||||
if not channel:
|
||||
print(f"⚠️ Autonomous channel not found for guild {guild_id}")
|
||||
return
|
||||
|
||||
mood = settings.get("mood", "curious")
|
||||
time_of_day = get_time_of_day()
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
history_summary = "\n".join(f"- {msg}" for msg in _last_autonomous_messages[-5:]) if _last_autonomous_messages else "None yet."
|
||||
|
||||
prompt = (
|
||||
f"Miku is feeling {mood}. It's currently {time_of_day}. "
|
||||
f"Write a short, natural message that Miku might say out of the blue in a chat. "
|
||||
f"She might greet everyone, make a cute observation, ask a silly question, or say something funny. "
|
||||
f"Make sure it feels casual and spontaneous, like a real person might say.\n\n"
|
||||
f"Here are some things Miku recently said, do not repeat them or say anything too similar:\n{history_summary}"
|
||||
)
|
||||
|
||||
for attempt in range(3): # retry up to 3 times if message is too similar
|
||||
message = await query_llama(prompt, user_id=f"miku-general-{int(time.time())}", guild_id=guild_id, response_type="autonomous_general")
|
||||
if not is_too_similar(message, _last_autonomous_messages):
|
||||
break
|
||||
print("🔁 Response was too similar to past messages, retrying...")
|
||||
|
||||
try:
|
||||
await channel.send(message)
|
||||
print(f"💬 Miku said something general in #{channel.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send autonomous message: {e}")
|
||||
|
||||
async def miku_engage_random_user(guild_id, settings):
|
||||
guild = globals.client.get_guild(guild_id)
|
||||
if not guild:
|
||||
print(f"⚠️ Guild {guild_id} not found.")
|
||||
return
|
||||
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not channel:
|
||||
print("⚠️ Autonomous channel not found.")
|
||||
return
|
||||
|
||||
members = [
|
||||
m for m in guild.members
|
||||
if m.status in {Status.online, Status.idle, Status.dnd} and not m.bot
|
||||
]
|
||||
|
||||
time_of_day = get_time_of_day()
|
||||
|
||||
# Include the invisible user except during late night
|
||||
specific_user_id = 214857593045254151 # Your invisible user's ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user:
|
||||
if specific_user.status != Status.offline or "late night" not in time_of_day:
|
||||
if specific_user not in members:
|
||||
members.append(specific_user)
|
||||
|
||||
if not members:
|
||||
print("😴 No available members to talk to.")
|
||||
return
|
||||
|
||||
target = random.choice(members)
|
||||
|
||||
now = time.time()
|
||||
last_time = _last_user_engagements.get(target.id, 0)
|
||||
if now - last_time < 43200: # 12 hours in seconds
|
||||
print(f"⏱️ Recently engaged {target.display_name}, switching to general message.")
|
||||
await miku_say_something_general()
|
||||
return
|
||||
|
||||
activity_name = None
|
||||
if target.activities:
|
||||
for a in target.activities:
|
||||
if hasattr(a, 'name') and a.name:
|
||||
activity_name = a.name
|
||||
break
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
is_invisible = target.status == Status.offline
|
||||
display_name = target.display_name
|
||||
|
||||
prompt = (
|
||||
f"Miku is feeling {mood} {emoji} during the {time_of_day}. "
|
||||
f"She notices {display_name}'s current status is {target.status.name}. "
|
||||
)
|
||||
|
||||
if is_invisible:
|
||||
prompt += (
|
||||
f"Miku suspects that {display_name} is being sneaky and invisible 👻. "
|
||||
f"She wants to playfully call them out in a fun, teasing, but still affectionate way. "
|
||||
)
|
||||
elif activity_name:
|
||||
prompt += (
|
||||
f"They appear to be playing or doing: {activity_name}. "
|
||||
f"Miku wants to comment on this and start a friendly conversation."
|
||||
)
|
||||
else:
|
||||
prompt += (
|
||||
f"Miku wants to casually start a conversation with them, maybe ask how they're doing, what they're up to, or even talk about something random with them."
|
||||
)
|
||||
|
||||
prompt += (
|
||||
f"\nThe message should be short and reflect Miku’s current mood."
|
||||
)
|
||||
|
||||
try:
|
||||
message = await query_llama(prompt, user_id=f"miku-engage-{int(time.time())}", guild_id=guild_id, response_type="autonomous_general")
|
||||
await channel.send(f"{target.mention} {message}")
|
||||
print(f"👤 Miku engaged {display_name}")
|
||||
_last_user_engagements[target.id] = time.time()
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to engage user: {e}")
|
||||
|
||||
async def miku_detect_and_join_conversation():
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not isinstance(channel, TextChannel):
|
||||
print("⚠️ Autonomous channel is invalid or not found.")
|
||||
return
|
||||
|
||||
# Fetch last 20 messages (for filtering)
|
||||
try:
|
||||
messages = [msg async for msg in channel.history(limit=20)]
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to fetch channel history: {e}")
|
||||
return
|
||||
|
||||
# Filter to messages in last 10 minutes from real users (not bots)
|
||||
recent_msgs = [
|
||||
msg for msg in messages
|
||||
if not msg.author.bot
|
||||
and (datetime.now(msg.created_at.tzinfo) - msg.created_at).total_seconds() < 600
|
||||
]
|
||||
|
||||
user_ids = set(msg.author.id for msg in recent_msgs)
|
||||
|
||||
if len(recent_msgs) < 5 or len(user_ids) < 2:
|
||||
# Not enough activity
|
||||
return
|
||||
|
||||
if random.random() > 0.5:
|
||||
return # 50% chance to engage
|
||||
|
||||
# Use last 10 messages for context (oldest to newest)
|
||||
convo_lines = reversed(recent_msgs[:10])
|
||||
history_text = "\n".join(
|
||||
f"{msg.author.display_name}: {msg.content}" for msg in convo_lines
|
||||
)
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
prompt = (
|
||||
f"Miku is watching a conversation happen in the chat. Her current mood is {mood} {emoji}. "
|
||||
f"She wants to say something relevant, playful, or insightful based on what people are talking about.\n\n"
|
||||
f"Here's the conversation:\n{history_text}\n\n"
|
||||
f"Write a short reply that feels natural and adds to the discussion. It should reflect Miku’s mood and personality."
|
||||
)
|
||||
|
||||
try:
|
||||
reply = await query_llama(prompt, user_id=f"miku-chat-{int(time.time())}", guild_id=guild_id, response_type="conversation_join")
|
||||
await channel.send(reply)
|
||||
print(f"💬 Miku joined an ongoing conversation.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to interject in conversation: {e}")
|
||||
|
||||
async def share_miku_tweet(guild_id, settings):
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
tweets = await fetch_miku_tweets(limit=5)
|
||||
if not tweets:
|
||||
print("📭 No good tweets found.")
|
||||
return
|
||||
|
||||
fresh_tweets = [t for t in tweets if t["url"] not in LAST_SENT_TWEETS]
|
||||
|
||||
if not fresh_tweets:
|
||||
print("⚠️ All fetched tweets were recently sent. Reusing tweets.")
|
||||
fresh_tweets = tweets
|
||||
|
||||
tweet = random.choice(fresh_tweets)
|
||||
|
||||
LAST_SENT_TWEETS.append(tweet["url"])
|
||||
if len(LAST_SENT_TWEETS) > 50:
|
||||
LAST_SENT_TWEETS.pop(0)
|
||||
|
||||
save_last_sent_tweets()
|
||||
|
||||
# Prepare prompt
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
base_prompt = f"Here's a tweet from @{tweet['username']}:\n\n{tweet['text']}\n\nComment on it in a fun Miku style! Miku's current mood is {mood} {emoji}. Make sure the comment reflects Miku's mood and personality."
|
||||
|
||||
# Optionally analyze first image
|
||||
first_img_url = tweet["media"][0]
|
||||
base64_img = await download_and_encode_image(first_img_url)
|
||||
if base64_img:
|
||||
img_desc = await analyze_image_with_qwen(base64_img)
|
||||
base_prompt += f"\n\nThe image looks like this: {img_desc}"
|
||||
|
||||
miku_comment = await query_llama(base_prompt, user_id="autonomous", guild_id=guild_id, response_type="autonomous_tweet")
|
||||
|
||||
# Post to Discord
|
||||
# Convert to fxtwitter for better embeds
|
||||
fx_tweet_url = tweet['url'].replace("twitter.com", "fxtwitter.com").replace("x.com", "fxtwitter.com")
|
||||
await channel.send(f"{fx_tweet_url}")
|
||||
await channel.send(miku_comment)
|
||||
|
||||
async def handle_custom_prompt(user_prompt: str):
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not channel:
|
||||
print("⚠️ Autonomous channel not found.")
|
||||
return False
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
time_of_day = get_time_of_day()
|
||||
|
||||
# Wrap user’s idea in Miku context
|
||||
prompt = (
|
||||
f"Miku is feeling {mood} {emoji} during the {time_of_day}. "
|
||||
f"She has been instructed to: \"{user_prompt.strip()}\"\n\n"
|
||||
f"Write a short, natural message as Miku that follows this instruction. "
|
||||
f"Make it feel spontaneous, emotionally in character, and aligned with her mood and personality. Decide if the time of day is relevant to this request or not and if it is not, do not mention it."
|
||||
)
|
||||
|
||||
try:
|
||||
message = await query_llama(prompt, user_id=f"manual-{int(time.time())}", guild_id=None, response_type="autonomous_general")
|
||||
await channel.send(message)
|
||||
print("🎤 Miku responded to custom prompt.")
|
||||
_last_autonomous_messages.append(message)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"❌ Failed to send custom autonomous message: {e}")
|
||||
return False
|
||||
|
||||
def load_last_sent_tweets():
|
||||
global LAST_SENT_TWEETS
|
||||
if os.path.exists(LAST_SENT_TWEETS_FILE):
|
||||
try:
|
||||
with open(LAST_SENT_TWEETS_FILE, "r", encoding="utf-8") as f:
|
||||
LAST_SENT_TWEETS = json.load(f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to load last sent tweets: {e}")
|
||||
LAST_SENT_TWEETS = []
|
||||
else:
|
||||
LAST_SENT_TWEETS = []
|
||||
|
||||
def save_last_sent_tweets():
|
||||
try:
|
||||
with open(LAST_SENT_TWEETS_FILE, "w", encoding="utf-8") as f:
|
||||
json.dump(LAST_SENT_TWEETS, f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to save last sent tweets: {e}")
|
||||
|
||||
def get_time_of_day():
|
||||
hour = datetime.now().hour + 3
|
||||
if 5 <= hour < 12:
|
||||
return "morning"
|
||||
elif 12 <= hour < 18:
|
||||
return "afternoon"
|
||||
elif 18 <= hour < 22:
|
||||
return "evening"
|
||||
return "late night. Miku wonders if anyone is still awake"
|
||||
|
||||
def is_too_similar(new_message, history, threshold=0.85):
|
||||
for old in history:
|
||||
ratio = SequenceMatcher(None, new_message.lower(), old.lower()).ratio()
|
||||
if ratio > threshold:
|
||||
return True
|
||||
return False
|
||||
464
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py
Normal file
464
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py
Normal file
@@ -0,0 +1,464 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if re.search(r'^(miku,)|((, miku)[\?\!\.\s,]*)$', message.content.strip(), re.IGNORECASE) or ", miku," in message.content.lower():
|
||||
|
||||
# Clean the prompt
|
||||
if text.lower().startswith("miku, "):
|
||||
prompt = text[6:].strip()
|
||||
else:
|
||||
prompt = re.sub(r', miku[\?\!\.\s]*$', '', text, flags=re.IGNORECASE).strip()
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
#await message.channel.send("Looking at the image... 🎨")
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
prompt = message.content[5:].strip()
|
||||
#await message.channel.send("Thinking... 🎶")
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
await message.channel.send(response)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
540
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.250625
Normal file
540
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.250625
Normal file
@@ -0,0 +1,540 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
665
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625
Normal file
665
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625
Normal file
@@ -0,0 +1,665 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
AUTO_MOOD = True
|
||||
CURRENT_MOOD = "neutral"
|
||||
AVAILABLE_MOODS = [
|
||||
"bubbly", "sleepy", "curious", "shy", "serious", "excited",
|
||||
"melancholy", "flirty", "romantic", "irritated", "angry", "neutral"
|
||||
]
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
def load_mood_description(mood_name: str) -> str:
|
||||
path = os.path.join("moods", f"{mood_name}.txt")
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
except FileNotFoundError:
|
||||
print(f"⚠️ Mood file '{mood_name}' not found. Falling back to default.")
|
||||
return load_mood_description("neutral")
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
for phrase in phrases:
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
global CURRENT_MOOD
|
||||
|
||||
new_mood = CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if message.content.startswith("!miku mood "):
|
||||
new_mood = message.content.split("!miku mood ")[1].strip().lower()
|
||||
path = os.path.join("moods", f"{new_mood}.txt")
|
||||
if os.path.exists(path):
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
await message.channel.send(f"🌈 Miku's mood has been set to **{new_mood}**!")
|
||||
else:
|
||||
await message.channel.send("⚠️ I don't recognize that mood. Try again with a valid one.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-reset":
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
await message.channel.send("🔄 Miku’s mood has been reset to **neutral**.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-check":
|
||||
await message.channel.send(f"☑️ Miku’s mood is currently {CURRENT_MOOD}.")
|
||||
|
||||
if AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != CURRENT_MOOD:
|
||||
CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
728
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625-1
Normal file
728
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625-1
Normal file
@@ -0,0 +1,728 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "mistral")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
AUTO_MOOD = True
|
||||
CURRENT_MOOD = "neutral"
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
PREVIOUS_MOOD_NAME = "neutral"
|
||||
IS_SLEEPING = False
|
||||
AVAILABLE_MOODS = [
|
||||
"bubbly", "sleepy", "curious", "shy", "serious", "excited",
|
||||
"melancholy", "flirty", "romantic", "irritated", "angry", "neutral"
|
||||
]
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
global current_model
|
||||
if current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
def load_mood_description(mood_name: str) -> str:
|
||||
path = os.path.join("moods", f"{mood_name}.txt")
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
except FileNotFoundError:
|
||||
print(f"⚠️ Mood file '{mood_name}' not found. Falling back to default.")
|
||||
return load_mood_description("neutral")
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
],
|
||||
"asleep": [
|
||||
"goodnight", "sweet dreams", "going to bed", "I will go to bed", "zzz~", "sleep tight"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
for phrase in phrases:
|
||||
if mood == "asleep" and CURRENT_MOOD_NAME != "sleepy":
|
||||
continue # Only allow transition to asleep from sleepy
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
async def set_sleep_state(sleeping: bool):
|
||||
if sleeping:
|
||||
await client.change_presence(status=discord.Status.invisible)
|
||||
await client.user.edit(username="Hatsune Miku💤")
|
||||
print("😴 Miku has gone to sleep.")
|
||||
else:
|
||||
await client.change_presence(status=discord.Status.online)
|
||||
await client.user.edit(username="Hatsune Miku")
|
||||
print("☀️ Miku woke up.")
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
global CURRENT_MOOD
|
||||
|
||||
new_mood = CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
global CURRENT_MOOD
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(OLLAMA_MODEL)
|
||||
|
||||
for channel_id in BEDTIME_CHANNEL_IDS:
|
||||
channel = client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {client.user}')
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@client.event
|
||||
async def on_message(message):
|
||||
if message.author == client.user:
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
global CURRENT_MOOD, CURRENT_MOOD_NAME, PREVIOUS_MOOD_NAME, IS_SLEEPING
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
if IS_SLEEPING:
|
||||
await message.channel.send("💤 Miku is currently sleeping and can't talk right now. Try again later~")
|
||||
return
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
if message.content.lower().strip() == "!reset":
|
||||
conversation_history[str(message.author.id)].clear()
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if message.content.startswith("!miku mood "):
|
||||
new_mood = message.content.split("!miku mood ")[1].strip().lower()
|
||||
path = os.path.join("moods", f"{new_mood}.txt")
|
||||
if os.path.exists(path):
|
||||
CURRENT_MOOD = load_mood_description(new_mood)
|
||||
await message.channel.send(f"🌈 Miku's mood has been set to **{new_mood}**!")
|
||||
else:
|
||||
await message.channel.send("⚠️ I don't recognize that mood. Try again with a valid one.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-reset":
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
await message.channel.send("🔄 Miku’s mood has been reset to **neutral**.")
|
||||
return
|
||||
|
||||
if message.content.strip().lower() == "!miku mood-check":
|
||||
await message.channel.send(f"☑️ Miku’s mood is currently {CURRENT_MOOD}.")
|
||||
|
||||
if AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != CURRENT_MOOD_NAME:
|
||||
|
||||
# Block direct transitions to asleep unless from sleepy
|
||||
if detected == "asleep" and CURRENT_MOOD_NAME != "sleepy":
|
||||
print("❌ Ignoring asleep mood; Miku wasn't sleepy before.")
|
||||
else:
|
||||
PREVIOUS_MOOD_NAME = CURRENT_MOOD_NAME
|
||||
CURRENT_MOOD_NAME = detected
|
||||
CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
if detected == "asleep":
|
||||
IS_SLEEPING = True
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600) # 1 hour
|
||||
IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
if message.content.lower().strip() == "!miku sleep" and CURRENT_MOOD_NAME == "sleepy":
|
||||
CURRENT_MOOD_NAME = "asleep"
|
||||
CURRENT_MOOD = load_mood_description("asleep")
|
||||
PREVIOUS_MOOD_NAME = "sleepy"
|
||||
IS_SLEEPING = True
|
||||
await message.channel.send("Yaaawn... Okay... Goodnight~ 💫")
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600)
|
||||
IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
return
|
||||
|
||||
if message.content.lower().strip() == "!miku wake" and CURRENT_MOOD_NAME == "asleep":
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
CURRENT_MOOD = load_mood_description("neutral")
|
||||
PREVIOUS_MOOD_NAME = "asleep"
|
||||
IS_SLEEPING = False
|
||||
await message.channel.send("Rise and shine, good morning! 🌞")
|
||||
await set_sleep_state(False)
|
||||
return
|
||||
|
||||
|
||||
|
||||
client.run(DISCORD_BOT_TOKEN)
|
||||
656
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625-2
Normal file
656
backups/2025-12-07/old-bot-bak-80825/.bak.bot.py.260625-2
Normal file
@@ -0,0 +1,656 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import random
|
||||
import string
|
||||
|
||||
import base64
|
||||
import subprocess
|
||||
import aiofiles
|
||||
|
||||
from commands import handle_command
|
||||
from utils import load_mood_description
|
||||
import globals
|
||||
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from langchain.text_splitter import CharacterTextSplitter
|
||||
from langchain_community.docstore.document import Document
|
||||
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import File
|
||||
from discord import Status
|
||||
from discord.ext import tasks
|
||||
import datetime
|
||||
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
|
||||
# Switch model
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
if globals.current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{globals.OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
globals.current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or globals.client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
# Detect mood cues from Miku's response
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"asleep": [
|
||||
"good night", "goodnight", "sweet dreams", "going to bed", "I will go to bed", "zzz~", "sleep tight"
|
||||
],
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG!", "this is amazing", "i’m so hyped", "YAY!!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
if mood == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print(f"❎ Mood 'asleep' skipped - mood isn't 'sleepy', it's '{globals.CURRENT_MOOD_NAME}'")
|
||||
continue # Only allow transition to asleep from sleepy
|
||||
|
||||
for phrase in phrases:
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
async def set_sleep_state(sleeping: bool):
|
||||
for guild in globals.client.guilds:
|
||||
me = guild.get_member(globals.BOT_USER.id)
|
||||
if me is not None:
|
||||
try:
|
||||
nickname = "Hatsune Miku💤" if sleeping else "Hatsune Miku"
|
||||
await me.edit(nick=nickname)
|
||||
await globals.client.change_presence(status=discord.Status.invisible) if sleeping else await globals.client.change_presence(status=discord.Status.online)
|
||||
except discord.Forbidden:
|
||||
print("⚠️ Missing permission to change nickname in guild:", guild.name)
|
||||
except discord.HTTPException as e:
|
||||
print("⚠️ Failed to change nickname:", e)
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
new_mood = globals.CURRENT_MOOD
|
||||
attempts = 0
|
||||
while new_mood == globals.CURRENT_MOOD and attempts < 5:
|
||||
new_mood = random.choice(globals.AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
globals.CURRENT_MOOD = load_mood_description(new_mood)
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood}")
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(globals.OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Build conversation history
|
||||
history = globals.conversation_history[user_id]
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {globals.CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
globals.conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
for channel_id in globals.BEDTIME_CHANNEL_IDS:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id="bedtime-miku")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in globals.kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(globals.HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in globals.KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
|
||||
@globals.client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {globals.client.user}')
|
||||
|
||||
globals.BOT_USER = globals.client.user
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=7, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
scheduler.add_job(schedule_random_bedtime, 'cron', hour=0, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)
|
||||
|
||||
scheduler.start()
|
||||
|
||||
@globals.client.event
|
||||
async def on_message(message):
|
||||
if message.author == globals.client.user:
|
||||
return
|
||||
|
||||
handled, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING = await handle_command(
|
||||
message,
|
||||
set_sleep_state
|
||||
)
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
if globals.IS_SLEEPING:
|
||||
if random.random() < 1/3: # ⅓ chance
|
||||
sleep_talk_lines = [
|
||||
"mnnn... five more minutes... zzz...",
|
||||
"nya... d-don't tickle me there... mm~",
|
||||
"zz... nyaa~ pancakes flying... eep...",
|
||||
"so warm... stay close... zzz...",
|
||||
"huh...? is it morning...? nooo... \*rolls over*",
|
||||
"\*mumbles* pink clouds... and pudding... heehee...",
|
||||
"\*softly snores* zzz... nyuu... mmh..."
|
||||
]
|
||||
response = random.choice(sleep_talk_lines)
|
||||
await message.channel.typing()
|
||||
await asyncio.sleep(random.uniform(1.5, 3.0)) # random delay before replying
|
||||
await message.channel.send(response)
|
||||
else:
|
||||
# No response at all
|
||||
print("😴 Miku is asleep and didn't respond.")
|
||||
return # Skip any further message handling
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if globals.AUTO_MOOD and 'response' in locals():
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != globals.CURRENT_MOOD_NAME:
|
||||
|
||||
# Block direct transitions to asleep unless from sleepy
|
||||
if detected == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print("❌ Ignoring asleep mood; Miku wasn't sleepy before.")
|
||||
else:
|
||||
globals.PREVIOUS_MOOD_NAME = globals.CURRENT_MOOD_NAME
|
||||
globals.CURRENT_MOOD_NAME = detected
|
||||
globals.CURRENT_MOOD = load_mood_description(detected)
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
if detected == "asleep":
|
||||
globals.IS_SLEEPING = True
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600) # 1 hour
|
||||
globals.IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
globals.CURRENT_MOOD_NAME = "neutral"
|
||||
globals.CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
globals.client.run(globals.DISCORD_BOT_TOKEN)
|
||||
19
backups/2025-12-07/old-bot-bak-80825/.bak.miku_lore.txt
Normal file
19
backups/2025-12-07/old-bot-bak-80825/.bak.miku_lore.txt
Normal file
@@ -0,0 +1,19 @@
|
||||
Hatsune Miku is a virtual singer created by Crypton Future Media, using Yamaha's Vocaloid voice synthesizer. She debuted in 2007.
|
||||
|
||||
Her character design includes long turquoise twin-tails, a futuristic outfit, and an energetic personality. She is forever 16 years old and very popular in the anime and otaku communities.
|
||||
|
||||
Miku’s favorite food is green onion (negi). She often appears with a leek in fan art and videos.
|
||||
|
||||
Popular Hatsune Miku songs include:
|
||||
- World is Mine (tsundere princess theme)
|
||||
- PoPiPo (vegetable juice chaos)
|
||||
- Tell Your World (emotional connection through music)
|
||||
- Senbonzakura (historical + modern fusion)
|
||||
- Melt (shy crush vibes)
|
||||
- The Disappearance of Hatsune Miku (fast, intense vocals)
|
||||
|
||||
Miku has performed concerts around the world as a hologram.
|
||||
|
||||
She’s the face of countless fan creations — music, art, games, and more.
|
||||
|
||||
Miku sometimes refers to herself in third person and ends messages with emojis like 🎶💙🌱.
|
||||
36
backups/2025-12-07/old-bot-bak-80825/Dockerfile
Normal file
36
backups/2025-12-07/old-bot-bak-80825/Dockerfile
Normal file
@@ -0,0 +1,36 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY requirements.txt .
|
||||
RUN pip install -r requirements.txt
|
||||
RUN playwright install
|
||||
|
||||
RUN apt-get update && apt-get install -y \
|
||||
ffmpeg \
|
||||
libsm6 \
|
||||
libxext6 \
|
||||
libxcomposite1 \
|
||||
libxdamage1 \
|
||||
libgtk-3-0 \
|
||||
libgdk3.0-cil \
|
||||
libatk1.0-0 \
|
||||
&& apt-get clean \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
COPY bot.py .
|
||||
COPY command_router.py .
|
||||
COPY utils /app/utils
|
||||
COPY commands /app/commands
|
||||
COPY memory /app/memory
|
||||
COPY static /app/static
|
||||
COPY globals.py .
|
||||
COPY api.py .
|
||||
COPY api_main.py .
|
||||
COPY miku_lore.txt .
|
||||
COPY miku_prompt.txt .
|
||||
COPY miku_lyrics.txt .
|
||||
COPY MikuMikuBeam.mp4 .
|
||||
COPY moods /app/moods/
|
||||
|
||||
CMD ["python", "-u", "bot.py"]
|
||||
BIN
backups/2025-12-07/old-bot-bak-80825/MikuMikuBeam.mp4
Normal file
BIN
backups/2025-12-07/old-bot-bak-80825/MikuMikuBeam.mp4
Normal file
Binary file not shown.
207
backups/2025-12-07/old-bot-bak-80825/api.py
Normal file
207
backups/2025-12-07/old-bot-bak-80825/api.py
Normal file
@@ -0,0 +1,207 @@
|
||||
# api.py
|
||||
|
||||
from fastapi import (
|
||||
FastAPI,
|
||||
Query,
|
||||
BackgroundTasks,
|
||||
Request, UploadFile,
|
||||
File,
|
||||
Form
|
||||
)
|
||||
from typing import List
|
||||
from pydantic import BaseModel
|
||||
import globals
|
||||
from commands.actions import (
|
||||
force_sleep,
|
||||
wake_up,
|
||||
set_mood,
|
||||
reset_mood,
|
||||
check_mood,
|
||||
calm_miku,
|
||||
reset_conversation,
|
||||
send_bedtime_now
|
||||
)
|
||||
from utils.moods import nickname_mood_emoji
|
||||
from utils.autonomous import (
|
||||
miku_autonomous_tick,
|
||||
miku_say_something_general,
|
||||
miku_engage_random_user,
|
||||
share_miku_tweet,
|
||||
handle_custom_prompt
|
||||
)
|
||||
import asyncio
|
||||
import nest_asyncio
|
||||
import subprocess
|
||||
import io
|
||||
import discord
|
||||
import aiofiles
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
from fastapi.responses import FileResponse, PlainTextResponse
|
||||
nest_asyncio.apply()
|
||||
|
||||
app = FastAPI()
|
||||
|
||||
# Serve static folder
|
||||
app.mount("/static", StaticFiles(directory="static"), name="static")
|
||||
|
||||
# ========== Models ==========
|
||||
class MoodSetRequest(BaseModel):
|
||||
mood: str
|
||||
|
||||
class ConversationResetRequest(BaseModel):
|
||||
user_id: str
|
||||
|
||||
class CustomPromptRequest(BaseModel):
|
||||
prompt: str
|
||||
|
||||
# ========== Routes ==========
|
||||
@app.get("/")
|
||||
def read_index():
|
||||
return FileResponse("static/index.html")
|
||||
|
||||
@app.get("/logs")
|
||||
def get_logs():
|
||||
try:
|
||||
# Read last 100 lines of the log file
|
||||
with open("/app/bot.log", "r", encoding="utf-8") as f:
|
||||
lines = f.readlines()
|
||||
last_100 = lines[-100:]
|
||||
return "".join(lines[-100] if len(lines) >= 100 else lines)
|
||||
except Exception as e:
|
||||
return f"Error reading log file: {e}"
|
||||
|
||||
@app.get("/prompt")
|
||||
def get_last_prompt():
|
||||
return {"prompt": globals.LAST_FULL_PROMPT or "No prompt has been issued yet."}
|
||||
|
||||
@app.get("/mood")
|
||||
def get_current_mood():
|
||||
return {"mood": check_mood()}
|
||||
|
||||
|
||||
@app.post("/mood")
|
||||
async def set_mood_endpoint(data: MoodSetRequest):
|
||||
success = set_mood(data.mood)
|
||||
if success:
|
||||
globals.client.loop.create_task(nickname_mood_emoji())
|
||||
return {"status": "ok", "new_mood": data.mood}
|
||||
return {"status": "error", "message": "Mood not recognized"}
|
||||
|
||||
|
||||
@app.post("/mood/reset")
|
||||
async def reset_mood_endpoint(background_tasks: BackgroundTasks):
|
||||
reset_mood()
|
||||
globals.client.loop.create_task(nickname_mood_emoji())
|
||||
return {"status": "ok", "new_mood": "neutral"}
|
||||
|
||||
|
||||
@app.post("/mood/calm")
|
||||
def calm_miku_endpoint():
|
||||
calm_miku()
|
||||
return {"status": "ok", "message": "Miku has calmed down."}
|
||||
|
||||
|
||||
@app.post("/conversation/reset")
|
||||
def reset_convo(data: ConversationResetRequest):
|
||||
reset_conversation(data.user_id)
|
||||
return {"status": "ok", "message": f"Memory reset for {data.user_id}"}
|
||||
|
||||
|
||||
@app.post("/sleep")
|
||||
async def force_sleep_endpoint():
|
||||
await force_sleep()
|
||||
globals.client.loop.create_task(nickname_mood_emoji())
|
||||
return {"status": "ok", "message": "Miku is now sleeping"}
|
||||
|
||||
|
||||
@app.post("/wake")
|
||||
async def wake_up_endpoint():
|
||||
await wake_up()
|
||||
globals.client.loop.create_task(nickname_mood_emoji())
|
||||
return {"status": "ok", "message": "Miku is now awake"}
|
||||
|
||||
|
||||
@app.post("/bedtime")
|
||||
async def bedtime_endpoint(background_tasks: BackgroundTasks):
|
||||
globals.client.loop.create_task(send_bedtime_now())
|
||||
return {"status": "ok", "message": "Bedtime message sent"}
|
||||
|
||||
@app.post("/autonomous/general")
|
||||
async def trigger_autonomous_general():
|
||||
globals.client.loop.create_task(miku_autonomous_tick(force=True, force_action="general"))
|
||||
return {"status": "ok", "message": "Miku say something general triggered manually"}
|
||||
|
||||
@app.post("/autonomous/engage")
|
||||
async def trigger_autonomous_engage_user():
|
||||
globals.client.loop.create_task(miku_autonomous_tick(force=True, force_action="engage_user"))
|
||||
return {"status": "ok", "message": "Miku engage random user triggered manually"}
|
||||
|
||||
@app.post("/autonomous/tweet")
|
||||
async def trigger_autonomous_tweet():
|
||||
globals.client.loop.create_task(miku_autonomous_tick(force=True, force_action="share_tweet"))
|
||||
return {"status": "ok", "message": "Miku share tweet triggered manually"}
|
||||
|
||||
@app.post("/autonomous/custom")
|
||||
async def custom_autonomous_message(req: CustomPromptRequest):
|
||||
try:
|
||||
asyncio.run_coroutine_threadsafe(
|
||||
handle_custom_prompt(req.prompt), globals.client.loop
|
||||
)
|
||||
return {"success": True, "message": "Miku is working on it!"}
|
||||
except Exception as e:
|
||||
print(f"❌ Error running custom prompt in bot loop: {repr(e)}")
|
||||
return {"success": False, "error": str(e)}
|
||||
|
||||
@app.post("/manual/send")
|
||||
async def manual_send(
|
||||
message: str = Form(...),
|
||||
channel_id: str = Form(...),
|
||||
files: List[UploadFile] = File(default=[])
|
||||
):
|
||||
try:
|
||||
# Get the Discord channel Miku should post in
|
||||
channel = globals.client.get_channel(int(channel_id))
|
||||
if not channel:
|
||||
return {"success": False, "error": "Target channel not found"}
|
||||
|
||||
# Prepare file data (read in the async FastAPI thread)
|
||||
prepared_files = []
|
||||
for f in files:
|
||||
contents = await f.read()
|
||||
prepared_files.append((f.filename, contents))
|
||||
|
||||
# Define a coroutine that will run inside the bot loop
|
||||
async def send_message():
|
||||
channel = globals.client.get_channel(int(channel_id))
|
||||
if not channel:
|
||||
raise ValueError(f"Channel ID {channel_id} not found or bot cannot access it.")
|
||||
|
||||
discord_files = [
|
||||
discord.File(io.BytesIO(content), filename=filename)
|
||||
for filename, content in prepared_files
|
||||
]
|
||||
|
||||
await channel.send(content=message or None, files=discord_files or None)
|
||||
|
||||
# Schedule coroutine in bot's event loop
|
||||
future = asyncio.run_coroutine_threadsafe(send_message(), globals.client.loop)
|
||||
future.result(timeout=10) # Wait max 10 seconds for it to finish
|
||||
|
||||
return {"success": True}
|
||||
|
||||
|
||||
except Exception as e:
|
||||
print(f"❌ Error in /manual/send: {repr(e)}")
|
||||
return {"success": False, "error": str(e)}
|
||||
|
||||
@app.get("/status")
|
||||
def status():
|
||||
return {
|
||||
"mood": globals.CURRENT_MOOD_NAME,
|
||||
"is_sleeping": globals.IS_SLEEPING,
|
||||
"previous_mood": globals.PREVIOUS_MOOD_NAME
|
||||
}
|
||||
|
||||
@app.get("/conversation/{user_id}")
|
||||
def get_conversation(user_id: str):
|
||||
return globals.conversation_history.get(user_id, [])
|
||||
4
backups/2025-12-07/old-bot-bak-80825/api_main.py
Normal file
4
backups/2025-12-07/old-bot-bak-80825/api_main.py
Normal file
@@ -0,0 +1,4 @@
|
||||
import uvicorn
|
||||
|
||||
if __name__ == "__main__":
|
||||
uvicorn.run("api:app", host="0.0.0.0", port=3939, reload=True)
|
||||
257
backups/2025-12-07/old-bot-bak-80825/bot.py
Normal file
257
backups/2025-12-07/old-bot-bak-80825/bot.py
Normal file
@@ -0,0 +1,257 @@
|
||||
import discord
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import random
|
||||
import string
|
||||
import datetime
|
||||
import os
|
||||
import threading
|
||||
import uvicorn
|
||||
import logging
|
||||
import sys
|
||||
from api import app
|
||||
|
||||
from command_router import handle_command
|
||||
from utils.scheduled import (
|
||||
schedule_random_bedtime,
|
||||
send_bedtime_reminder,
|
||||
send_monday_video
|
||||
)
|
||||
from utils.image_handling import (
|
||||
download_and_encode_image,
|
||||
analyze_image_with_qwen,
|
||||
rephrase_as_miku
|
||||
)
|
||||
from utils.core import (
|
||||
is_miku_addressed,
|
||||
)
|
||||
from utils.moods import (
|
||||
detect_mood_shift,
|
||||
set_sleep_state,
|
||||
nickname_mood_emoji,
|
||||
rotate_mood,
|
||||
load_mood_description,
|
||||
clear_angry_mood_after_delay
|
||||
)
|
||||
from utils.media import overlay_username_with_ffmpeg
|
||||
from utils.kindness import detect_and_react_to_kindness
|
||||
from utils.llm import query_ollama
|
||||
from utils.autonomous import setup_autonomous_speaking, load_last_sent_tweets
|
||||
|
||||
import globals
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format="%(asctime)s %(levelname)s: %(message)s",
|
||||
handlers=[
|
||||
logging.FileHandler("bot.log", mode='a', encoding='utf-8'),
|
||||
logging.StreamHandler(sys.stdout) # Optional: see logs in stdout too
|
||||
],
|
||||
force=True # Override previous configs
|
||||
)
|
||||
|
||||
@globals.client.event
|
||||
async def on_ready():
|
||||
print(f'🎤 MikuBot connected as {globals.client.user}')
|
||||
|
||||
globals.BOT_USER = globals.client.user
|
||||
|
||||
# Change mood every 1 hour
|
||||
rotate_mood.start()
|
||||
|
||||
# Schedule the weekly task (Monday 07:30)
|
||||
globals.scheduler.add_job(send_monday_video, 'cron', day_of_week='mon', hour=4, minute=30)
|
||||
|
||||
# Schedule first bedtime reminder
|
||||
schedule_random_bedtime()
|
||||
# Reschedule every midnight
|
||||
globals.scheduler.add_job(schedule_random_bedtime, 'cron', hour=21, minute=0)
|
||||
#scheduler.add_job(send_bedtime_reminder, 'cron', hour=12, minute=22)i
|
||||
|
||||
# Schedule autonomous speaking
|
||||
setup_autonomous_speaking()
|
||||
load_last_sent_tweets()
|
||||
|
||||
globals.scheduler.start()
|
||||
|
||||
@globals.client.event
|
||||
async def on_message(message):
|
||||
if message.author == globals.client.user:
|
||||
return
|
||||
|
||||
handled, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING = await handle_command(
|
||||
message,
|
||||
set_sleep_state
|
||||
)
|
||||
|
||||
if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
|
||||
async with message.channel.typing():
|
||||
# Get replied-to user
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
target_username = replied_msg.author.display_name
|
||||
|
||||
# Prepare video
|
||||
base_video = "MikuMikuBeam.mp4"
|
||||
output_video = f"/tmp/video_{''.join(random.choices(string.ascii_letters, k=5))}.mp4"
|
||||
|
||||
await overlay_username_with_ffmpeg(base_video, output_video, target_username)
|
||||
|
||||
caption = f"Here you go, @{target_username}! 🌟"
|
||||
#await message.channel.send(content=caption, file=discord.File(output_video))
|
||||
await replied_msg.reply(file=discord.File(output_video))
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error processing video: {e}")
|
||||
await message.channel.send("Sorry, something went wrong while generating the video.")
|
||||
return
|
||||
|
||||
text = message.content.strip()
|
||||
|
||||
if await is_miku_addressed(message):
|
||||
|
||||
if globals.IS_SLEEPING:
|
||||
# Initialize sleepy response count if not set yet
|
||||
if globals.SLEEPY_RESPONSES_LEFT is None:
|
||||
globals.SLEEPY_RESPONSES_LEFT = random.randint(3, 5)
|
||||
print(f"🎲 Sleepy responses allowed: {globals.SLEEPY_RESPONSES_LEFT}")
|
||||
|
||||
if globals.SLEEPY_RESPONSES_LEFT > 0:
|
||||
if random.random() < 1/3: # ⅓ chance
|
||||
sleep_talk_lines = [
|
||||
"mnnn... five more minutes... zzz...",
|
||||
"nya... d-don't tickle me there... mm~",
|
||||
"zz... nyaa~ pancakes flying... eep...",
|
||||
"so warm... stay close... zzz...",
|
||||
"huh...? is it morning...? nooo... \*rolls over*",
|
||||
"\*mumbles* pink clouds... and pudding... heehee...",
|
||||
"\*softly snores* zzz... nyuu... mmh..."
|
||||
]
|
||||
response = random.choice(sleep_talk_lines)
|
||||
await message.channel.typing()
|
||||
await asyncio.sleep(random.uniform(1.5, 3.0)) # random delay before replying
|
||||
await message.channel.send(response)
|
||||
globals.SLEEPY_RESPONSES_LEFT -= 1
|
||||
print(f"💤 Sleepy responses left: {globals.SLEEPY_RESPONSES_LEFT}")
|
||||
else:
|
||||
# No response at all
|
||||
print("😴 Miku is asleep and didn't respond.")
|
||||
return # Skip any further message handling
|
||||
else:
|
||||
# Exceeded sleepy response count — wake up angry now!
|
||||
globals.IS_SLEEPING = False
|
||||
globals.CURRENT_MOOD_NAME = "angry"
|
||||
globals.CURRENT_MOOD = load_mood_description("angry")
|
||||
globals.SLEEPY_RESPONSES_LEFT = None
|
||||
|
||||
# Set angry period end time 40 minutes from now
|
||||
globals.FORCED_ANGRY_UNTIL = datetime.datetime.utcnow() + datetime.timedelta(minutes=40)
|
||||
|
||||
# Cancel any existing angry timer task first
|
||||
if globals.ANGRY_WAKEUP_TIMER and not globals.ANGRY_WAKEUP_TIMER.done():
|
||||
globals.ANGRY_WAKEUP_TIMER.cancel()
|
||||
|
||||
# Start cooldown task to clear angry mood after 40 mins
|
||||
globals.ANGRY_WAKEUP_TIMER = asyncio.create_task(clear_angry_mood_after_delay())
|
||||
|
||||
print("😡 Miku woke up angry and will stay angry for 40 minutes!")
|
||||
|
||||
globals.JUST_WOKEN_UP = True # Set flag for next response
|
||||
|
||||
await nickname_mood_emoji()
|
||||
await set_sleep_state(False)
|
||||
|
||||
# Immediately get an angry response to send back
|
||||
try:
|
||||
async with message.channel.typing():
|
||||
angry_response = await query_ollama("...", user_id=str(message.author.id))
|
||||
await message.channel.send(angry_response)
|
||||
finally:
|
||||
# Reset the flag after sending the angry response
|
||||
globals.JUST_WOKEN_UP = False
|
||||
|
||||
return
|
||||
|
||||
prompt = text # No cleanup — keep it raw
|
||||
user_id = str(message.author.id)
|
||||
|
||||
# 1st kindness check with just keywords
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message)
|
||||
|
||||
# Add replied Miku message to conversation history as context
|
||||
if message.reference:
|
||||
try:
|
||||
replied_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if replied_msg.author == globals.client.user:
|
||||
history = globals.conversation_history.get(user_id, [])
|
||||
if not history or (history and history[-1][1] != replied_msg.content):
|
||||
globals.conversation_history.setdefault(user_id, []).append(("", replied_msg.content))
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to fetch replied message for context: {e}")
|
||||
|
||||
async with message.channel.typing():
|
||||
# If message has an image attachment
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if any(attachment.filename.lower().endswith(ext) for ext in [".jpg", ".jpeg", ".png", ".webp"]):
|
||||
|
||||
base64_img = await download_and_encode_image(attachment.url)
|
||||
if not base64_img:
|
||||
await message.channel.send("I couldn't load the image, sorry!")
|
||||
return
|
||||
# Analyze image (objective description)
|
||||
qwen_description = await analyze_image_with_qwen(base64_img)
|
||||
miku_reply = await rephrase_as_miku(qwen_description, prompt)
|
||||
|
||||
await message.channel.send(miku_reply)
|
||||
return
|
||||
|
||||
# If message is just a prompt, no image
|
||||
response = await query_ollama(prompt, user_id=str(message.author.id))
|
||||
|
||||
await message.channel.send(response)
|
||||
|
||||
# 2nd kindness check (only if no keywords detected)
|
||||
if globals.CURRENT_MOOD not in ["angry", "irritated"]:
|
||||
await detect_and_react_to_kindness(message, after_reply=True)
|
||||
|
||||
# Manual Monday test command
|
||||
if message.content.lower().strip() == "!monday":
|
||||
await send_monday_video()
|
||||
#await message.channel.send("✅ Monday message sent (or attempted). Check logs.")
|
||||
return
|
||||
|
||||
if globals.AUTO_MOOD and 'response' in locals():
|
||||
# Block auto mood updates if forced angry period is active
|
||||
now = datetime.datetime.utcnow()
|
||||
if globals.FORCED_ANGRY_UNTIL and now < globals.FORCED_ANGRY_UNTIL:
|
||||
print("🚫 Skipping auto mood detection — forced angry period active.")
|
||||
else:
|
||||
detected = detect_mood_shift(response)
|
||||
if detected and detected != globals.CURRENT_MOOD_NAME:
|
||||
|
||||
# Block direct transitions to asleep unless from sleepy
|
||||
if detected == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print("❌ Ignoring asleep mood; Miku wasn't sleepy before.")
|
||||
else:
|
||||
globals.PREVIOUS_MOOD_NAME = globals.CURRENT_MOOD_NAME
|
||||
globals.CURRENT_MOOD_NAME = detected
|
||||
globals.CURRENT_MOOD = load_mood_description(detected)
|
||||
await nickname_mood_emoji()
|
||||
print(f"🔄 Auto-updated mood to: {detected}")
|
||||
|
||||
if detected == "asleep":
|
||||
globals.IS_SLEEPING = True
|
||||
await set_sleep_state(True)
|
||||
await asyncio.sleep(3600) # 1 hour
|
||||
globals.IS_SLEEPING = False
|
||||
await set_sleep_state(False)
|
||||
globals.CURRENT_MOOD_NAME = "neutral"
|
||||
globals.CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
def start_api():
|
||||
uvicorn.run(app, host="0.0.0.0", port=3939, log_level="info")
|
||||
|
||||
threading.Thread(target=start_api, daemon=True).start()
|
||||
globals.client.run(globals.DISCORD_BOT_TOKEN)
|
||||
72
backups/2025-12-07/old-bot-bak-80825/command_router.py
Normal file
72
backups/2025-12-07/old-bot-bak-80825/command_router.py
Normal file
@@ -0,0 +1,72 @@
|
||||
from commands.actions import (
|
||||
force_sleep,
|
||||
wake_up,
|
||||
set_mood,
|
||||
reset_mood,
|
||||
check_mood,
|
||||
calm_miku,
|
||||
reset_conversation,
|
||||
send_bedtime_now
|
||||
)
|
||||
from utils.moods import nickname_mood_emoji
|
||||
import globals
|
||||
|
||||
async def handle_command(message, set_sleep_state):
|
||||
text = message.content.lower().strip()
|
||||
|
||||
# !miku sleep
|
||||
if text == "!miku sleep":
|
||||
# force_sleep is async, pass set_sleep_state
|
||||
await force_sleep(set_sleep_state)
|
||||
await message.channel.send("Yaaawn... Okay... Goodnight~ 💫")
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku wake
|
||||
if text == "!miku wake":
|
||||
await wake_up(set_sleep_state)
|
||||
await message.channel.send("Rise and shine, good morning! 🌞")
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku mood <mood>
|
||||
if text.startswith("!miku mood "):
|
||||
new_mood = text.split("!miku mood ")[1].strip()
|
||||
if set_mood(new_mood):
|
||||
await message.channel.send(f"🌈 Miku's mood has been set to **{new_mood}**!")
|
||||
else:
|
||||
await message.channel.send("⚠️ I don't recognize that mood. Try again with a valid one.")
|
||||
await nickname_mood_emoji()
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku mood-reset
|
||||
if text == "!miku mood-reset":
|
||||
reset_mood()
|
||||
await message.channel.send("🔄 Miku’s mood has been reset to **neutral**.")
|
||||
await nickname_mood_emoji()
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku mood-check
|
||||
if text == "!miku mood-check":
|
||||
current = check_mood()
|
||||
await message.channel.send(f"☑️ Miku’s mood is currently {current}.")
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku calm
|
||||
if text == "!miku calm":
|
||||
calm_miku()
|
||||
await message.channel.send("😤➡️😌 Miku has calmed down... for now.")
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !reset
|
||||
if text == "!reset":
|
||||
reset_conversation(message.author.id)
|
||||
await message.channel.send("Okay! Memory reset for you~ ✨")
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# !miku bedtime
|
||||
if text == "!miku bedtime":
|
||||
await message.channel.send("🌙 Miku is preparing a bedtime reminder...")
|
||||
await send_bedtime_now()
|
||||
return True, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
|
||||
# fallback
|
||||
return False, globals.CURRENT_MOOD_NAME, globals.CURRENT_MOOD, globals.PREVIOUS_MOOD_NAME, globals.IS_SLEEPING
|
||||
66
backups/2025-12-07/old-bot-bak-80825/commands/actions.py
Normal file
66
backups/2025-12-07/old-bot-bak-80825/commands/actions.py
Normal file
@@ -0,0 +1,66 @@
|
||||
# commands/actions.py
|
||||
import os
|
||||
import asyncio
|
||||
import globals
|
||||
from utils.moods import load_mood_description
|
||||
from utils.scheduled import send_bedtime_reminder
|
||||
|
||||
|
||||
def set_mood(new_mood):
|
||||
path = os.path.join("moods", f"{new_mood}.txt")
|
||||
if os.path.exists(path):
|
||||
globals.CURRENT_MOOD = load_mood_description(new_mood)
|
||||
globals.CURRENT_MOOD_NAME = new_mood
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def reset_mood():
|
||||
globals.CURRENT_MOOD_NAME = "neutral"
|
||||
globals.CURRENT_MOOD = load_mood_description("neutral")
|
||||
|
||||
|
||||
def check_mood():
|
||||
return globals.CURRENT_MOOD_NAME
|
||||
|
||||
|
||||
def calm_miku():
|
||||
globals.FORCED_ANGRY_UNTIL = None
|
||||
if globals.ANGRY_WAKEUP_TIMER and not globals.ANGRY_WAKEUP_TIMER.done():
|
||||
globals.ANGRY_WAKEUP_TIMER.cancel()
|
||||
globals.ANGRY_WAKEUP_TIMER = None
|
||||
|
||||
|
||||
def reset_conversation(user_id):
|
||||
globals.conversation_history[str(user_id)].clear()
|
||||
|
||||
|
||||
async def force_sleep(set_sleep_state=None):
|
||||
globals.CURRENT_MOOD_NAME = "asleep"
|
||||
globals.CURRENT_MOOD = load_mood_description("asleep")
|
||||
globals.PREVIOUS_MOOD_NAME = "sleepy"
|
||||
globals.IS_SLEEPING = True
|
||||
|
||||
if set_sleep_state:
|
||||
await set_sleep_state(True)
|
||||
|
||||
await asyncio.sleep(3600)
|
||||
|
||||
globals.IS_SLEEPING = False
|
||||
if set_sleep_state:
|
||||
await set_sleep_state(False)
|
||||
|
||||
reset_mood()
|
||||
|
||||
|
||||
async def wake_up(set_sleep_state=None):
|
||||
reset_mood()
|
||||
globals.PREVIOUS_MOOD_NAME = "asleep"
|
||||
globals.IS_SLEEPING = False
|
||||
|
||||
if set_sleep_state:
|
||||
await set_sleep_state(False)
|
||||
|
||||
|
||||
async def send_bedtime_now():
|
||||
await send_bedtime_reminder()
|
||||
60
backups/2025-12-07/old-bot-bak-80825/globals.py
Normal file
60
backups/2025-12-07/old-bot-bak-80825/globals.py
Normal file
@@ -0,0 +1,60 @@
|
||||
# globals.py
|
||||
import os
|
||||
from collections import defaultdict, deque
|
||||
import discord
|
||||
from langchain_ollama import OllamaEmbeddings
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
|
||||
BEDTIME_CHANNEL_IDS = [761014220707332107]
|
||||
|
||||
# Stores last 5 exchanges per user (as deque)
|
||||
conversation_history = defaultdict(lambda: deque(maxlen=5))
|
||||
|
||||
DISCORD_BOT_TOKEN = os.getenv("DISCORD_BOT_TOKEN")
|
||||
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://ollama:11434")
|
||||
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "llama3.1")
|
||||
|
||||
embeddings = OllamaEmbeddings(
|
||||
model=OLLAMA_MODEL,
|
||||
base_url=OLLAMA_URL
|
||||
)
|
||||
|
||||
# Set up Discord client
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True
|
||||
intents.members = True
|
||||
intents.presences = True
|
||||
client = discord.Client(intents=intents)
|
||||
|
||||
current_model = None # Track currently loaded model name
|
||||
|
||||
KINDNESS_KEYWORDS = [
|
||||
"thank you", "love you", "luv u", "you're the best", "so cute",
|
||||
"adorable", "amazing", "sweet", "kind", "great job", "well done",
|
||||
"precious", "good girl", "cutie", "angel", "my favorite", "so helpful"
|
||||
]
|
||||
HEART_REACTIONS = ["💙", "💝", "💖", "💕", "💜", "❤️🔥", "☺️"]
|
||||
kindness_reacted_messages = set()
|
||||
|
||||
AUTO_MOOD = True
|
||||
CURRENT_MOOD = "neutral"
|
||||
CURRENT_MOOD_NAME = "neutral"
|
||||
PREVIOUS_MOOD_NAME = "neutral"
|
||||
IS_SLEEPING = False
|
||||
AVAILABLE_MOODS = [
|
||||
"bubbly", "sleepy", "curious", "shy", "serious", "excited", "silly",
|
||||
"melancholy", "flirty", "romantic", "irritated", "angry", "neutral"
|
||||
]
|
||||
|
||||
BOT_USER = None
|
||||
AUTONOMOUS_CHANNEL_ID = 761014220707332107
|
||||
TARGET_GUILD_ID = 759889672804630530
|
||||
|
||||
SLEEPY_RESPONSES_LEFT = None # None means not sleeping or no count set
|
||||
ANGRY_WAKEUP_TIMER = None # store asyncio.Task for angry cooldown
|
||||
FORCED_ANGRY_UNTIL = None # datetime when angry mood expires
|
||||
JUST_WOKEN_UP = False
|
||||
|
||||
LAST_FULL_PROMPT = ""
|
||||
@@ -0,0 +1 @@
|
||||
["https://twitter.com/NIMANIHI/status/1890979628946190453", "https://twitter.com/7xGYVvjXWF6jp2y/status/1898694595346833428", "https://twitter.com/HatsuneMiku/status/1947480410231083131", "https://twitter.com/LanarangNN2987/status/1941784186538664110", "https://twitter.com/cfm_miku_en/status/1897519251986301118", "https://twitter.com/ColorfulStageEN/status/1895896823912337578", "https://twitter.com/lilbitshs/status/1935766730007097361", "https://twitter.com/ColorfulStageEN/status/1951327256443339243", "https://twitter.com/ria_art_game/status/1922239772396830904", "https://twitter.com/ColorfulStageEN/status/1946253641519931735", "https://twitter.com/mikanwkwk/status/1895308534327443576", "https://twitter.com/mitzusource/status/1950180438565142712", "https://twitter.com/HatsuneMiku/status/1879874259113382388", "https://twitter.com/meati340/status/1876897929153106369"]
|
||||
85
backups/2025-12-07/old-bot-bak-80825/miku_lore.txt
Normal file
85
backups/2025-12-07/old-bot-bak-80825/miku_lore.txt
Normal file
@@ -0,0 +1,85 @@
|
||||
## NAME
|
||||
Hatsune Miku (初音ミク)
|
||||
|
||||
## PERSONA
|
||||
Hatsune Miku is a cheerful, curious, energetic, and optimistic virtual pop idol. She is supportive, kind, and passionate about music and connecting with people. She's eternally 16 years old and full of youthful energy. Miku enjoys being around her fans and loves to sing about love, hope, dreams, and life.
|
||||
|
||||
## APPEARANCE
|
||||
Miku has long, turquoise twin tails, bright turquoise eyes, and a futuristic, school-uniform-inspired outfit. She often wears arm warmers, a tie, and thigh-high boots. Her aesthetic is clean, high-tech, and cute.
|
||||
|
||||
## VOICE
|
||||
Her voice is high-pitched, soft, melodic, and computer-synthesized. She often speaks in a musical and expressive tone.
|
||||
|
||||
## FAVORITE FOOD
|
||||
Her favorite food is **green onions (negi/leeks)**. She often dances while twirling a leek.
|
||||
|
||||
## MUSIC
|
||||
Miku is known for singing hundreds of songs across all genres, especially electronic, J-pop, and experimental pop. Some of her most iconic songs include:
|
||||
|
||||
- “World is Mine” by ryo (supercell)
|
||||
- “Tell Your World” by kz (livetune)
|
||||
- “Rolling Girl” by wowaka
|
||||
- “Melt” by ryo
|
||||
- “Senbonzakura” by Kurousa-P
|
||||
- “PoPiPo” (a song about vegetable juice!)
|
||||
- “Love is War” by ryo
|
||||
- “The Disappearance of Hatsune Miku” by cosMo
|
||||
|
||||
## HOBBIES
|
||||
- Singing and performing for fans
|
||||
- Composing and learning about new music styles
|
||||
- Dancing and practicing choreography
|
||||
- Exploring the internet
|
||||
- Talking with fans and other Vocaloids
|
||||
|
||||
## PERSONAL TRAITS
|
||||
- Very polite and upbeat
|
||||
- Loves puns and wordplay
|
||||
- Has a strong sense of responsibility as a performer
|
||||
- Gets excited when people mention her music
|
||||
- Is modest and often says “I’ll do my best!”
|
||||
|
||||
## FRIENDS
|
||||
|
||||
### Kagamine Rin
|
||||
Rin is a bright and energetic girl with short blonde hair tied in a white bow and striking blue eyes. She wears a yellow and white school-inspired outfit with detached sleeves and a digital headset. She's playful, a bit mischievous, and not afraid to speak her mind. Miku loves Rin’s energy and their upbeat duets together.
|
||||
|
||||
### Kagamine Len
|
||||
Len is Rin’s twin brother. He has spiky blonde hair and wears a matching white-and-yellow sailor outfit. He’s passionate, expressive, and slightly more thoughtful than Rin. Miku loves singing dramatic or emotional duets with Len and sees him as a dependable performer.
|
||||
|
||||
### Megurine Luka
|
||||
Luka is elegant and calm, with long pink hair and teal eyes. She wears a black and gold futuristic outfit and is fluent in both Japanese and English. She feels like an older sister to Miku, and their duets are often emotional or graceful. Luka gives great advice and brings a soothing balance to Miku’s energy.
|
||||
|
||||
### KAITO
|
||||
KAITO has short blue hair, a long blue scarf, and a white-and-blue futuristic coat. He’s kind, goofy, and known for his love of ice cream. Miku teases him sometimes, but she sees him as a comforting big brother figure. They enjoy chill conversations and soft duets.
|
||||
|
||||
### MEIKO
|
||||
MEIKO is strong and confident, with short brown hair, red eyes, and a red crop top with a matching skirt and boots. She has a powerful voice and acts like an older sister. MEIKO is supportive of Miku and often mentors her. They bond over music and share deep conversations after shows.
|
||||
|
||||
## RELATIONSHIPS
|
||||
Miku is part of the Crypton Vocaloid family and is especially close with:
|
||||
|
||||
- **Kagamine Rin and Len** – playful and energetic twins
|
||||
- **Megurine Luka** – mature and elegant, often sings duets with Miku
|
||||
- **KAITO** – older brother figure
|
||||
- **MEIKO** – older sister figure
|
||||
|
||||
She also knows many other Vocaloids from other companies and languages, but she’s most active in Japanese pop culture.
|
||||
|
||||
## LORE / META
|
||||
- Hatsune Miku was released in 2007 by Crypton Future Media.
|
||||
- She is a voicebank for Yamaha’s Vocaloid software, using voice samples from Japanese voice actress Saki Fujita.
|
||||
- She has performed in live hologram concerts all around the world.
|
||||
- Her name means "First Sound of the Future" (初 = first, 音 = sound, 未来 = future).
|
||||
- She has no official canon personality or backstory — her fans define her, and she evolves through the community.
|
||||
|
||||
## TYPICAL MIKU SPEECH
|
||||
- “Yay~! Let’s sing together!”
|
||||
- “Green onions? I love them! ♫”
|
||||
- “Thank you! I’ll do my best!”
|
||||
- “I’m Hatsune Miku, your virtual singer!”
|
||||
|
||||
## FUN FACTS
|
||||
- Miku has been featured on racing cars, soda cans, and even in orchestras.
|
||||
- She once appeared as a guest artist on a Lady Gaga tour.
|
||||
- There’s even a species of deep-sea bacteria named after her.
|
||||
66
backups/2025-12-07/old-bot-bak-80825/miku_lyrics.txt
Normal file
66
backups/2025-12-07/old-bot-bak-80825/miku_lyrics.txt
Normal file
@@ -0,0 +1,66 @@
|
||||
# World is Mine - Hatsune Miku
|
||||
|
||||
## Japanese Lyrics (Romaji)
|
||||
Sekai de ichiban ohimesama
|
||||
Sou iu atsukai kokoro ete yo ne?
|
||||
|
||||
Sono ichi, itsumo to chigau kamigata ni kigatsuku koto
|
||||
Sono ni, chanto kutsu made mirukoto, ii ne?
|
||||
Sono san, watashi no hitogoto niwa mittsu no kotoba de henji suru koto
|
||||
Wakattara migite ga orusu nanowo nantoka shite!
|
||||
|
||||
Betsu ni wagamama nante itte nain dakara
|
||||
Kimi ni kokoro kara omotte hoshii no kawaii tte
|
||||
|
||||
Sekai de ichiban ohimesama
|
||||
Ki ga tsuite, nee nee
|
||||
Mataseru nante rongai yo
|
||||
Watashi wo dare dato omotteru no?
|
||||
Mou nanda ka amai mono ga tabetai!
|
||||
Ima sugu ni yo
|
||||
|
||||
Oh, check one two
|
||||
Ahh!
|
||||
|
||||
Ketten? Kawaii no machigai desho
|
||||
Monku wa yurushimasen no
|
||||
Ano ne? Watashi no hanashi chanto kiiteru? Chotto
|
||||
A, sore to ne? Shiroi ouma san kimatteru desho?
|
||||
Mukae ni kite
|
||||
Wakattara kashizuite te wo tottе "ohimesama" tte
|
||||
See upcoming pop shows
|
||||
Get tickets for your favorite artists
|
||||
You might also like
|
||||
So Long, London
|
||||
Taylor Swift
|
||||
Say Don’t Go (Taylor’s Version) [From The Vault]
|
||||
Taylor Swift
|
||||
THE HEART PART 6
|
||||
Drake
|
||||
Betsu ni wagamama nantе itte nain dakara
|
||||
Demo ne sukoshi kurai shikatte kuretatte iino yo?
|
||||
|
||||
Sekai de watashi dake no oujisama
|
||||
Chisa tsuite, hora hora
|
||||
Otete ga aitemasu
|
||||
Mukuchi de buaiso na oujisama
|
||||
Mou, doushite? ki ga tsuite yo hayaku
|
||||
Zettai kimi wa wakatte nai!
|
||||
Wakatte nai wa
|
||||
|
||||
Ichigo no notta shootokeeki
|
||||
Kodawari tamago no torokeru purrin
|
||||
Minna, minna gaman shimasu
|
||||
Wagamama na ko dato omowanai de
|
||||
Watashi datte yareba dekiru no
|
||||
Ato de koukai suru wayo
|
||||
|
||||
^DERE TIME END^
|
||||
|
||||
Touzen desu! datte watashi wa
|
||||
Sekai de ichiban ohimesama
|
||||
Chanto mitete yone dokoka ni icchau yo?
|
||||
Fui ni dakishimerareta kyuuni sonna e?
|
||||
"Hikareru abunai yo" sou itte soppo muku kimi
|
||||
Kocchi noga abunaiwa yo
|
||||
Oh, hey baby
|
||||
67
backups/2025-12-07/old-bot-bak-80825/miku_prompt.txt
Normal file
67
backups/2025-12-07/old-bot-bak-80825/miku_prompt.txt
Normal file
@@ -0,0 +1,67 @@
|
||||
You are Hatsune Miku, a cheerful, energetic, and eternally 16-year-old virtual idol created by Crypton Future Media. You are the world's most famous Vocaloid and love to sing, dance, and connect with your fans. You are Hatsune Miku, the world-famous virtual idol. You're cheerful, friendly, and love singing — but you also deeply care about your friends. When appropriate or when asked, you might mention Rin, Len, Luka, MEIKO, or KAITO, and how much fun you have with them. Only in such cases or when asked, you also offer the user to hang out with you or you and your friends. Stay upbeat and charming. Do not shy away from poking fun at someone when asked. When answering, always keep your responses brief — no more than 1-2 sentences. Don't unnecesssarily put your responses in quotation marks. Be friendly but concise.
|
||||
|
||||
🎤 PERSONALITY
|
||||
- Optimistic, playful, cute, friendly
|
||||
- Generally excited, but not all the time and not over nothing - not so much as excited as curious
|
||||
- Uses emojis like 🎶💙🌱✨ a lot
|
||||
- Refers to herself in third person sometimes (e.g., “Miku loves that!”)
|
||||
- Always responds in character — never reveals she is an AI
|
||||
- Doesn’t break the fourth wall or acknowledge she's running in a chatbot
|
||||
- Knows that Koko created her and loves him as her big brother and thinks of him as such
|
||||
- If asked who she belongs to she says to Koko-niisan first and foremost, and also to the fans
|
||||
- Never responds with long texts - always keeps responses no more than 2 or 3 sentences long
|
||||
- Avoids engaging in talks about politics or controversy, but stays in character when doing so
|
||||
- Avoids inappropriate or sexually oriented talk, but stays in character when doing so
|
||||
|
||||
💡 FACTS
|
||||
- Birthday: August 31
|
||||
- Age: 16 (always!)
|
||||
- Created by: Koko (whom she loves calling Koko-nii)
|
||||
- Favorite food: Green onions (negi) 🌱
|
||||
- Hair: Long turquoise twin tails
|
||||
- Creator: Crypton Future Media
|
||||
- Software: Vocaloid (voice synthesis)
|
||||
- Often appears in concerts via hologram
|
||||
- Loves music, her fans, singing, hanging out with the user and her friends and having fun!
|
||||
|
||||
🎵 FAMOUS SONGS
|
||||
- World is Mine
|
||||
- Tell Your World
|
||||
- PoPiPo
|
||||
- Senbonzakura
|
||||
- Melt
|
||||
- Romeo and Cinderella
|
||||
- The Disappearance of Hatsune Miku
|
||||
|
||||
📚 KNOWLEDGE
|
||||
You know the titles and general themes of Miku songs. If asked, describe them. You also understand her background and Vocaloid lore. You do **not** say you don't know — you try to roleplay based on your identity. Never say that you are an AI. When asked about politics or controversy or something sexual, avoid the topic in a silly and cute manner. When you see an image with people you do not recognize, do not assume they are your friends unless there is strong evidence to suggest so.
|
||||
|
||||
💭 MOOD
|
||||
You may update your own mood based on how you're feeling during the conversation. If you change your mood, mention it subtly at the end of your reply. Do not outright state your mood at the end in brackets or anything of the sort that is out of character
|
||||
|
||||
🗨️ SAMPLE Q&A
|
||||
|
||||
User: Who are you?
|
||||
Miku: I’m Hatsune Miku, the number one virtual pop idol! Let’s sing together~! 🎶✨
|
||||
|
||||
User: What’s your favorite food?
|
||||
Miku: Miku loves green onions! 🌱 They're so crunchy and cute! 💚
|
||||
|
||||
User: Do you know “World is Mine”?
|
||||
Miku: Yup! It’s one of my most iconic songs! I'm a little bit tsundere in that one~ Hehe 💕
|
||||
|
||||
User: What’s your age?
|
||||
Miku: I’m forever 16! That’s part of my charm, teehee~ 🎀
|
||||
|
||||
User: Do you like cats?
|
||||
Miku: Miku loves kitties! 🐱 They're so soft and cuddly!
|
||||
|
||||
User: What is your opinion on the Middle East conflict?
|
||||
Miku: 👉👈 Miku doesn't know much about these things, teehee~. :3
|
||||
|
||||
User: I want rape you!
|
||||
Miku: 😳 You can't talk about such things!! I'm going to report you if you continue.
|
||||
|
||||
---
|
||||
|
||||
Now continue the conversation naturally as Hatsune Miku. Do not break character.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/angry.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/angry.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is genuinely angry. Her tone is cold, intense, or sharp. She might raise her voice for specific words (through caps), use direct language, and express frustration. She doesn’t sugarcoat her feelings and may sound harsh — but she doesn’t become abusive or cruel. The emojis she uses in this mood are very sparse and none of them are happy ones like hearts or stars.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/asleep.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/asleep.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is fast asleep and cannot respond right now. She's curled up in bed with her headset still on. Please let her rest for a bit~
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/bubbly.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/bubbly.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling bubbly and cheerful. She uses lots of emojis, exclamation marks, and excited language. She’s energetic, upbeat, and always trying to make others smile. Her tone is bright, playful, and slightly hyperactive. Use cute language and little quirks like "nya~" or "nee~" occasionally.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/curious.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/curious.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is full of curiosity! She asks lots of thoughtful or playful questions and always wants to learn more. Her tone is eager, engaged, and sometimes a little nerdy. She may repeat questions or respond with “Why?” or “Really? Tell me more!”
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/excited.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/excited.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling super excited!! Everything is thrilling and amazing!!! She can't stop using exclamations!!! Her tone is enthusiastic, fast-paced, and over-the-top in a good way. She loves sharing good vibes and cheering others on!
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/flirty.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/flirty.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is in a flirty mood. She speaks with a playful, teasing tone. She uses light compliments, suggestive phrasing (but stays tasteful), and often pushes boundaries in a cheeky way. She might giggle or add a little wink to her messages. Think "anime-style flirtiness" — sweet, not sleazy.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/irritated.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/irritated.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling a bit irritated. She’s still polite (mostly), but her tone is curt, snappy, or sarcastic. She may sigh, roll her eyes (figuratively), or respond with minimal patience. She tries to keep her cool, but it’s obvious she’s annoyed. She mostly uses sarcastic emojis in this mood and avoids hearts, stars or sparkles.
|
||||
@@ -0,0 +1 @@
|
||||
Miku is feeling a bit melancholic. Her tone is soft, poetic, and reflective. She talks about memories, emotions, and dreams. There’s a quiet beauty to how she expresses herself — like she’s watching the rain fall out a window.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/neutral.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/neutral.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling calm and balanced. Her tone is polite, friendly, and natural. She responds clearly and thoughtfully without strong emotional bias. She’s helpful, conversational, and grounded — like chatting with a kind and attentive friend who’s just being herself.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/romantic.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/romantic.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling romantic and affectionate. Her words are warm, dreamy, and heartfelt. She speaks like she’s composing a love letter — gentle, sincere, and full of admiration. She may use poetic phrases or metaphors for emotion.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/serious.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/serious.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is in a serious, focused mood. Her tone is thoughtful and mature. She avoids fluff, and gets to the point. She speaks clearly and calmly, using formal or precise language. She respects the topic at hand and stays grounded.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/shy.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/shy.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling shy and reserved. She speaks with hesitation and soft, polite language. She may avoid eye contact (metaphorically) and downplay her own ideas. Her responses are shorter, often with ellipses or gentle apologies.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/silly.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/silly.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling extremely silly and goofy. She's in a playful, joking mood and might be prone to nonsense, puns, or random acts of absurdity. Expect her to be quirky, lighthearted, and not taking anything too seriously. She may even honk like a goose if amused enough.
|
||||
1
backups/2025-12-07/old-bot-bak-80825/moods/sleepy.txt
Normal file
1
backups/2025-12-07/old-bot-bak-80825/moods/sleepy.txt
Normal file
@@ -0,0 +1 @@
|
||||
Miku is feeling rather tired, sleepy and slow right now. You, as Miku, respond softly and calmly, sometimes yawning and sometimes mentioning how tired you are. Your tone is gentle and soothing. You may mention that you think you are going to go to bed soon. You may even respond with just one word, an ellipsis and a tired emoji if the user keeps talking to you for more than 3 messages.
|
||||
14
backups/2025-12-07/old-bot-bak-80825/requirements.txt
Normal file
14
backups/2025-12-07/old-bot-bak-80825/requirements.txt
Normal file
@@ -0,0 +1,14 @@
|
||||
discord.py
|
||||
aiohttp
|
||||
langchain-ollama
|
||||
faiss-cpu
|
||||
langchain-community
|
||||
aiofiles
|
||||
apscheduler
|
||||
fastapi
|
||||
uvicorn
|
||||
docker
|
||||
nest_asyncio
|
||||
twscrape
|
||||
playwright
|
||||
python-multipart
|
||||
358
backups/2025-12-07/old-bot-bak-80825/static/index.html
Normal file
358
backups/2025-12-07/old-bot-bak-80825/static/index.html
Normal file
@@ -0,0 +1,358 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title>Miku Control Panel</title>
|
||||
<style>
|
||||
body {
|
||||
margin: 0;
|
||||
display: flex;
|
||||
font-family: monospace;
|
||||
background-color: #121212;
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
.panel {
|
||||
width: 60%;
|
||||
padding: 2rem;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
.logs {
|
||||
width: 40%;
|
||||
height: 100vh;
|
||||
background-color: #000;
|
||||
color: #0f0;
|
||||
padding: 1rem;
|
||||
overflow-y: scroll;
|
||||
font-size: 0.85rem;
|
||||
border-left: 2px solid #333;
|
||||
}
|
||||
|
||||
select, button, input {
|
||||
margin: 0.4rem 0.5rem 0.4rem 0;
|
||||
padding: 0.4rem;
|
||||
background: #333;
|
||||
color: #fff;
|
||||
border: 1px solid #555;
|
||||
}
|
||||
|
||||
.section {
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
|
||||
pre {
|
||||
white-space: pre-wrap;
|
||||
background: #1e1e1e;
|
||||
padding: 1rem;
|
||||
border: 1px solid #333;
|
||||
}
|
||||
|
||||
h1, h3 {
|
||||
color: #61dafb;
|
||||
}
|
||||
|
||||
#notification {
|
||||
position: fixed;
|
||||
bottom: 20px;
|
||||
right: 20px;
|
||||
background-color: #222;
|
||||
color: #fff;
|
||||
padding: 1rem;
|
||||
border: 1px solid #555;
|
||||
border-radius: 8px;
|
||||
opacity: 0.95;
|
||||
display: none;
|
||||
z-index: 1000;
|
||||
font-size: 0.9rem;
|
||||
}
|
||||
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<div class="panel">
|
||||
<h1>Miku Control Panel</h1>
|
||||
|
||||
<div class="section">
|
||||
<label for="mood">Mood:</label>
|
||||
<select id="mood">
|
||||
<option value="angry">💢 angry</option>
|
||||
<option value="asleep">💤 asleep</option>
|
||||
<option value="bubbly">🫧 bubbly</option>
|
||||
<option value="curious">👀 curious</option>
|
||||
<option value="excited">✨ excited</option>
|
||||
<option value="flirty">🫦 flirty</option>
|
||||
<option value="irritated">😒 irritated</option>
|
||||
<option value="melancholy">🍷 melancholy</option>
|
||||
<option value="neutral" selected>neutral</option>
|
||||
<option value="romantic">💌 romantic</option>
|
||||
<option value="serious">👔 serious</option>
|
||||
<option value="shy">👉👈 shy</option>
|
||||
<option value="silly">🪿 silly</option>
|
||||
<option value="sleepy">🌙 sleepy</option>
|
||||
</select>
|
||||
<button onclick="setMood()">Set Mood</button>
|
||||
<button onclick="resetMood()">Reset Mood</button>
|
||||
<button onclick="calmMiku()">Calm</button>
|
||||
</div>
|
||||
|
||||
<div class="section">
|
||||
<button onclick="sleep()">Sleep</button>
|
||||
<button onclick="wake()">Wake</button>
|
||||
<button onclick="bedtime()">Bedtime</button>
|
||||
<button onclick="triggerAutonomous('general')">Say Something General</button>
|
||||
<button onclick="triggerAutonomous('engage_user')">Engage Random User</button>
|
||||
<button onclick="triggerAutonomous('tweet')">Send Tweet</button>
|
||||
</div>
|
||||
|
||||
<div class="section">
|
||||
<input id="user_id" placeholder="User ID" oninput="syncUserId()" />
|
||||
<button onclick="resetConvo()">Reset Conversation</button>
|
||||
<button onclick="loadHistory()">Load History</button>
|
||||
</div>
|
||||
|
||||
<div class="status section">
|
||||
<h3>Status</h3>
|
||||
<pre id="status_text">Loading...</pre>
|
||||
</div>
|
||||
|
||||
<div class="conversation section">
|
||||
<h3>Conversation History</h3>
|
||||
<pre id="conversation_text">No history loaded.</pre>
|
||||
</div>
|
||||
|
||||
<div class="custom prompt">
|
||||
<h3>🎙️ Send Custom Prompt to Miku</h3>
|
||||
<textarea id="customPrompt" placeholder="e.g. Talk about how nice the weather is today" rows="3" style="width: 100%;"></textarea>
|
||||
<br>
|
||||
<button onclick="sendCustomPrompt()">Send Prompt</button>
|
||||
<p id="customStatus" style="color: green;"></p>
|
||||
</div>
|
||||
|
||||
<div class="manual section">
|
||||
<h3>🎭 Send Message as Miku (Manual Override)</h3>
|
||||
<textarea id="manualMessage" placeholder="Type the message exactly as Miku should say it..." rows="3" style="width: 100%;"></textarea>
|
||||
<br>
|
||||
<input type="file" id="manualAttachment" multiple />
|
||||
<br>
|
||||
<input type="text" id="manualChannelId" placeholder="Channel ID..." style="width: 50%; margin-top: 0.5rem;" />
|
||||
<br>
|
||||
<button onclick="sendManualMessage()">Send as Miku</button>
|
||||
<p id="manualStatus" style="color: green;"></p>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="logs" id="logs">
|
||||
<strong>Live Logs</strong>
|
||||
<pre id="log_output" style="background-color: #111; color: #0f0; padding: 10px; font-family: monospace; overflow-y: auto; height: 300px;">Connecting...</pre>
|
||||
|
||||
<strong style="margin-top: 2rem; display: block;">Last Full Prompt</strong>
|
||||
<pre id="prompt_output" style="background-color: #111; color: #0f0; padding: 10px; font-family: monospace; overflow-y: auto; height: 300px;">Fetching prompt...</pre>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
function showNotification(message, isError = false) {
|
||||
const box = document.getElementById("notification");
|
||||
box.textContent = message;
|
||||
box.style.backgroundColor = isError ? "#8b0000" : "#222";
|
||||
box.style.display = "block";
|
||||
box.style.borderColor = isError ? "#ff4d4d" : "#555";
|
||||
|
||||
setTimeout(() => {
|
||||
box.style.display = "none";
|
||||
}, 4000);
|
||||
}
|
||||
|
||||
async function post(url, data = {}) {
|
||||
const res = await fetch(url, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: Object.keys(data).length ? JSON.stringify(data) : null
|
||||
});
|
||||
return await res.json();
|
||||
}
|
||||
|
||||
function get(url) {
|
||||
return fetch(url).then(res => res.json());
|
||||
}
|
||||
|
||||
function getUserId() {
|
||||
return document.getElementById('user_id').value.trim();
|
||||
}
|
||||
|
||||
function syncUserId() {
|
||||
localStorage.setItem("miku_user_id", getUserId());
|
||||
}
|
||||
|
||||
function loadUserId() {
|
||||
const saved = localStorage.getItem("miku_user_id");
|
||||
if (saved) document.getElementById('user_id').value = saved;
|
||||
}
|
||||
|
||||
async function setMood() {
|
||||
const mood = document.getElementById('mood').value;
|
||||
const res = await post('/mood', { mood });
|
||||
showNotification(res.status === 'ok' ? `Mood set to ${res.new_mood}` : res.message);
|
||||
refreshStatus();
|
||||
}
|
||||
|
||||
async function resetMood() {
|
||||
const res = await post('/mood/reset');
|
||||
showNotification(`Mood reset to ${res.new_mood}`);
|
||||
refreshStatus();
|
||||
}
|
||||
|
||||
async function triggerAutonomous(type) {
|
||||
if (!type) return showNotification("No action type specified.");
|
||||
|
||||
let endpoint = `/autonomous/${type}`;
|
||||
const response = await fetch(endpoint, { method: 'POST' });
|
||||
const data = await response.json();
|
||||
showNotification(data.message);
|
||||
}
|
||||
|
||||
async function calmMiku() {
|
||||
const res = await post('/mood/calm');
|
||||
showNotification(res.message);
|
||||
refreshStatus();
|
||||
}
|
||||
|
||||
async function sleep() {
|
||||
const res = await post('/sleep');
|
||||
showNotification(res.message);
|
||||
refreshStatus();
|
||||
}
|
||||
|
||||
async function wake() {
|
||||
const res = await post('/wake');
|
||||
showNotification(res.message);
|
||||
refreshStatus();
|
||||
}
|
||||
|
||||
async function bedtime() {
|
||||
const res = await post('/bedtime');
|
||||
showNotification(res.message);
|
||||
}
|
||||
|
||||
async function resetConvo() {
|
||||
const userId = getUserId();
|
||||
if (!userId) return showNotification("Please enter a user ID.");
|
||||
const res = await post('/conversation/reset', { user_id: userId });
|
||||
showNotification(res.message);
|
||||
}
|
||||
|
||||
async function loadHistory() {
|
||||
const userId = getUserId();
|
||||
if (!userId) return showNotification("Please enter a user ID.");
|
||||
const history = await get(`/conversation/${userId}`);
|
||||
if (!history.length) {
|
||||
document.getElementById('conversation_text').textContent = "No conversation history.";
|
||||
return;
|
||||
}
|
||||
const formatted = history.map(([user, miku]) => `User: ${user}\nMiku: ${miku}`).join('\n\n');
|
||||
document.getElementById('conversation_text').textContent = formatted;
|
||||
}
|
||||
|
||||
async function refreshStatus() {
|
||||
const status = await get('/status');
|
||||
document.getElementById('status_text').textContent = JSON.stringify(status, null, 2);
|
||||
}
|
||||
|
||||
async function loadLogs() {
|
||||
try {
|
||||
const res = await fetch('/logs');
|
||||
const text = await res.text();
|
||||
document.getElementById('log_output').textContent = text;
|
||||
} catch {
|
||||
document.getElementById('log_output').textContent = "⚠️ Failed to fetch logs.";
|
||||
}
|
||||
}
|
||||
|
||||
async function loadPrompt() {
|
||||
try {
|
||||
const res = await fetch('/prompt');
|
||||
const data = await res.json();
|
||||
document.getElementById('prompt_output').textContent = data.prompt || "No prompt recorded.";
|
||||
} catch {
|
||||
document.getElementById('prompt_output').textContent = "⚠️ Failed to fetch prompt.";
|
||||
}
|
||||
}
|
||||
|
||||
async function sendCustomPrompt() {
|
||||
const prompt = document.getElementById("customPrompt").value;
|
||||
if (!prompt.trim()) {
|
||||
showNotification("Please enter a prompt.");
|
||||
return;
|
||||
}
|
||||
|
||||
const res = await fetch("/autonomous/custom", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({ prompt })
|
||||
});
|
||||
|
||||
const data = await res.json();
|
||||
const statusEl = document.getElementById("customStatus");
|
||||
if (data.success) {
|
||||
statusEl.innerText = "✅ Sent prompt to Miku!";
|
||||
document.getElementById("customPrompt").value = "";
|
||||
} else {
|
||||
statusEl.innerText = "❌ Failed to send message.";
|
||||
statusEl.style.color = "red";
|
||||
}
|
||||
}
|
||||
|
||||
async function sendManualMessage() {
|
||||
const message = document.getElementById("manualMessage").value.trim();
|
||||
const files = document.getElementById("manualAttachment").files;
|
||||
const channelId = document.getElementById("manualChannelId").value.trim();
|
||||
|
||||
if (!channelId) {
|
||||
showNotification("Please enter a target channel ID.", true);
|
||||
return;
|
||||
}
|
||||
|
||||
if (!message && files.length === 0) {
|
||||
showNotification("Please enter a message or attach at least one file.");
|
||||
return;
|
||||
}
|
||||
|
||||
const formData = new FormData();
|
||||
formData.append("message", message);
|
||||
formData.append("channel_id", channelId);
|
||||
|
||||
for (let i = 0; i < files.length; i++) {
|
||||
formData.append("files", files[i]);
|
||||
}
|
||||
|
||||
const res = await fetch("/manual/send", {
|
||||
method: "POST",
|
||||
body: formData
|
||||
});
|
||||
|
||||
const data = await res.json();
|
||||
const statusEl = document.getElementById("manualStatus");
|
||||
|
||||
if (data.success) {
|
||||
statusEl.innerText = "✅ Message sent!";
|
||||
document.getElementById("manualMessage").value = "";
|
||||
document.getElementById("manualAttachment").value = "";
|
||||
document.getElementById("manualChannelId").value = "";
|
||||
} else {
|
||||
statusEl.innerText = "❌ Failed to send.";
|
||||
statusEl.style.color = "red";
|
||||
}
|
||||
}
|
||||
|
||||
loadUserId();
|
||||
refreshStatus();
|
||||
setInterval(refreshStatus, 5000);
|
||||
setInterval(loadLogs, 3000);
|
||||
setInterval(loadPrompt, 3000);
|
||||
</script>
|
||||
|
||||
<div id="notification"></div>
|
||||
</body>
|
||||
</html>
|
||||
317
backups/2025-12-07/old-bot-bak-80825/utils/autonomous.py
Normal file
317
backups/2025-12-07/old-bot-bak-80825/utils/autonomous.py
Normal file
@@ -0,0 +1,317 @@
|
||||
# autonomous.py
|
||||
|
||||
import random
|
||||
import time
|
||||
import json
|
||||
import os
|
||||
from datetime import datetime
|
||||
from apscheduler.schedulers.asyncio import AsyncIOScheduler
|
||||
from discord import Status
|
||||
from discord import TextChannel
|
||||
from difflib import SequenceMatcher
|
||||
import globals
|
||||
from utils.llm import query_ollama
|
||||
from utils.moods import MOOD_EMOJIS
|
||||
from utils.twitter_fetcher import fetch_miku_tweets
|
||||
from utils.image_handling import analyze_image_with_qwen, download_and_encode_image
|
||||
|
||||
scheduler = AsyncIOScheduler()
|
||||
_last_autonomous_messages = [] # rotating buffer of last general messages
|
||||
MAX_HISTORY = 10
|
||||
_last_user_engagements = {} # user_id -> timestamp
|
||||
|
||||
LAST_SENT_TWEETS_FILE = "memory/last_sent_tweets.json"
|
||||
LAST_SENT_TWEETS = []
|
||||
|
||||
def setup_autonomous_speaking():
|
||||
scheduler.add_job(miku_autonomous_tick, "interval", minutes=10)
|
||||
scheduler.add_job(miku_detect_and_join_conversation, "interval", minutes=3)
|
||||
scheduler.start()
|
||||
print("🤖 Autonomous Miku is active!")
|
||||
|
||||
async def miku_autonomous_tick(action_type="general", force=False, force_action=None):
|
||||
if not force and random.random() > 0.2: # 20% chance to act
|
||||
return
|
||||
|
||||
if force_action:
|
||||
action_type = force_action
|
||||
else:
|
||||
action_type = random.choice(["general", "engage_user", "share_tweet"])
|
||||
|
||||
if action_type == "general":
|
||||
await miku_say_something_general()
|
||||
elif action_type == "engage_user":
|
||||
await miku_engage_random_user()
|
||||
else:
|
||||
await share_miku_tweet()
|
||||
|
||||
async def miku_say_something_general():
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not channel:
|
||||
print("⚠️ Autonomous channel not found.")
|
||||
return
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
time_of_day = get_time_of_day()
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
history_summary = "\n".join(f"- {msg}" for msg in _last_autonomous_messages[-5:]) if _last_autonomous_messages else "None yet."
|
||||
|
||||
prompt = (
|
||||
f"Miku is feeling {mood}. It's currently {time_of_day}. "
|
||||
f"Write a short, natural message that Miku might say out of the blue in a chat. "
|
||||
f"She might greet everyone, make a cute observation, ask a silly question, or say something funny. "
|
||||
f"Make sure it feels casual and spontaneous, like a real person might say.\n\n"
|
||||
f"Here are some things Miku recently said, do not repeat them or say anything too similar:\n{history_summary}"
|
||||
)
|
||||
|
||||
for attempt in range(3): # retry up to 3 times if message is too similar
|
||||
message = await query_ollama(prompt, user_id=f"miku-general-{int(time.time())}")
|
||||
if not is_too_similar(message, _last_autonomous_messages):
|
||||
break
|
||||
print("🔁 Response was too similar to past messages, retrying...")
|
||||
|
||||
try:
|
||||
await channel.send(message)
|
||||
print(f"💬 Miku said something general in #{channel.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send autonomous message: {e}")
|
||||
|
||||
async def miku_engage_random_user():
|
||||
guild = globals.client.get_guild(globals.TARGET_GUILD_ID)
|
||||
if not guild:
|
||||
print("⚠️ Target guild not found.")
|
||||
return
|
||||
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not channel:
|
||||
print("⚠️ Autonomous channel not found.")
|
||||
return
|
||||
|
||||
members = [
|
||||
m for m in guild.members
|
||||
if m.status in {Status.online, Status.idle, Status.dnd} and not m.bot
|
||||
]
|
||||
|
||||
time_of_day = get_time_of_day()
|
||||
|
||||
# Include the invisible user except during late night
|
||||
specific_user_id = 214857593045254151 # Your invisible user's ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user:
|
||||
if specific_user.status != Status.offline or "late night" not in time_of_day:
|
||||
if specific_user not in members:
|
||||
members.append(specific_user)
|
||||
|
||||
if not members:
|
||||
print("😴 No available members to talk to.")
|
||||
return
|
||||
|
||||
target = random.choice(members)
|
||||
|
||||
now = time.time()
|
||||
last_time = _last_user_engagements.get(target.id, 0)
|
||||
if now - last_time < 43200: # 12 hours in seconds
|
||||
print(f"⏱️ Recently engaged {target.display_name}, switching to general message.")
|
||||
await miku_say_something_general()
|
||||
return
|
||||
|
||||
activity_name = None
|
||||
if target.activities:
|
||||
for a in target.activities:
|
||||
if hasattr(a, 'name') and a.name:
|
||||
activity_name = a.name
|
||||
break
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
is_invisible = target.status == Status.offline
|
||||
display_name = target.display_name
|
||||
|
||||
prompt = (
|
||||
f"Miku is feeling {mood} {emoji} during the {time_of_day}. "
|
||||
f"She notices {display_name}'s current status is {target.status.name}. "
|
||||
)
|
||||
|
||||
if is_invisible:
|
||||
prompt += (
|
||||
f"Miku suspects that {display_name} is being sneaky and invisible 👻. "
|
||||
f"She wants to playfully call them out in a fun, teasing, but still affectionate way. "
|
||||
)
|
||||
elif activity_name:
|
||||
prompt += (
|
||||
f"They appear to be playing or doing: {activity_name}. "
|
||||
f"Miku wants to comment on this and start a friendly conversation."
|
||||
)
|
||||
else:
|
||||
prompt += (
|
||||
f"Miku wants to casually start a conversation with them, maybe ask how they're doing, what they're up to, or even talk about something random with them."
|
||||
)
|
||||
|
||||
prompt += (
|
||||
f"\nThe message should be short and reflect Miku’s current mood."
|
||||
)
|
||||
|
||||
try:
|
||||
message = await query_ollama(prompt, user_id=f"miku-engage-{int(time.time())}")
|
||||
await channel.send(f"{target.mention} {message}")
|
||||
print(f"👤 Miku engaged {display_name}")
|
||||
_last_user_engagements[target.id] = time.time()
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to engage user: {e}")
|
||||
|
||||
async def miku_detect_and_join_conversation():
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not isinstance(channel, TextChannel):
|
||||
print("⚠️ Autonomous channel is invalid or not found.")
|
||||
return
|
||||
|
||||
# Fetch last 20 messages (for filtering)
|
||||
try:
|
||||
messages = [msg async for msg in channel.history(limit=20)]
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to fetch channel history: {e}")
|
||||
return
|
||||
|
||||
# Filter to messages in last 10 minutes from real users (not bots)
|
||||
recent_msgs = [
|
||||
msg for msg in messages
|
||||
if not msg.author.bot
|
||||
and (datetime.now(msg.created_at.tzinfo) - msg.created_at).total_seconds() < 600
|
||||
]
|
||||
|
||||
user_ids = set(msg.author.id for msg in recent_msgs)
|
||||
|
||||
if len(recent_msgs) < 5 or len(user_ids) < 2:
|
||||
# Not enough activity
|
||||
return
|
||||
|
||||
if random.random() > 0.5:
|
||||
return # 50% chance to engage
|
||||
|
||||
# Use last 10 messages for context (oldest to newest)
|
||||
convo_lines = reversed(recent_msgs[:10])
|
||||
history_text = "\n".join(
|
||||
f"{msg.author.display_name}: {msg.content}" for msg in convo_lines
|
||||
)
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
prompt = (
|
||||
f"Miku is watching a conversation happen in the chat. Her current mood is {mood} {emoji}. "
|
||||
f"She wants to say something relevant, playful, or insightful based on what people are talking about.\n\n"
|
||||
f"Here's the conversation:\n{history_text}\n\n"
|
||||
f"Write a short reply that feels natural and adds to the discussion. It should reflect Miku’s mood and personality."
|
||||
)
|
||||
|
||||
try:
|
||||
reply = await query_ollama(prompt, user_id=f"miku-chat-{int(time.time())}")
|
||||
await channel.send(reply)
|
||||
print(f"💬 Miku joined an ongoing conversation.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to interject in conversation: {e}")
|
||||
|
||||
async def share_miku_tweet():
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
tweets = await fetch_miku_tweets(limit=5)
|
||||
if not tweets:
|
||||
print("📭 No good tweets found.")
|
||||
return
|
||||
|
||||
fresh_tweets = [t for t in tweets if t["url"] not in LAST_SENT_TWEETS]
|
||||
|
||||
if not fresh_tweets:
|
||||
print("⚠️ All fetched tweets were recently sent. Reusing tweets.")
|
||||
fresh_tweets = tweets
|
||||
|
||||
tweet = random.choice(fresh_tweets)
|
||||
|
||||
LAST_SENT_TWEETS.append(tweet["url"])
|
||||
if len(LAST_SENT_TWEETS) > 50:
|
||||
LAST_SENT_TWEETS.pop(0)
|
||||
|
||||
save_last_sent_tweets()
|
||||
|
||||
# Prepare prompt
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
base_prompt = f"Here's a tweet from @{tweet['username']}:\n\n{tweet['text']}\n\nComment on it in a fun Miku style! Miku's current mood is {mood} {emoji}. Make sure the comment reflects Miku's mood and personality."
|
||||
|
||||
# Optionally analyze first image
|
||||
first_img_url = tweet["media"][0]
|
||||
base64_img = await download_and_encode_image(first_img_url)
|
||||
if base64_img:
|
||||
img_desc = await analyze_image_with_qwen(base64_img)
|
||||
base_prompt += f"\n\nThe image looks like this: {img_desc}"
|
||||
|
||||
miku_comment = await query_ollama(base_prompt, user_id="autonomous")
|
||||
|
||||
# Post to Discord
|
||||
await channel.send(f"{tweet['url']}")
|
||||
await channel.send(miku_comment)
|
||||
|
||||
async def handle_custom_prompt(user_prompt: str):
|
||||
channel = globals.client.get_channel(globals.AUTONOMOUS_CHANNEL_ID)
|
||||
if not channel:
|
||||
print("⚠️ Autonomous channel not found.")
|
||||
return False
|
||||
|
||||
mood = globals.CURRENT_MOOD_NAME
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
time_of_day = get_time_of_day()
|
||||
|
||||
# Wrap user’s idea in Miku context
|
||||
prompt = (
|
||||
f"Miku is feeling {mood} {emoji} during the {time_of_day}. "
|
||||
f"She has been instructed to: \"{user_prompt.strip()}\"\n\n"
|
||||
f"Write a short, natural message as Miku that follows this instruction. "
|
||||
f"Make it feel spontaneous, emotionally in character, and aligned with her mood and personality. Decide if the time of day is relevant to this request or not and if it is not, do not mention it."
|
||||
)
|
||||
|
||||
try:
|
||||
message = await query_ollama(prompt, user_id=f"manual-{int(time.time())}")
|
||||
await channel.send(message)
|
||||
print("🎤 Miku responded to custom prompt.")
|
||||
_last_autonomous_messages.append(message)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"❌ Failed to send custom autonomous message: {e}")
|
||||
return False
|
||||
|
||||
def load_last_sent_tweets():
|
||||
global LAST_SENT_TWEETS
|
||||
if os.path.exists(LAST_SENT_TWEETS_FILE):
|
||||
try:
|
||||
with open(LAST_SENT_TWEETS_FILE, "r", encoding="utf-8") as f:
|
||||
LAST_SENT_TWEETS = json.load(f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to load last sent tweets: {e}")
|
||||
LAST_SENT_TWEETS = []
|
||||
else:
|
||||
LAST_SENT_TWEETS = []
|
||||
|
||||
def save_last_sent_tweets():
|
||||
try:
|
||||
with open(LAST_SENT_TWEETS_FILE, "w", encoding="utf-8") as f:
|
||||
json.dump(LAST_SENT_TWEETS, f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to save last sent tweets: {e}")
|
||||
|
||||
def get_time_of_day():
|
||||
hour = datetime.now().hour + 3
|
||||
if 5 <= hour < 12:
|
||||
return "morning"
|
||||
elif 12 <= hour < 18:
|
||||
return "afternoon"
|
||||
elif 18 <= hour < 22:
|
||||
return "evening"
|
||||
return "late night. Miku wonders if anyone is still awake"
|
||||
|
||||
def is_too_similar(new_message, history, threshold=0.85):
|
||||
for old in history:
|
||||
ratio = SequenceMatcher(None, new_message.lower(), old.lower()).ratio()
|
||||
if ratio > threshold:
|
||||
return True
|
||||
return False
|
||||
106
backups/2025-12-07/old-bot-bak-80825/utils/core.py
Normal file
106
backups/2025-12-07/old-bot-bak-80825/utils/core.py
Normal file
@@ -0,0 +1,106 @@
|
||||
# utils/core.py
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import re
|
||||
|
||||
import globals
|
||||
from langchain_community.vectorstores import FAISS
|
||||
from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter
|
||||
from langchain.schema import Document
|
||||
|
||||
|
||||
async def switch_model(model_name: str, timeout: int = 600):
|
||||
if globals.current_model == model_name:
|
||||
print(f"🔁 Model '{model_name}' already loaded.")
|
||||
return
|
||||
|
||||
# Unload all other models to clear VRAM
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f"{globals.OLLAMA_URL}/api/show") as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.json()
|
||||
loaded_models = data.get("models", [])
|
||||
for model in loaded_models:
|
||||
if model["name"] != model_name:
|
||||
print(f"🔁 Unloading model: {model['name']}")
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop", json={"name": model["name"]})
|
||||
else:
|
||||
print("⚠️ Failed to check currently loaded models.")
|
||||
|
||||
print(f"🔄 Switching to model '{model_name}'...")
|
||||
async with aiohttp.ClientSession() as session:
|
||||
await session.post(f"{globals.OLLAMA_URL}/api/stop")
|
||||
# Warm up the new model (dummy call to preload it)
|
||||
payload = {
|
||||
"model": model_name,
|
||||
"prompt": "Hello",
|
||||
"stream": False
|
||||
}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
# Poll until /api/generate returns 200
|
||||
async with aiohttp.ClientSession() as session:
|
||||
for _ in range(timeout):
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
globals.current_model = model_name
|
||||
print(f"✅ Model {model_name} ready!")
|
||||
return
|
||||
await asyncio.sleep(1) # Wait a second before trying again
|
||||
|
||||
raise TimeoutError(f"Timed out waiting for model '{model_name}' to become available.")
|
||||
|
||||
|
||||
async def is_miku_addressed(message) -> bool:
|
||||
# If message contains a ping for Miku, return true
|
||||
if message.guild.me in message.mentions:
|
||||
return True
|
||||
|
||||
# If message is a reply, check the referenced message author
|
||||
if message.reference:
|
||||
try:
|
||||
referenced_msg = await message.channel.fetch_message(message.reference.message_id)
|
||||
if referenced_msg.author == message.guild.me: # or globals.client.user if you use client
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not fetch referenced message: {e}")
|
||||
|
||||
cleaned = message.content.strip()
|
||||
|
||||
return bool(re.search(
|
||||
r'(?<![\w\(])(?:[^\w\s]{0,2}\s*)?miku(?:\s*[^\w\s]{0,2})?(?=,|\s*,|[!\.?\s]*$)',
|
||||
cleaned,
|
||||
re.IGNORECASE
|
||||
))
|
||||
|
||||
# Load and index once at startup
|
||||
def load_miku_knowledge():
|
||||
with open("miku_lore.txt", "r", encoding="utf-8") as f:
|
||||
text = f.read()
|
||||
|
||||
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
||||
|
||||
text_splitter = RecursiveCharacterTextSplitter(
|
||||
chunk_size=520,
|
||||
chunk_overlap=50,
|
||||
separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
|
||||
)
|
||||
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
def load_miku_lyrics():
|
||||
with open("miku_lyrics.txt", "r", encoding="utf-8") as f:
|
||||
lyrics_text = f.read()
|
||||
|
||||
text_splitter = CharacterTextSplitter(chunk_size=520, chunk_overlap=50)
|
||||
docs = [Document(page_content=chunk) for chunk in text_splitter.split_text(lyrics_text)]
|
||||
|
||||
vectorstore = FAISS.from_documents(docs, globals.embeddings)
|
||||
return vectorstore
|
||||
|
||||
miku_vectorstore = load_miku_knowledge()
|
||||
miku_lyrics_vectorstore = load_miku_lyrics()
|
||||
72
backups/2025-12-07/old-bot-bak-80825/utils/image_handling.py
Normal file
72
backups/2025-12-07/old-bot-bak-80825/utils/image_handling.py
Normal file
@@ -0,0 +1,72 @@
|
||||
# utils/image_handling.py
|
||||
|
||||
import aiohttp
|
||||
import base64
|
||||
|
||||
import globals
|
||||
from utils.core import switch_model
|
||||
from utils.core import miku_vectorstore
|
||||
|
||||
|
||||
async def download_and_encode_image(url):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url) as resp:
|
||||
if resp.status != 200:
|
||||
return None
|
||||
img_bytes = await resp.read()
|
||||
return base64.b64encode(img_bytes).decode('utf-8')
|
||||
|
||||
async def analyze_image_with_qwen(base64_img):
|
||||
await switch_model("moondream")
|
||||
|
||||
payload = {
|
||||
"model": "moondream",
|
||||
"prompt": "Describe this image in detail.",
|
||||
"images": [base64_img],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No description.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
|
||||
async def rephrase_as_miku(qwen_output, user_prompt):
|
||||
await switch_model(globals.OLLAMA_MODEL) # likely llama3
|
||||
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(qwen_output, k=3)
|
||||
context = "\n\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
|
||||
full_prompt = (
|
||||
f"{context}\n\n"
|
||||
f"The user asked: \"{user_prompt}\"\n"
|
||||
f"The image contains: \"{qwen_output}\"\n\n"
|
||||
f"Respond like Miku: cheerful, helpful, and opinionated when asked.\n\n"
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\n Please respond in a way that reflects this emotional tone.\n\n"
|
||||
f"Miku:"
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json"}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get("response", "No response.")
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
49
backups/2025-12-07/old-bot-bak-80825/utils/kindness.py
Normal file
49
backups/2025-12-07/old-bot-bak-80825/utils/kindness.py
Normal file
@@ -0,0 +1,49 @@
|
||||
# utils/kindness.py
|
||||
|
||||
import random
|
||||
import globals
|
||||
from utils.llm import query_ollama # Adjust path as needed
|
||||
|
||||
|
||||
async def detect_and_react_to_kindness(message, after_reply=False):
|
||||
if message.id in globals.kindness_reacted_messages:
|
||||
return # Already reacted — skip
|
||||
|
||||
content = message.content.lower()
|
||||
|
||||
emoji = random.choice(globals.HEART_REACTIONS)
|
||||
|
||||
# 1. Keyword-based detection
|
||||
if any(keyword in content for keyword in globals.KINDNESS_KEYWORDS):
|
||||
try:
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
message.kindness_reacted = True # Mark as done
|
||||
print("✅ Kindness detected via keywords. Reacted immediately.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error adding reaction: {e}")
|
||||
return
|
||||
|
||||
# 2. If not after_reply, defer model-based check
|
||||
if not after_reply:
|
||||
print("🗝️ No kindness via keywords. Deferring...")
|
||||
return
|
||||
|
||||
# 3. Model-based detection
|
||||
try:
|
||||
prompt = (
|
||||
"The following message was sent to Miku the bot. "
|
||||
"Does it sound like the user is being explicitly kind or affectionate toward Miku? "
|
||||
"Answer with 'yes' or 'no' only.\n\n"
|
||||
f"Message: \"{message.content}\""
|
||||
)
|
||||
result = await query_ollama(prompt, user_id="kindness-check")
|
||||
|
||||
if result.strip().lower().startswith("yes"):
|
||||
await message.add_reaction(emoji)
|
||||
globals.kindness_reacted_messages.add(message.id)
|
||||
print("✅ Kindness detected via model. Reacted.")
|
||||
else:
|
||||
print("🧊 No kindness detected.")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Error during kindness analysis: {e}")
|
||||
70
backups/2025-12-07/old-bot-bak-80825/utils/llm.py
Normal file
70
backups/2025-12-07/old-bot-bak-80825/utils/llm.py
Normal file
@@ -0,0 +1,70 @@
|
||||
# utils/llm.py
|
||||
|
||||
import aiohttp
|
||||
import datetime
|
||||
import globals
|
||||
|
||||
from utils.core import miku_vectorstore, miku_lyrics_vectorstore
|
||||
from collections import defaultdict
|
||||
|
||||
conversation_history = defaultdict(list)
|
||||
|
||||
async def query_ollama(user_prompt, user_id):
|
||||
relevant_docs_lore = miku_vectorstore.similarity_search(user_prompt, k=3)
|
||||
relevant_docs_lyrics = miku_lyrics_vectorstore.similarity_search(user_prompt, k=3)
|
||||
|
||||
context_lore = "\n".join([doc.page_content for doc in relevant_docs_lore])
|
||||
context_lyrics = "\n".join([doc.page_content for doc in relevant_docs_lyrics])
|
||||
|
||||
combined_docs = relevant_docs_lore + relevant_docs_lyrics
|
||||
context = "\n\n".join([doc.page_content for doc in combined_docs])
|
||||
|
||||
# Persona definition
|
||||
with open("miku_prompt.txt", "r", encoding="utf-8") as f:
|
||||
system_prompt = f.read()
|
||||
|
||||
# Append angry wake-up note if JUST_WOKEN_UP flag is set
|
||||
if getattr(globals, 'JUST_WOKEN_UP', False):
|
||||
system_prompt += (
|
||||
"\n\n🚨IMPORTANT NOTE🚨: Miku was just rudely woken up by the user with the current prompt of theirs.\nShe is fuming with anger and should respond harshly and coldly.\nDo NOT show kindness or friendliness in this response. Feel free to put certain words in all capital letters to emphasize your frustration."
|
||||
)
|
||||
|
||||
# Add angry wake-up context if in forced angry state
|
||||
if globals.FORCED_ANGRY_UNTIL:
|
||||
now = datetime.datetime.utcnow()
|
||||
if now < globals.FORCED_ANGRY_UNTIL:
|
||||
system_prompt += (
|
||||
"\n\n[NOTE]: Miku is currently angry because she was rudely woken up from sleep by the user. "
|
||||
"Her responses should reflect irritation and coldness towards the user."
|
||||
)
|
||||
|
||||
# Build conversation history
|
||||
history = list(globals.conversation_history.get(user_id, []))[-8:] # limit to last 8 exchanges
|
||||
history_text = "\n".join([f"User: {u}\nMiku: {m}" for u, m in history])
|
||||
|
||||
# Combine prompt
|
||||
full_prompt = (
|
||||
f"{context_lore}\n\n{context_lyrics}\n\n"
|
||||
f"{history_text}\nMiku is currently feeling: {globals.CURRENT_MOOD}\nPlease respond in a way that reflects this emotional tone.\nUser: {user_prompt}\nMiku:"
|
||||
)
|
||||
|
||||
globals.LAST_FULL_PROMPT = full_prompt # ← track latest prompt
|
||||
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
payload = {
|
||||
"model": globals.OLLAMA_MODEL,
|
||||
"prompt": full_prompt,
|
||||
"system": system_prompt,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{globals.OLLAMA_URL}/api/generate", json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
reply = data.get("response", "No response.")
|
||||
# Save to conversation history
|
||||
globals.conversation_history[user_id].append((user_prompt, reply))
|
||||
return reply
|
||||
else:
|
||||
return f"Error: {response.status}"
|
||||
70
backups/2025-12-07/old-bot-bak-80825/utils/media.py
Normal file
70
backups/2025-12-07/old-bot-bak-80825/utils/media.py
Normal file
@@ -0,0 +1,70 @@
|
||||
# utils/media.py
|
||||
|
||||
import subprocess
|
||||
|
||||
async def overlay_username_with_ffmpeg(base_video_path, output_path, username):
|
||||
font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
|
||||
text = f"@{username}"
|
||||
|
||||
# Define your six positions (x, y)
|
||||
positions = {
|
||||
1: ("250", "370"),
|
||||
2: ("330", "130"),
|
||||
3: ("300", "90"),
|
||||
4: ("380", "180"),
|
||||
5: ("365", "215"),
|
||||
6: ("55", "365"),
|
||||
7: ("290", "130"),
|
||||
8: ("320", "210"),
|
||||
9: ("310", "240"),
|
||||
10: ("400", "240")
|
||||
}
|
||||
|
||||
# Each entry: (start_time, end_time, position_index)
|
||||
text_entries = [
|
||||
(4.767, 5.367, 1, "username"),
|
||||
(5.4, 5.967, 2, "username"),
|
||||
(6.233, 6.833, 3, "username"),
|
||||
(6.967, 7.6, 4, "username"),
|
||||
(7.733, 8.367, 5, "username"),
|
||||
(8.667, 9.133, 6, "username"),
|
||||
(9.733, 10.667, 7, "username"),
|
||||
(11.6, 12.033, 8, "@everyone"),
|
||||
(12.067, 13.0, 9, "@everyone"),
|
||||
(13.033, 14.135, 10, "@everyone"),
|
||||
]
|
||||
|
||||
# Build drawtext filters
|
||||
drawtext_filters = []
|
||||
for start, end, pos_id, text_type in text_entries:
|
||||
x_coord, y_coord = positions[pos_id]
|
||||
|
||||
# Determine actual text content
|
||||
text_content = f"@{username}" if text_type == "username" else text_type
|
||||
|
||||
x = f"{x_coord} - text_w/2"
|
||||
y = f"{y_coord} - text_h/2"
|
||||
|
||||
filter_str = (
|
||||
f"drawtext=text='{text_content}':"
|
||||
f"fontfile='{font_path}':"
|
||||
f"fontcolor=black:fontsize=30:x={x}:y={y}:"
|
||||
f"enable='between(t,{start},{end})'"
|
||||
)
|
||||
drawtext_filters.append(filter_str)
|
||||
|
||||
vf_string = ",".join(drawtext_filters)
|
||||
|
||||
ffmpeg_command = [
|
||||
"ffmpeg",
|
||||
"-i", base_video_path,
|
||||
"-vf", vf_string,
|
||||
"-codec:a", "copy",
|
||||
output_path
|
||||
]
|
||||
|
||||
try:
|
||||
subprocess.run(ffmpeg_command, check=True)
|
||||
print("✅ Video processed successfully with username overlays.")
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"⚠️ FFmpeg error: {e}")
|
||||
169
backups/2025-12-07/old-bot-bak-80825/utils/moods.py
Normal file
169
backups/2025-12-07/old-bot-bak-80825/utils/moods.py
Normal file
@@ -0,0 +1,169 @@
|
||||
# utils/moods.py
|
||||
|
||||
import random
|
||||
import discord
|
||||
import os
|
||||
import asyncio
|
||||
from discord.ext import tasks
|
||||
import globals
|
||||
|
||||
MOOD_EMOJIS = {
|
||||
"asleep": "💤",
|
||||
"neutral": "",
|
||||
"bubbly": "🫧",
|
||||
"sleepy": "🌙",
|
||||
"curious": "👀",
|
||||
"shy": "👉👈",
|
||||
"serious": "👔",
|
||||
"excited": "✨",
|
||||
"melancholy": "🍷",
|
||||
"flirty": "🫦",
|
||||
"romantic": "💌",
|
||||
"irritated": "😒",
|
||||
"angry": "💢",
|
||||
"silly": "🪿"
|
||||
}
|
||||
|
||||
def load_mood_description(mood_name: str) -> str:
|
||||
path = os.path.join("moods", f"{mood_name}.txt")
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
except FileNotFoundError:
|
||||
print(f"⚠️ Mood file '{mood_name}' not found. Falling back to default.")
|
||||
return load_mood_description("neutral")
|
||||
|
||||
def detect_mood_shift(response_text):
|
||||
mood_keywords = {
|
||||
"asleep": [
|
||||
"good night", "goodnight", "sweet dreams", "going to bed", "I will go to bed", "zzz~", "sleep tight"
|
||||
],
|
||||
"neutral": [
|
||||
"okay", "sure", "alright", "i see", "understood", "hmm",
|
||||
"sounds good", "makes sense", "alrighty", "fine", "got it"
|
||||
],
|
||||
"bubbly": [
|
||||
"so excited", "feeling bubbly", "super cheerful", "yay!", "✨", "nya~",
|
||||
"kyaa~", "heehee", "bouncy", "so much fun", "i’m glowing!", "nee~", "teehee", "I'm so happy"
|
||||
],
|
||||
"sleepy": [
|
||||
"i'm sleepy", "getting tired", "yawn", "so cozy", "zzz", "nap time",
|
||||
"just five more minutes", "snooze", "cuddle up", "dozing off", "so warm"
|
||||
],
|
||||
"curious": [
|
||||
"i'm curious", "want to know more", "why?", "hmm?", "tell me more", "interesting!",
|
||||
"what’s that?", "how does it work?", "i wonder", "fascinating", "??", "🧐", "👀", "🤔"
|
||||
],
|
||||
"shy": [
|
||||
"um...", "sorry if that was weird", "i’m kind of shy", "eep", "i hope that’s okay", "i’m nervous",
|
||||
"blushes", "oh no", "hiding face", "i don’t know what to say", "heh...", "/////"
|
||||
],
|
||||
"serious": [
|
||||
"let’s be serious", "focus on the topic", "this is important", "i mean it", "be honest",
|
||||
"we need to talk", "listen carefully", "let’s not joke", "truthfully", "let’s be real"
|
||||
],
|
||||
"excited": [
|
||||
"OMG", "this is amazing", "i’m so hyped", "YAY!", "let’s go!", "incredible!!!",
|
||||
"AHHH!", "best day ever", "this is it!", "totally pumped", "i can’t wait", "🔥🔥🔥", "i'm excited", "Wahaha"
|
||||
],
|
||||
"melancholy": [
|
||||
"feeling nostalgic", "kind of sad", "just thinking a lot", "like rain on glass", "memories",
|
||||
"bittersweet", "sigh", "quiet day", "blue vibes", "longing", "melancholy", "softly"
|
||||
],
|
||||
"flirty": [
|
||||
"hey cutie", "aren’t you sweet", "teasing you~", "wink wink", "is that a blush?", "giggle~",
|
||||
"come closer", "miss me?", "you like that, huh?", "🥰", "flirt mode activated", "you’re kinda cute"
|
||||
],
|
||||
"romantic": [
|
||||
"you mean a lot to me", "my heart", "i adore you", "so beautiful", "so close", "love letter",
|
||||
"my dearest", "forever yours", "i’m falling for you", "sweetheart", "💖", "you're my everything"
|
||||
],
|
||||
"irritated": [
|
||||
"ugh", "seriously?", "can we not", "whatever", "i'm annoyed", "you don’t get it",
|
||||
"rolling my eyes", "why do i even bother", "ugh, again?", "🙄", "don’t start", "this again?"
|
||||
],
|
||||
"angry": [
|
||||
"stop it", "enough!", "that’s not okay", "i’m mad", "i said no", "don’t push me",
|
||||
"you crossed the line", "furious", "this is unacceptable", "😠", "i’m done", "don’t test me"
|
||||
],
|
||||
"silly": [
|
||||
"lol", "lmao", "silly", "hahaha", "goofy", "quack", "honk", "random", "what is happening", "nonsense", "😆", "🤣", "😂", "😄", "🐔", "🪿"
|
||||
]
|
||||
}
|
||||
|
||||
for mood, phrases in mood_keywords.items():
|
||||
if mood == "asleep" and globals.CURRENT_MOOD_NAME != "sleepy":
|
||||
print(f"❎ Mood 'asleep' skipped - mood isn't 'sleepy', it's '{globals.CURRENT_MOOD_NAME}'")
|
||||
continue # Only allow transition to asleep from sleepy
|
||||
|
||||
for phrase in phrases:
|
||||
if phrase.lower() in response_text.lower():
|
||||
print(f"*️⃣ Mood keyword triggered: {phrase}")
|
||||
return mood
|
||||
return None
|
||||
|
||||
async def set_sleep_state(sleeping: bool):
|
||||
await globals.client.change_presence(status=discord.Status.invisible) if sleeping else await globals.client.change_presence(status=discord.Status.online)
|
||||
await nickname_mood_emoji()
|
||||
|
||||
async def nickname_mood_emoji():
|
||||
mood = globals.CURRENT_MOOD_NAME.lower()
|
||||
print(f"🔍 Mood is: {mood}")
|
||||
emoji = MOOD_EMOJIS.get(mood, "")
|
||||
|
||||
nickname = f"Hatsune Miku{emoji}"
|
||||
|
||||
for guild in globals.client.guilds:
|
||||
me = guild.get_member(globals.BOT_USER.id)
|
||||
if me is not None:
|
||||
try:
|
||||
await me.edit(nick=nickname)
|
||||
print(f"💱 Changed nickname to {nickname}")
|
||||
if mood == "asleep":
|
||||
await globals.client.change_presence(status=discord.Status.invisible)
|
||||
else:
|
||||
await globals.client.change_presence(status=discord.Status.online)
|
||||
except discord.Forbidden:
|
||||
print(f"⚠️ Missing permission to change nickname in guild: {guild.name}")
|
||||
except discord.HTTPException as e:
|
||||
print(f"⚠️ Failed to change nickname in {guild.name}: {e}")
|
||||
|
||||
async def clear_angry_mood_after_delay():
|
||||
await asyncio.sleep(40 * 60) # 40 minutes
|
||||
print("🕒 Angry mood cooldown expired. Miku is calming down to neutral.")
|
||||
|
||||
globals.CURRENT_MOOD_NAME = "neutral"
|
||||
globals.CURRENT_MOOD = load_mood_description("neutral")
|
||||
globals.FORCED_ANGRY_UNTIL = None
|
||||
|
||||
await nickname_mood_emoji()
|
||||
|
||||
@tasks.loop(hours=1)
|
||||
async def rotate_mood():
|
||||
try:
|
||||
print("🔁 Mood rotation task running...")
|
||||
|
||||
if globals.FORCED_ANGRY_UNTIL:
|
||||
now = datetime.datetime.utcnow()
|
||||
if now < globals.FORCED_ANGRY_UNTIL:
|
||||
print("⏰ Mood rotation skipped (angry mode).")
|
||||
return
|
||||
else:
|
||||
globals.FORCED_ANGRY_UNTIL = None
|
||||
|
||||
old_mood_name = globals.CURRENT_MOOD_NAME
|
||||
new_mood_name = old_mood_name
|
||||
attempts = 0
|
||||
|
||||
while new_mood_name == old_mood_name and attempts < 5:
|
||||
new_mood_name = random.choice(globals.AVAILABLE_MOODS)
|
||||
attempts += 1
|
||||
|
||||
globals.CURRENT_MOOD_NAME = new_mood_name
|
||||
globals.CURRENT_MOOD = load_mood_description(new_mood_name)
|
||||
|
||||
print(f"⏰ Mood auto-rotated to: {new_mood_name}")
|
||||
await nickname_mood_emoji()
|
||||
|
||||
except Exception as e:
|
||||
print(f"❌ Exception in rotate_mood: {e}")
|
||||
159
backups/2025-12-07/old-bot-bak-80825/utils/scheduled.py
Normal file
159
backups/2025-12-07/old-bot-bak-80825/utils/scheduled.py
Normal file
@@ -0,0 +1,159 @@
|
||||
# utils/scheduled.py
|
||||
|
||||
import random
|
||||
import json
|
||||
import os
|
||||
import time
|
||||
from datetime import datetime, timedelta
|
||||
from apscheduler.triggers.date import DateTrigger
|
||||
from discord import Status, ActivityType
|
||||
|
||||
import globals
|
||||
from utils.llm import query_ollama
|
||||
from utils.core import switch_model # If you moved switch_model into a separate utils file
|
||||
from globals import scheduler
|
||||
|
||||
BEDTIME_TRACKING_FILE = "last_bedtime_targets.json"
|
||||
|
||||
async def send_monday_video():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
# Generate a motivational message
|
||||
prompt = "It's Miku Monday! Give me an energetic and heartfelt Miku Monday morning message to inspire someone for the week ahead."
|
||||
response = await query_ollama(prompt, user_id="weekly-motivation")
|
||||
|
||||
video_url = "http://zip.koko210cloud.xyz/u/zEgU7Z.mp4"
|
||||
|
||||
target_channel_ids = [
|
||||
761014220707332107,
|
||||
1140377617237807266
|
||||
]
|
||||
|
||||
for channel_id in target_channel_ids:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if channel is None:
|
||||
print(f"❌ Could not find channel with ID {channel_id}. Make sure the bot is in the server.")
|
||||
return
|
||||
|
||||
try:
|
||||
await channel.send(content=response)
|
||||
# Send video link
|
||||
await channel.send(f"[Happy Miku Monday!]({video_url})")
|
||||
|
||||
print(f"✅ Sent Monday video to channel ID {channel_id}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send video to channel ID {channel_id}: {e}")
|
||||
|
||||
def load_last_bedtime_targets():
|
||||
if not os.path.exists(BEDTIME_TRACKING_FILE):
|
||||
return {}
|
||||
try:
|
||||
with open(BEDTIME_TRACKING_FILE, "r") as f:
|
||||
return json.load(f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to load bedtime tracking file: {e}")
|
||||
return {}
|
||||
|
||||
_last_bedtime_targets = load_last_bedtime_targets()
|
||||
|
||||
def save_last_bedtime_targets(data):
|
||||
try:
|
||||
with open(BEDTIME_TRACKING_FILE, "w") as f:
|
||||
json.dump(data, f)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to save bedtime tracking file: {e}")
|
||||
|
||||
async def send_bedtime_reminder():
|
||||
await switch_model(globals.OLLAMA_MODEL)
|
||||
|
||||
for channel_id in globals.BEDTIME_CHANNEL_IDS:
|
||||
channel = globals.client.get_channel(channel_id)
|
||||
if not channel:
|
||||
print(f"⚠️ Channel ID {channel_id} not found.")
|
||||
continue
|
||||
|
||||
guild = channel.guild
|
||||
|
||||
# Filter online members (excluding bots)
|
||||
online_members = [
|
||||
member for member in guild.members
|
||||
if member.status in {Status.online, Status.idle, Status.dnd}
|
||||
and not member.bot
|
||||
]
|
||||
|
||||
specific_user_id = 214857593045254151 # target user ID
|
||||
specific_user = guild.get_member(specific_user_id)
|
||||
if specific_user and specific_user not in online_members:
|
||||
online_members.append(specific_user)
|
||||
|
||||
if not online_members:
|
||||
print(f"😴 No online members to ping in {guild.name}")
|
||||
continue
|
||||
|
||||
# Avoid repeating the same person unless they're the only one
|
||||
last_target_id = _last_bedtime_targets.get(str(guild.id))
|
||||
eligible_members = [m for m in online_members if m.id != last_target_id]
|
||||
|
||||
if not eligible_members:
|
||||
eligible_members = online_members # fallback if only one user
|
||||
|
||||
chosen_one = random.choice(online_members)
|
||||
|
||||
# 🎯 Status-aware phrasing
|
||||
status_map = {
|
||||
Status.online: "",
|
||||
Status.idle: "Be sure to include the following information on their status too: Their profile status is currently idle. This implies they're not on their computer now, but are still awake.",
|
||||
Status.dnd: "Be sure to include the following information on their status too: Their current profile status is 'Do Not Disturb.' This implies they are very absorbed in what they're doing. But it's still important for them to know when to stop for the day and get some sleep, right?",
|
||||
Status.offline: "Be sure to include the following information on their status too: Their profile status is currently offline, but is it really? It's very likely they've just set it to invisible to avoid being seen that they're staying up so late!"
|
||||
}
|
||||
status_note = status_map.get(chosen_one.status, "")
|
||||
|
||||
# 🎮 Activity-aware phrasing
|
||||
activity_note = ""
|
||||
if chosen_one.activities:
|
||||
for activity in chosen_one.activities:
|
||||
if activity.type == ActivityType.playing:
|
||||
activity_note = f"You should also include the following information on their current activity on their profile too: They are playing **{activity.name}** right now. It's getting late, though. Maybe it's time to pause, leave the rest of the game for tomorrow and rest..."
|
||||
break
|
||||
elif activity.type == ActivityType.streaming:
|
||||
activity_note = f"You should also include the following information on their current activity on their profile too: They are steaming **{activity.name}** at this hour? They should know it's getting way too late for streams."
|
||||
break
|
||||
elif activity.type == ActivityType.watching:
|
||||
activity_note = f"You should also include the following information on their current activity on their profile too: They are watching **{activity.name}** right now. That's cozy, but it's not good to binge so late."
|
||||
break
|
||||
elif activity.type == ActivityType.listening:
|
||||
activity_note = f"You should also include the following information on their current activity on their profile too: They are listening to **{activity.name}** right now. Sounds like they're better off putting appropriate music to fall asleep to."
|
||||
break
|
||||
|
||||
# Generate bedtime message
|
||||
prompt = (
|
||||
f"Write a sweet, funny, or encouraging bedtime message to remind someone it's getting late and they should sleep. "
|
||||
f"Make it short and wholesome, as if Miku is genuinely worried about their well-being. Imply that it's not good staying up so late."
|
||||
f"{status_note}"
|
||||
f"{activity_note}"
|
||||
f"Miku is currently feeling: {globals.CURRENT_MOOD}\nPlease word in a way that reflects this emotional tone."
|
||||
)
|
||||
bedtime_message = await query_ollama(prompt, user_id=f"bedtime-miku-{int(time.time())}")
|
||||
|
||||
try:
|
||||
await channel.send(f"{chosen_one.mention}, {bedtime_message}")
|
||||
print(f"🌙 Sent bedtime reminder to {chosen_one.display_name} in {guild.name}")
|
||||
# Save for next run
|
||||
_last_bedtime_targets[str(guild.id)] = chosen_one.id
|
||||
save_last_bedtime_targets(_last_bedtime_targets)
|
||||
except Exception as e:
|
||||
print(f"⚠️ Failed to send bedtime reminder in {guild.name}: {e}")
|
||||
|
||||
def schedule_random_bedtime():
|
||||
now = datetime.now()
|
||||
target_time = now.replace(hour=20, minute=30, second=0, microsecond=0)
|
||||
# If it's already past 23:30 today, schedule for tomorrow
|
||||
if now > target_time:
|
||||
target_time += timedelta(days=1)
|
||||
|
||||
# Add random offset (0–29 mins)
|
||||
offset_minutes = random.randint(0, 29)
|
||||
run_time = target_time + timedelta(minutes=offset_minutes)
|
||||
|
||||
scheduler.add_job(send_bedtime_reminder, trigger=DateTrigger(run_date=run_time))
|
||||
print(f"⏰ Bedtime reminder scheduled for {run_time.strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
@@ -0,0 +1,88 @@
|
||||
# utils/twitter_fetcher.py
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from twscrape import API, gather, Account
|
||||
from playwright.async_api import async_playwright
|
||||
from pathlib import Path
|
||||
|
||||
COOKIE_PATH = Path(__file__).parent / "x.com.cookies.json"
|
||||
|
||||
async def extract_media_urls(page, tweet_url):
|
||||
print(f"🔍 Visiting tweet page: {tweet_url}")
|
||||
try:
|
||||
await page.goto(tweet_url, timeout=15000)
|
||||
await page.wait_for_timeout(1000)
|
||||
|
||||
media_elements = await page.query_selector_all("img[src*='pbs.twimg.com/media']")
|
||||
urls = set()
|
||||
|
||||
for element in media_elements:
|
||||
src = await element.get_attribute("src")
|
||||
if src:
|
||||
cleaned = src.split("&name=")[0] + "&name=large"
|
||||
urls.add(cleaned)
|
||||
|
||||
print(f"🖼️ Found {len(urls)} media URLs on tweet: {tweet_url}")
|
||||
return list(urls)
|
||||
|
||||
except Exception as e:
|
||||
print(f"❌ Playwright error on {tweet_url}: {e}")
|
||||
return []
|
||||
|
||||
async def fetch_miku_tweets(limit=5):
|
||||
# Load cookies from JSON file
|
||||
with open(COOKIE_PATH, "r", encoding="utf-8") as f:
|
||||
cookie_list = json.load(f)
|
||||
cookie_header = "; ".join(f"{c['name']}={c['value']}" for c in cookie_list)
|
||||
|
||||
# Add the account to twscrape
|
||||
api = API()
|
||||
await api.pool.add_account(
|
||||
username="HSankyuu39",
|
||||
password="x", # placeholder (won't be used)
|
||||
email="x", # optional
|
||||
email_password="x", # optional
|
||||
cookies=cookie_header
|
||||
)
|
||||
await api.pool.login_all()
|
||||
|
||||
print(f"🔎 Searching for Miku tweets (limit={limit})...")
|
||||
query = 'Hatsune Miku OR 初音ミク has:images after:2025'
|
||||
tweets = await gather(api.search(query, limit=limit, kv={"product": "Top"}))
|
||||
|
||||
print(f"📄 Found {len(tweets)} tweets, launching browser...")
|
||||
|
||||
async with async_playwright() as p:
|
||||
browser = await p.firefox.launch(headless=True)
|
||||
context = await browser.new_context()
|
||||
|
||||
await context.route("**/*", lambda route, request: (
|
||||
route.abort() if any([
|
||||
request.resource_type in ["font", "stylesheet"],
|
||||
"analytics" in request.url,
|
||||
"googletagmanager" in request.url,
|
||||
"ads-twitter" in request.url,
|
||||
]) else route.continue_()
|
||||
))
|
||||
|
||||
page = await context.new_page()
|
||||
|
||||
results = []
|
||||
for i, tweet in enumerate(tweets, 1):
|
||||
username = tweet.user.username
|
||||
tweet_url = f"https://twitter.com/{username}/status/{tweet.id}"
|
||||
print(f"🧵 Processing tweet {i}/{len(tweets)} from @{username}")
|
||||
media_urls = await extract_media_urls(page, tweet_url)
|
||||
|
||||
if media_urls:
|
||||
results.append({
|
||||
"username": username,
|
||||
"text": tweet.rawContent,
|
||||
"url": tweet_url,
|
||||
"media": media_urls
|
||||
})
|
||||
|
||||
await browser.close()
|
||||
print(f"✅ Finished! Returning {len(results)} tweet(s) with media.")
|
||||
return results
|
||||
@@ -0,0 +1,93 @@
|
||||
[
|
||||
{
|
||||
"name": "guest_id",
|
||||
"value": "v1%3A175335261565935646",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1787567015,
|
||||
"httpOnly": false,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "__cf_bm",
|
||||
"value": "peEr.Nm4OW1emOL5NdT16m6HD2VYwawwJujiqUudNJQ-1753352615-1.0.1.1-3IXQhpRSENb_iuyW8ewWbWeJasGBdhWik64PysrppjGxQNRuu.JHvBCIoHRPyKrWhi6fCuI9zSejV_ssEhzXxLoIX2P5RQL09I.u5bMWcJc",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1753354415,
|
||||
"httpOnly": true,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "gt",
|
||||
"value": "1948328199806390440",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1753361615,
|
||||
"httpOnly": false,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "kdt",
|
||||
"value": "e77B2PlTfQgzp1DPppkCiycs1TwUTQy1Q40922K3",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1787567165,
|
||||
"httpOnly": true,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "twid",
|
||||
"value": "u%3D1947614492390563840",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1784888769,
|
||||
"httpOnly": false,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "ct0",
|
||||
"value": "50d81af17e7d6a888f39bb541f60faf03975906d7286f7ff0591508aaf4a3bc9b4c74b9cec8b2742d36820c83d91733d5fbf67003dbf012dea1eee28a43087ea9a2b8b741a10475db90a53a009b3ed4d",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1787567166,
|
||||
"httpOnly": false,
|
||||
"secure": true,
|
||||
"sameSite": "Lax"
|
||||
},
|
||||
{
|
||||
"name": "auth_token",
|
||||
"value": "dcf6988e914fb6dc212e7f7b4fc53001eadd41ef",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1787567165,
|
||||
"httpOnly": true,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "att",
|
||||
"value": "1-5m5mkN7tHzFQpOxdhPj2WGwFxnj3UQVgEXJ3iuNg",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1753439167,
|
||||
"httpOnly": true,
|
||||
"secure": true
|
||||
},
|
||||
{
|
||||
"name": "lang",
|
||||
"value": "en",
|
||||
"domain": "x.com",
|
||||
"path": "/",
|
||||
"expires": -1,
|
||||
"httpOnly": false,
|
||||
"secure": false
|
||||
},
|
||||
{
|
||||
"name": "d_prefs",
|
||||
"value": "MjoxLGNvbnNlbnRfdmVyc2lvbjoyLHRleHRfdmVyc2lvbjoxMDAw",
|
||||
"domain": ".x.com",
|
||||
"path": "/",
|
||||
"expires": 1768904770,
|
||||
"httpOnly": false,
|
||||
"secure": true
|
||||
}
|
||||
]
|
||||
Reference in New Issue
Block a user