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8b14160028
| Author | SHA1 | Date | |
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| 8b14160028 | |||
| 02686c3b96 |
@@ -1746,9 +1746,9 @@ def get_autonomous_stats():
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@app.get("/conversation/{user_id}")
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def get_conversation(user_id: str):
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if user_id in globals.conversation_history:
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return {"conversation": list(globals.conversation_history[user_id])}
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return {"conversation": []}
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"""Get conversation history for a user/channel (uses centralized ConversationHistory)."""
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messages = conversation_history.get_recent_messages(user_id)
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return {"conversation": [{"author": author, "content": content, "is_bot": is_bot} for author, content, is_bot in messages]}
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# ========== Figurine DM Subscription APIs ==========
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@app.get("/figurines/subscribers")
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@@ -4,6 +4,7 @@ import asyncio
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import globals
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from utils.moods import load_mood_description
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from utils.scheduled import send_bedtime_reminder
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from utils.conversation_history import conversation_history
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from utils.logger import get_logger
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logger = get_logger('commands')
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@@ -32,7 +33,7 @@ def calm_miku() -> str:
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def reset_conversation(user_id):
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globals.conversation_history[str(user_id)].clear()
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conversation_history.clear_channel(str(user_id))
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async def force_sleep() -> str:
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@@ -1,14 +1,10 @@
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# globals.py
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import os
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from collections import defaultdict, deque
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import discord
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from apscheduler.schedulers.asyncio import AsyncIOScheduler
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scheduler = AsyncIOScheduler()
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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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# Autonomous V2 Debug Mode (set to True to see detailed decision logging)
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@@ -26,6 +22,7 @@ VISION_MODEL = os.getenv("VISION_MODEL", "vision")
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EVIL_TEXT_MODEL = os.getenv("EVIL_TEXT_MODEL", "darkidol") # Uncensored model for evil mode
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JAPANESE_TEXT_MODEL = os.getenv("JAPANESE_TEXT_MODEL", "swallow") # Llama 3.1 Swallow model for Japanese
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OWNER_USER_ID = int(os.getenv("OWNER_USER_ID", "209381657369772032")) # Bot owner's Discord user ID for reports
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PREFER_AMD_GPU = os.getenv("PREFER_AMD_GPU", "false").lower() == "true" # Runtime-overridable via config API
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# Cheshire Cat AI integration (Phase 3)
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CHESHIRE_CAT_URL = os.getenv("CHESHIRE_CAT_URL", "http://cheshire-cat:80")
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@@ -1034,8 +1034,8 @@ async def run_argument(channel: discord.TextChannel, client, trigger_context: st
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# Clean up argument conversation history
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try:
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conversation_history.clear_history(argument_user_id)
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except:
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conversation_history.clear_channel(argument_user_id)
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except Exception:
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pass # History cleanup is not critical
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end_argument(channel_id)
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@@ -5,8 +5,8 @@ from datetime import datetime
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from typing import List, Dict, Any, Tuple
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import discord
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import globals
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from utils.conversation_history import conversation_history
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from utils.twitter_fetcher import fetch_figurine_tweets_latest
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from utils.image_handling import analyze_image_with_qwen, download_and_encode_image
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from utils.llm import query_llama
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@@ -204,15 +204,11 @@ async def send_figurine_dm_to_user(client: discord.Client, user_id: int, tweet:
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# Log the comment message
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dm_logger.log_user_message(user, comment_message, is_bot_message=True)
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# IMPORTANT: Also add to globals.conversation_history for LLM context
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# Add to conversation history for LLM context (uses centralized ConversationHistory)
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user_id_str = str(user_id)
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# Add the tweet URL as a "system message" about what Miku just sent (use original URL for context)
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tweet_context = f"[I just sent you this figurine tweet: {tweet_url}]"
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# Add the figurine comment to conversation history
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# Use empty user prompt since this was initiated by Miku
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globals.conversation_history.setdefault(user_id_str, []).append((tweet_context, miku_comment))
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conversation_history.add_message(channel_id=user_id_str, author_name="Miku", content=tweet_context, is_bot=True)
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conversation_history.add_message(channel_id=user_id_str, author_name="Miku", content=miku_comment, is_bot=True)
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logger.debug(f"Messages logged to both DM history and conversation context for user {user_id}")
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@@ -37,7 +37,8 @@ MODEL_TO_GPU = {
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}
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# Configuration
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PREFER_AMD_GPU = os.getenv("PREFER_AMD_GPU", "false").lower() == "true"
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# PREFER_AMD_GPU lives in globals so the config API can update it at runtime.
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# We read globals.PREFER_AMD_GPU in functions below instead of a frozen local.
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AMD_MODELS_ENABLED = os.getenv("AMD_MODELS_ENABLED", "true").lower() == "true"
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@@ -101,7 +102,7 @@ def get_llama_url_with_load_balancing(
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return globals.LLAMA_URL, "llama3.1"
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# AMD enabled - implement load balancing
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use_amd = prefer_amd or PREFER_AMD_GPU or (random.random() < 0.5)
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use_amd = prefer_amd or globals.PREFER_AMD_GPU or (random.random() < 0.5)
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if task_type == "evil":
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# Evil/uncensored models
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@@ -475,10 +475,6 @@ Please respond in a way that reflects this emotional tone.{pfp_context}"""
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is_bot=True
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)
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# Also save to legacy globals for backward compatibility (skip error messages)
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if user_prompt and user_prompt.strip() and reply and reply.strip() and reply != "Someone tell Koko-nii there is a problem with my AI.":
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globals.conversation_history[user_id].append((user_prompt, reply))
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return reply
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else:
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error_text = await response.text()
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