Initial commit: Miku Discord Bot

bot/utils/core.py

@@ -0,0 +1,80 @@
+# utils/core.py
+
+import asyncio
+import aiohttp
+import re
+
+import globals
+from langchain_community.vectorstores import FAISS
+from langchain_text_splitters import CharacterTextSplitter, RecursiveCharacterTextSplitter
+from langchain_core.documents import Document
+
+
+# switch_model() removed - llama-swap handles model switching automatically
+
+
+async def is_miku_addressed(message) -> bool:
+    # Check if this is a DM (no guild)
+    if message.guild is None:
+        # In DMs, always respond to every message
+        return True
+    
+    # Safety check: ensure guild and guild.me exist
+    if not message.guild or not message.guild.me:
+        print(f"⚠️ Warning: Invalid guild or guild.me in message from {message.author}")
+        return False
+    
+    # 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:
+                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
+    ))
+
+# Vectorstore functionality disabled - not needed with current structured context approach
+# If you need embeddings in the future, you can use a different embedding provider
+# For now, the bot uses structured prompts from context_manager.py
+
+# def load_miku_knowledge():
+#     with open("miku_lore.txt", "r", encoding="utf-8") as f:
+#         text = f.read()
+#     
+#     from langchain_text_splitters 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=520, 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()