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core/knowledge_engine.py

@@ -39,40 +39,51 @@ class KnowledgeEngine:
     def __init__(self, persist_dir: str = "./chroma_db"):
         self.persist_dir = Path(persist_dir)
         self.persist_dir.mkdir(parents=True, exist_ok=True)
+        self.index = None
+        self._initialized = False
 
         if not LLAMAINDEX_AVAILABLE:
-            self.index = None
             return
 
-        # Configure LlamaIndex settings
-        Settings.embed_model = OpenAIEmbedding(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="text-embedding-3-small"
-        )
-        Settings.llm = Anthropic(
-            api_key=os.getenv("ANTHROPIC_API_KEY"),
-            model="claude-sonnet-4-20250514"
-        )
-
-        # Initialize ChromaDB
-        self.chroma_client = chromadb.PersistentClient(path=str(self.persist_dir))
-        self.chroma_collection = self.chroma_client.get_or_create_collection("omnimind_knowledge")
-
-        # Vector store
-        self.vector_store = ChromaVectorStore(chroma_collection=self.chroma_collection)
-        self.storage_context = StorageContext.from_defaults(vector_store=self.vector_store)
+    def _ensure_initialized(self):
+        """Lazy initialization to avoid startup errors"""
+        if self._initialized or not LLAMAINDEX_AVAILABLE:
+            return
 
-        # Try to load existing index
         try:
-            self.index = load_index_from_storage(self.storage_context)
-            print("[OK] Loaded existing knowledge base")
-        except:
-            self.index = None
-            print("[INFO] No existing knowledge base - will create on first document add")
+            # Configure LlamaIndex settings
+            Settings.embed_model = OpenAIEmbedding(
+                api_key=os.getenv("OPENAI_API_KEY"),
+                model="text-embedding-3-small"
+            )
+            # Skip Anthropic LLM initialization to avoid version conflict
+            # Settings.llm = Anthropic(...)
+
+            # Initialize ChromaDB
+            self.chroma_client = chromadb.PersistentClient(path=str(self.persist_dir))
+            self.chroma_collection = self.chroma_client.get_or_create_collection("omnimind_knowledge")
+
+            # Vector store
+            self.vector_store = ChromaVectorStore(chroma_collection=self.chroma_collection)
+            self.storage_context = StorageContext.from_defaults(vector_store=self.vector_store)
+
+            # Try to load existing index
+            try:
+                self.index = load_index_from_storage(self.storage_context)
+                print("[OK] Loaded existing knowledge base")
+            except:
+                self.index = None
+                print("[INFO] No existing knowledge base - will create on first document add")
+
+            self._initialized = True
+        except Exception as e:
+            print(f"[WARNING] LlamaIndex initialization failed: {e}")
+            self._initialized = False
 
     async def add_documents(self, documents_path: str) -> Dict[str, Any]:
         """Add documents to the knowledge base"""
-        if not LLAMAINDEX_AVAILABLE:
+        self._ensure_initialized()
+        if not LLAMAINDEX_AVAILABLE or not self._initialized:
             return {"status": "unavailable", "message": "LlamaIndex not installed"}
 
         reader = SimpleDirectoryReader(documents_path)
@@ -97,7 +108,8 @@ class KnowledgeEngine:
 
     async def query(self, question: str, top_k: int = 3) -> Dict[str, Any]:
         """Query the knowledge base"""
-        if not LLAMAINDEX_AVAILABLE or self.index is None:
+        self._ensure_initialized()
+        if not LLAMAINDEX_AVAILABLE or not self._initialized or self.index is None:
             return {
                 "status": "unavailable",
                 "answer": "Knowledge base not configured",