Vector.

app/agents/vectorization_agent.py

@@ -1,29 +1,25 @@
 # app/agents/vectorization_agent.py
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain_openai import OpenAIEmbeddings
-embedding_model = OpenAIEmbeddings(model="text-embedding-3-small")
-import chromadb
-
-client = chromadb.PersistentClient(path="./chroma_db")
-vector_store = client.get_or_create_collection(name="documents")
 
 text_splitter = RecursiveCharacterTextSplitter(
     chunk_size=1000,
     chunk_overlap=100,
 )
 
-def agent_vectorize_and_store(doc_id: str, text: str, category: str, language: str):
-    """
-    Agent 4: Vectorizes a document and stores it in ChromaDB.
-    """
+def agent_vectorize_and_store(
+        doc_id: str,
+        text: str,
+        category: str,
+        language: str,
+        embedding_model,
+        vector_store
+):
     print(f"--- [Background Task] Starting vectorization (ID: {doc_id})...")
 
     try:
-        return
-
         chunks = text_splitter.split_text(text)
         if not chunks:
-            print(f"--- [Background Task] document {doc_id} has no text to vectorize.")
+            print(f"--- [Background task] document is empty, skip vectorization. (ID: {doc_id})")
             return
 
         chunk_ids = [f"{doc_id}_{i}" for i in range(len(chunks))]
@@ -38,6 +34,6 @@ def agent_vectorize_and_store(doc_id: str, text: str, category: str, language: s
             documents=chunks,
             metadatas=metadatas
         )
-        print(f"--- [Background Task] Document {doc_id} vectorized and stored successfully.")
+        print(f"--- [Background Task] Document {doc_id} vectorized。")
     except Exception as e:
-        print(f"--- [background Task] Vectorization failed (ID: {doc_id}): {e}")
+        print(f"--- [Background Task] Document vectorization failed (ID: {doc_id}): {e}")