Vector.

app/core/vector_store.py

@@ -1,47 +1,28 @@
-# app/core/vector_store.py
 import os
 import chromadb
 from dotenv import load_dotenv
 from langchain_openai import AzureOpenAIEmbeddings, OpenAIEmbeddings
 
 load_dotenv()
-
 LLM_PROVIDER = os.getenv("LLM_PROVIDER", "openai").lower()
-
 embedding_model = None
 
 print(f"--- [Core] Initializing Embeddings with provider: {LLM_PROVIDER} ---")
 
 if LLM_PROVIDER == "azure":
-    required_vars = [
-        "AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_API_KEY",
-        "OPENAI_API_VERSION", "AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME"
-    ]
-    if not all(os.getenv(var) for var in required_vars):
-        raise ValueError("One or more Azure OpenAI environment variables for embeddings are not set.")
-
     embedding_model = AzureOpenAIEmbeddings(
         azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
         api_key=os.getenv("AZURE_OPENAI_API_KEY"),
         api_version=os.getenv("OPENAI_API_VERSION"),
         azure_deployment=os.getenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME"),
     )
-
 elif LLM_PROVIDER == "openai":
-    if not os.getenv("OPENAI_API_KEY"):
-        raise ValueError("OPENAI_API_KEY is not set for the 'openai' provider.")
-
     embedding_model = OpenAIEmbeddings(
         api_key=os.getenv("OPENAI_API_KEY"),
         model=os.getenv("OPENAI_EMBEDDING_MODEL_NAME", "text-embedding-3-small")
     )
-
 else:
-    raise ValueError(f"Unsupported LLM_PROVIDER: {LLM_PROVIDER}. Please use 'azure' or 'openai'.")
-
+    raise ValueError(f"Unsupported LLM_PROVIDER: {LLM_PROVIDER}.")
 
 client = chromadb.PersistentClient(path="./chroma_db")
-vector_store = client.get_or_create_collection(
-    name="documents",
-    metadata={"hnsw:space": "cosine"}
-)
+vector_store = client.get_or_create_collection(name="documents")