Update auditqa/engine/vectorstore.py

auditqa/engine/vectorstore.py

@@ -6,40 +6,5 @@ embeddingmodel = "BAAI/bge-small-en-v1.5"
 load_dotenv()
 HF_Token = os.environ.get("HF_TOKEN")
 
-
-client_path = f"./vectorstore"
-collection_name = f"collection"
-
-if provider_retrieval_model == "HF":
-  qdrantClient = QdrantClient(path=client_path, prefer_grpc=True)
-
-  embeddings = HuggingFaceInferenceAPIEmbeddings(
-      api_key=HF_Token, model_name=embeddingmodel
-  )
-
-  dim = 1024
-
-elif provider_retrieval_model == "OAI":
-
-  qdrantClient = QdrantClient(path=client_path, prefer_grpc=True)
-
-  embeddings = OpenAIEmbeddings(
-          model="text-embedding-ada-002",
-          openai_api_key=os.getenv("OPENAI_API_KEY"),
-  )
-
-  dim = 1536
-
-
-qdrantClient.create_collection(
-    collection_name=collection_name,
-    vectors_config=VectorParams(size=dim, distance=Distance.COSINE),
-)
-
-vectorstore = Qdrant(
-    client=qdrantClient,
-    collection_name=collection_name,
-    embeddings=embeddings,
-)
-
-vectorstore.add_documents(docs_samp)
+def token():
+    print(HF_Token)