Update agent.py

agent.py

@@ -26,7 +26,7 @@ import uuid
 import requests
 import json
 from langchain_core.documents import Document
-from langchain.vectorstores import FAISS
+from langchain_community.vectorstores import FAISS
 
 #from langchain.embeddings import BERTEmbeddings
 #from langchain_community.embeddings import HuggingFaceEmbeddings
@@ -64,7 +64,7 @@ from typing import Union
 from functools import reduce
 from youtube_transcript_api import YouTubeTranscriptApi
 from youtube_transcript_api._errors import TranscriptsDisabled, VideoUnavailable
-import faiss
+from langchain_faiss import FAISS
 
 from langchain.schema import Document
 
@@ -388,9 +388,9 @@ docs = [
 texts = [doc.page_content for doc in docs]
 
 # Initialize the embedding model
-embedding_model = HuggingFaceEmbeddings(model_name="bert-base-uncased")
+embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
 
-embeddings = [embedding_model.embed_query(text) for text in texts]
+docs = [Document(page_content=text, metadata={"task_id": item["task_id"]}) for item in data]
 
 # Create the FAISS index
 vector_store = FAISS.from_documents(docs, embedding_model)