wt002 commited on
Commit
818a170
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1 Parent(s): eef5b16

Update agent.py

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Files changed (1) hide show
  1. agent.py +12 -6
agent.py CHANGED
@@ -59,7 +59,7 @@ from youtube_transcript_api._errors import TranscriptsDisabled, VideoUnavailable
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  from langchain.schema import Document
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  from langchain_community.vectorstores import FAISS
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- from langchain_community.embeddings import HuggingFaceEmbeddings
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  from langchain.tools.retriever import create_retriever_tool
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  #from langchain_community.tools import create_retriever_tool
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  from typing import TypedDict, Annotated, List
@@ -429,18 +429,24 @@ embedding_model = HuggingFaceEmbeddings(
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  # -----------------------------
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  # Create FAISS index and save it
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  # -----------------------------
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- vector_store = FAISS.from_documents(
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- documents=docs,
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- embedding=embedding_model
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- )
 
 
 
 
 
 
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- vector_store.save_local("/home/wendy/Downloads/faiss_index")
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  # -----------------------------
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  # Load FAISS index properly
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  # -----------------------------
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  loaded_store = FAISS.load_local("/home/wendy/Downloads/faiss_index", embedding_model)
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  # -----------------------------
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  # Create LangChain Retriever Tool
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  # -----------------------------
 
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  from langchain.schema import Document
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  from langchain_community.vectorstores import FAISS
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+ from langchain_huggingface import HuggingFaceEmbeddings
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  from langchain.tools.retriever import create_retriever_tool
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  #from langchain_community.tools import create_retriever_tool
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  from typing import TypedDict, Annotated, List
 
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  # -----------------------------
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  # Create FAISS index and save it
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  # -----------------------------
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+ try:
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+ vector_store = FAISS.load_local(
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+ "/home/wendy/Downloads/faiss_index/faiss_index",
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+ embedding_model,
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+ allow_dangerous_deserialization=True
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+ )
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+ except Exception as e:
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+ print(f"Error loading index: {str(e)}")
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+ # Fallback to rebuilding index
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+ vector_store = FAISS.from_documents(docs, embedding_model)
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  # -----------------------------
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  # Load FAISS index properly
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  # -----------------------------
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  loaded_store = FAISS.load_local("/home/wendy/Downloads/faiss_index", embedding_model)
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+
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  # -----------------------------
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  # Create LangChain Retriever Tool
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  # -----------------------------