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Runtime error
| from langchain.memory import ConversationBufferMemory | |
| from langchain.vectorstores.faiss import FAISS | |
| import os | |
| from langchain.memory import ConversationBufferMemory | |
| from langchain.chains import ConversationalRetrievalChain | |
| import pandas as pd | |
| import numpy as np | |
| from langchain.embeddings import HuggingFaceEmbeddings | |
| from langchain import HuggingFaceHub | |
| from typing import Any, Dict, List | |
| embeddings = HuggingFaceEmbeddings() | |
| HUGGINGFACEHUB_API_TOKEN=HUGGINGFACEHUB_API_TOKEN | |
| new_vectorstore = FAISS.load_local("./faiss_docs_index", embeddings) | |
| llm = HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs={"temperature": 0.1, "max_length": 512},huggingfacehub_api_token= "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") | |
| # Front end web app | |
| import gradio as gr | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot() | |
| msg = gr.Textbox("Ask Freddy") | |
| clear = gr.Button("Clear") | |
| chat_history = [] | |
| def user(user_message, history): | |
| # Get response from QA chain | |
| memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True, output_key='answer') | |
| qa=ConversationalRetrievalChain.from_llm( llm=llm ,retriever=new_vectorstore.as_retriever(search_kwargs={"k":1, "include_metadata": True}),chain_type="refine",memory=memory,return_source_documents=True) | |
| result = qa({"question": user_message,"chat_history": chat_history}) | |
| myresponse=result['answer'] | |
| # Append user message and response to chat history | |
| chat_history.append((user_message, myresponse)) | |
| return gr.update(value=""), chat_history | |
| msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False) | |
| clear.click(lambda: None, None, chatbot, queue=False) | |
| if __name__ == "__main__": | |
| demo.launch(debug=True,share=False) |