Duplicate from enadewan/ASK_FREDDY_BY_CL

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README.md

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+---
+title: ASK FREDDY
+emoji: 🚀
+colorFrom: red
+colorTo: gray
+sdk: gradio
+sdk_version: 3.38.0
+app_file: app.py
+pinned: false
+duplicated_from: enadewan/ASK_FREDDY_BY_CL
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+
+
+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
+from InstructorEmbedding import INSTRUCTOR
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+instructor_embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
+HUGGINGFACEHUB_API_TOKEN='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'
+new_vectorstore = FAISS.load_local("./faiss_docs_xl_index", instructor_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)

faiss_docs_index/index.pkl

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+oid sha256:f30d6613a8e831374d304c440a3f7b4f78fd20f27ff208b6faa3ac9d802ea055
+size 205087

faiss_docs_xl_index/index.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b64f6df6d35f3118be58ab75c60bf39487885c9cefa752e21d3216bb03c599bc
+size 205087

requirements.txt

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+langchain
+pandas
+faiss-cpu
+huggingface_hub
+sentence-transformers 
+InstructorEmbedding
+gradio