#this is one is using FALCON-7B from langchain import HuggingFaceHub, LLMChain, PromptTemplate from langchain.memory import ConversationBufferWindowMemory from langchain.embeddings.openai import OpenAIEmbeddings from langchain.chat_models import ChatOpenAI from langchain.chains import ConversationalRetrievalChain from langchain.document_loaders.csv_loader import CSVLoader from langchain.vectorstores import FAISS import tempfile from streamlit_chat import message import streamlit as st import os import sys import pandas as pd def conversational_chat(query): result = chain({"question": query, "chat_history": st.session_state['history']}) st.session_state['history'].append((query, result["answer"])) return result["answer"] user_api_key = st.sidebar.text_input( label="#### Your HuggingFace API key 👇", placeholder="Paste your HuggingGace API key, sk-", type="password") if user_api_key is not None and user_api_key.strip() != "": huggingfacehub_api_token = os.environ[user_api_key] #setting up the LLM repo_id = "tiiuae/falcon-7b-instruct" chain = ConversationalRetrievalChain.from_llm( llm = HuggingFaceHub(huggingfacehub_api_token=huggingfacehub_api_token, repo_id=repo_id, model_kwargs={"temperature":0.6, "max_new_tokens":2000})) if 'history' not in st.session_state: st.session_state['history'] = [] if 'generated' not in st.session_state: st.session_state['generated'] = ["Hello ! Ask me anything about " + " 🤗"] if 'past' not in st.session_state: st.session_state['past'] = ["Hey ! 👋"] #container for the chat history response_container = st.container() #container for the user's text input container = st.container() with container: with st.form(key='my_form', clear_on_submit=True): user_input = st.text_input("Query:", placeholder="Talk about your csv data here (:", key='input') submit_button = st.form_submit_button(label='Send') if submit_button and user_input: output = conversational_chat(user_input) st.session_state['past'].append(user_input) st.session_state['generated'].append(output) if st.session_state['generated']: with response_container: for i in range(len(st.session_state['generated'])): message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile") message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs") else: st.text("Please enter your OpenAI API key above.")