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| #pip install streamlit langchain openai faiss-cpu tiktoken | |
| import streamlit as st | |
| from streamlit_chat import message | |
| 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 | |
| user_api_key = st.sidebar.text_input( | |
| label="#### Your OpenAI API key 👇", | |
| placeholder="Paste your openAI API key, sk-", | |
| type="password") | |
| uploaded_file = st.sidebar.file_uploader("upload", type="csv") | |
| if uploaded_file : | |
| with tempfile.NamedTemporaryFile(delete=False) as tmp_file: | |
| tmp_file.write(uploaded_file.getvalue()) | |
| tmp_file_path = tmp_file.name | |
| loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8") | |
| data = loader.load() | |
| embeddings = OpenAIEmbeddings() | |
| vectors = FAISS.from_documents(data, embeddings) | |
| chain = ConversationalRetrievalChain.from_llm(llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo', openai_api_key=user_api_key), | |
| retriever=vectors.as_retriever()) | |
| 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"] | |
| 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 " + uploaded_file.name + " 🤗"] | |
| 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") | |
| #streamlit run tuto_chatbot_csv.py |