Duplicate from FyVa/chat

.gitattributes

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README.md

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+---
+title: Chat
+emoji: 🔥
+colorFrom: green
+colorTo: blue
+sdk: streamlit
+sdk_version: 1.19.0
+app_file: app.py
+pinned: false
+license: bsd
+duplicated_from: FyVa/chat
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+"""Python file to serve as the frontend"""
+import streamlit as st
+from streamlit_chat import message
+
+from langchain.chains import ConversationChain
+from langchain.llms import OpenAI
+import os
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import Pinecone
+from langchain.document_loaders import TextLoader
+import pinecone 
+from langchain.document_loaders import TextLoader
+import streamlit as st
+# import pandas as pd
+from constants import INDEX_NAME, NAMESPACE,PINECONE_ENV
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
+from langchain.llms import OpenAI
+from langchain.chains.question_answering import load_qa_chain
+
+
+
+PINECONE_API_KEY= st.secrets["PINECONE_API_KEY"]
+OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
+
+os.environ['OPENAI_API_KEY'] =OPENAI_API_KEY
+
+# initialize pinecone
+pinecone.init(
+    api_key=PINECONE_API_KEY,  # find at app.pinecone.io
+    environment=PINECONE_ENV  # next to api key in console
+)
+
+embeddings = OpenAIEmbeddings()
+
+llm = OpenAI(temperature=0)
+
+@st.cache_resource
+def load_pinecone_existing_index(question):
+    pass
+    searchIndex = Pinecone.from_existing_index(index_name=INDEX_NAME,embedding = embeddings, namespace=NAMESPACE)
+    docsReturned = searchIndex.similarity_search(question, k=2)
+    return docsReturned
+
+@st.cache_resource
+def get_answer(question):
+    chain = load_qa_chain(llm, chain_type="stuff")
+    docs=load_pinecone_existing_index(question)
+    answer = chain.run(input_documents=docs, question=question)
+    return answer
+# chain = load_qa_chain(llm, chain_type="stuff")
+# answer = chain.run(input_documents=docs, question=QUERY)
+
+# From here down is all the StreamLit UI.
+st.set_page_config(page_title="FyVa", page_icon=":robot:")
+st.header("FyVa")
+
+if "generated" not in st.session_state:
+    st.session_state["generated"] = []
+
+if "past" not in st.session_state:
+    st.session_state["past"] = []
+
+
+def get_text():
+    input_text = st.text_input("You: ", "Hi,how are you.", key="input")
+    return input_text
+
+
+user_input = get_text()
+
+if user_input:
+    # output = chain.run(input=user_input)
+    output = get_answer(user_input)
+
+    st.session_state.past.append(user_input)
+    st.session_state.generated.append(output)
+
+if st.session_state["generated"]:
+
+    for i in range(len(st.session_state["generated"]) - 1, -1, -1):
+        message(st.session_state["generated"][i], key=str(i))
+        message(st.session_state["past"][i], is_user=True, key=str(i) + "_user")

constants.py

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+INDEX_NAME = "arunachala"
+NAMESPACE = "medine"
+PINECONE_ENV = "asia-northeast1-gcp"
+QUERY = 'What is the business model?'

requirements.txt

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+langchain==0.0.157
+pinecone_client==2.2.1
+streamlit==1.22.0
+streamlit_chat==0.0.2.2
+openai==0.27.6