app.py

from dataclasses import dataclass
from typing import Literal
import streamlit as st
import os
# from llamaapi import LlamaAPI
# from langchain_experimental.llms import ChatLlamaAPI
from langchain.embeddings import HuggingFaceEmbeddings
from pinecone import Pinecone

from langchain.prompts import PromptTemplate
from langchain.chains import RetrievalQA
import streamlit.components.v1 as components
from langchain_groq import ChatGroq
from langchain.chains import ConversationalRetrievalChain
from langchain.memory import ChatMessageHistory, ConversationBufferMemory
import time
import os
os.environ['PINECONE_API_KEY'] = "fa944c7c-5775-4a96-8704-e04f7a86614e"
pc = Pinecone()

HUGGINGFACEHUB_API_TOKEN = st.secrets['HUGGINGFACEHUB_API_TOKEN']
from langchain.vectorstores import Pinecone
@dataclass
class Message:
 """Class for keeping track of a chat message."""
 origin: Literal["👤 Human", "👨🏻‍⚖️ Ai"]
 message: str


def download_hugging_face_embeddings():
 embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
 return embeddings


def initialize_session_state():
 if "history" not in st.session_state:
 st.session_state.history = []
 if "conversation" not in st.session_state:
 # llama = LlamaAPI(st.secrets["LlamaAPI"])
 # model = ChatLlamaAPI(client=llama)
 chat = ChatGroq(temperature=0.5, groq_api_key=st.secrets["Groq_api"], model_name="mixtral-8x7b-32768")

 embeddings = download_hugging_face_embeddings()

 
 index_name = "medical-advisor"

 if index_name in pc.list_indexes().names():
 print("index already exists" , index_name)
 index= pc.Index(index_name) #your index which is already existing and is ready to use
 print(index.describe_index_stats())
 # put in the name of your pinecone index here

 docsearch = Pinecone.from_existing_index(index_name, embeddings)

 prompt_template = """
 You are a trained bot to guide people about their medical concerns acting as Doctor. You will answer user's query with your knowledge and the context provided. 
 
 If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.

 Provide very detailed answer as Doctor.
 
 Use the following pieces of context to answer the users question.
 Context: {context}
 Question: {question}
 Only return the helpful answer below and nothing else.
 Helpful answer:
 """

 PROMPT = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
 
 #chain_type_kwargs = {"prompt": PROMPT}
 message_history = ChatMessageHistory()
 memory = ConversationBufferMemory(
 memory_key="chat_history",
 output_key="answer",
 chat_memory=message_history,
 return_messages=True,
 )
 retrieval_chain = ConversationalRetrievalChain.from_llm(llm=chat,
 chain_type="stuff",
 retriever=docsearch.as_retriever(
 search_kwargs={'k': 3}),
 return_source_documents=True,
 combine_docs_chain_kwargs={"prompt": PROMPT},
 memory= memory
 )

 st.session_state.conversation = retrieval_chain


def on_click_callback():
 human_prompt = st.session_state.human_prompt
 st.session_state.human_prompt=""
 response = st.session_state.conversation(
 human_prompt
 )
 llm_response = response['answer']
 st.session_state.history.append(
 Message("👤 Human", human_prompt)
 )
 st.session_state.history.append(
 Message("👨🏻‍⚖️ Ai", llm_response)
 )


initialize_session_state()

st.title("Medical Advisor Chatbot 🇮🇳")

# st.markdown(
# """
# 👋 **Namaste! Welcome to LegalEase Advisor!**
# I'm here to assist you with your legal queries within the framework of Indian law. Whether you're navigating through specific legal issues or seeking general advice, I'm here to help.
 
# 📚 **How I Can Assist:**
 
# - Answer questions on various aspects of Indian law.
# - Guide you through legal processes relevant to India.
# - Provide information on your rights and responsibilities as per Indian legal standards.
 
# ⚖️ **Disclaimer:**
 
# While I can provide general information, it's essential to consult with a qualified Indian attorney for advice tailored to your specific situation.
 
# 🤖 **Getting Started:**
 
# Feel free to ask any legal question related to Indian law, using keywords like "property rights," "labor laws," or "family law." I'm here to assist you!
# Let's get started! How can I assist you today?
# """
# )

chat_placeholder = st.container()
prompt_placeholder = st.form("chat-form")

with chat_placeholder:
 for chat in st.session_state.history:
 st.markdown(f"{chat.origin} : {chat.message}")

with prompt_placeholder:
 st.markdown("**Chat**")
 cols = st.columns((6, 1))
 cols[0].text_input(
 "Chat",
 label_visibility="collapsed",
 key="human_prompt",
 )
 cols[1].form_submit_button(
 "Submit",
 type="primary",
 on_click=on_click_callback,
 )