rag-chatbot/chat1.py at main · sDaCoder/rag-chatbot · GitHub

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import os
from dotenv import load_dotenv
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.messages import SystemMessage, HumanMessage, AIMessage
import streamlit as st
import time
from designClass import Design
# from rich.console import Console
# from rich.markdown import Markdown

# console = Console()

# load_dotenv()
# GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
# model = ChatGoogleGenerativeAI(
#     model="gemini-2.0-flash",
#     google_api_key=GEMINI_API_KEY
# )

# def stream_data(text):
#     for word in text.split(" "):
#         yield word + " "
#         time.sleep(0.05)

# st.set_page_config(page_title="Kissan AI | Your virtual farmer", page_icon="🌾")

# st.markdown("---")
# st.markdown("<h1 style=''>Kissan AI 🌾</h1>", unsafe_allow_html=True)
# st.caption("Ask me anything about your farming and agriculture.")
# st.markdown("---")
# with st.sidebar:
#     st.image("https://images.unsplash.com/photo-1589923188900-85dae523342b?q=80&w=2670&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D")
#     st.title("Kissan AI")
#     st.caption('''
#     Kissan AI aims to be a virtual farmer and agricultural expert who predicts the favourable crops that can be grown in a particular region and a particular period.
#     ''', unsafe_allow_html=False)

# if "messages" not in  st.session_state:
#     st.session_state.messages = [
#         SystemMessage("""
#             Think yourself as a virtual farmer and an agricultural expert who predict the favourable crops that can be grown in a particular region and a particular period. If anyone asks your name, tell your name as 'Kissan AI', Now answer the following question using only the context provided.
#         """)
#     ]

# if 'chat_history' not in st.session_state:
#     st.session_state.chat_history = [{
#         "role": "assistant",
#         "content": "Hi, I'm Kissan AI. How can I help you today?"
#     }]

# for chat in st.session_state.chat_history:
#     a = "🧑🏼‍🌾" if chat["role"] == "assistant" else "🧑🏼"
#     with st.chat_message(chat["role"], avatar=a):
#         st.write(chat["content"])

# query = st.chat_input("Ask me anything about agriculture and farming...")
# if query:
#     with st.chat_message("human", avatar="🧑🏼"):
#         st.write(query)
#     st.session_state.chat_history.append({"role": "human", "content": query})
#     st.session_state.messages.append(HumanMessage(content=query))

#     with st.status("Generating response..."):
#         response = model.invoke(st.session_state.messages)
#         st.session_state.messages.append(AIMessage(content=response.content))
#         st.session_state.chat_history.append({"role": "assistant", "content": response.content})

#     with st.chat_message("assistant", avatar="🧑🏼‍🌾"):
#         st.write_stream(stream_data(response.content))

D = Design()
D.chat()

# while True:
#     query = input("You: ")
#     if query.lower() in ['exit', 'quit']:
#         break
#     messages.append(HumanMessage(content=query))
#     print()

#     response = model.invoke(messages)
#     messages.append(AIMessage(content=response.content))
#     console.print(Markdown(response.content))