app.py

import os
import gradio as gr
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferMemory


import getpass

token=os.environ.get("TOKEN")
os.environ["GOOGLE_API_KEY"] = token

template = """You are a helpful assistant to answer all user queries.
{chat_history}
User: {user_message}
Chatbot:"""

prompt = PromptTemplate(
    input_variables=["chat_history", "user_message"], template=template
)

memory = ConversationBufferMemory(memory_key="chat_history")

llm_chain = LLMChain(
    llm=ChatGoogleGenerativeAI(model="gemini-pro"),
    prompt=prompt,
    verbose=True,
    memory=memory,
)

def get_text_response(user_message,history):
    response = llm_chain.predict(user_message = user_message)
    print(response)
    return "non abonné "

demo = gr.ChatInterface(get_text_response)

demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.