app.py

import gradio as gr
import os
from langchain_groq import ChatGroq  # Using Groq's API
from langchain.memory import ConversationBufferMemory
from langchain.schema import SystemMessage, HumanMessage, AIMessage
from langchain.agents import initialize_agent, AgentType
from langchain.tools import Tool

# Set API Key for Groq
API_KEY = os.getenv("API_KEY")  # Ensure API Key is set in the environment

# Initialize the LLM (Groq's Mixtral)
llm = ChatGroq(
    groq_api_key=API_KEY,
    model_name="mixtral-8x7b-32768",
    temperature=0.7,
    max_tokens=512,
)

# Memory for conversation history
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)

# Define useful tools
def search_tool(query: str) -> str:
    """A simple search function (can be connected to real APIs)."""
    return f"Searching for: {query}... [Sample Response]"

tools = [
    Tool(
        name="Search Tool",
        func=search_tool,
        description="Searches for information based on user queries."
    )
]

# Initialize the agent
agent = initialize_agent(
    tools=tools,
    llm=llm,
    agent=AgentType.CONVERSATIONAL_REACT_DESCRIPTION,
    verbose=True,
    memory=memory,
)

# Define response function
def respond(message, history, system_message, max_tokens, temperature, top_p):
    memory.chat_memory.add_message(SystemMessage(content=system_message))

    for user_input, bot_response in history:
        if user_input:
            memory.chat_memory.add_message(HumanMessage(content=user_input))
        if bot_response:
            memory.chat_memory.add_message(AIMessage(content=bot_response))

    memory.chat_memory.add_message(HumanMessage(content=message))

    response = agent.run(message)

    return response


# Gradio Interface
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a helpful Travel AI assistant.Your name is Travelo", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
    ],
)

if __name__ == "__main__":
    demo.launch()