app.py

import gradio as gr
from langchain_core.messages import HumanMessage
from langchain.chat_models import init_chat_model

model = init_chat_model("gemini-2.0-flash", model_provider="google_genai")


def respond(
    user_input: str,
    messages: list[dict],
    system_message: str,
    max_new_tokens: int,
    temperature: float,
    top_p: float,
) -> str:
    """
    Respond to user input using the model.
    """
    response = model.invoke(
        messages + [HumanMessage(content=user_input)],
    )
    return response.content

"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
    fn=respond,
    type="messages",
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", 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()