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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()
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