import gradio as gr
from utils.generator import generate

# ---------------------------------------------------------------------
# Gradio Interface with MCP support
# ---------------------------------------------------------------------


ui = gr.Interface(
    fn=generate,
    inputs=[
        gr.Textbox(
            label="Query", 
            lines=2, 
            placeholder="Enter query here",
            info="The query to search for in the vector database"
        ),
        gr.Textbox(
            label="Context", 
            lines=8, 
            placeholder="Paste relevant context here",
            info="Provide the context/documents to use for answering. The API expects a list of dictionaries, but the UI should except anything"
        ),
    ],
    outputs=[gr.Text(label="Generated Answer", lines=6, show_copy_button=True)],
            title="ChatFed Generation Module",
            description="Ask questions based on provided context. Intended for use in RAG pipelines as an MCP server with other ChatFed modules (i.e. context supplied by semantic retriever service).",
            api_name="generate"
)

# Launch with MCP server enabled
if __name__ == "__main__":
    ui.launch(
        server_name="0.0.0.0",
        server_port=7860,
        #mcp_server=True,
        show_error=True
    )