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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
)
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