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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.Textbox( | |
| 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 | |
| ) | |