gui.py

# Simple Gradio GUI
# Ramy-ibrahim-Ahmed
import gradio as gr
from langchain_core.messages import HumanMessage
from src.agent import GRAPH

RECURSION_LIMIT = 15


async def run_agent_interaction(query: str) -> str:
    if not query:
        return "Please enter a research query."

    config = {"recursion_limit": RECURSION_LIMIT}
    try:
        final_state = await GRAPH.ainvoke(
            {"messages": HumanMessage(content=query)}, config=config
        )
        messages = final_state.get("messages", [])
        last_message = messages[-1] if messages else None
        report_text = final_state.get("report_text")

        if report_text:
            return f"**Report Generated:**\n\n---\n\n{report_text}"
        elif last_message:
            return f"**Agent Finished:**\n\n---\n\n[{last_message.name}]\n{last_message.content}"
        else:
            return "**Agent Finished:**\n\n---\n\nAgent finished, but the final state is unclear."

    except Exception as e:
        return (
            f"**Error:**\n\n---\n\nAn error occurred during agent execution: {str(e)}"
        )


with gr.Blocks(theme=gr.themes.Soft(), title="Research Bot") as iface:
    gr.Markdown("# 🔍Electronic Market Research Bot")
    gr.Markdown("Enter your query below to generate an electronics research report.")

    with gr.Row():
        query_input = gr.Textbox(
            label="Research Query",
            placeholder="e.g., Compare the latest iPhone Pro Max vs Samsung Galaxy Ultra camera...",
            lines=3,
            show_copy_button=True,
        )

    run_button = gr.Button("Run Research", variant="primary")

    with gr.Row():
        output_display = gr.Markdown(label="Agent Response")

    run_button.click(
        fn=run_agent_interaction,
        inputs=[query_input],
        outputs=[output_display],
    )

    gr.Markdown("---")
    gr.Markdown(
        "Note: Report generation can take some time depending on the complexity."
    )

iface.launch(share=False)