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import asyncio |
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import gradio as gr |
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import nest_asyncio |
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from huggingface_hub import login |
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from src.agent_hackathon.consts import PROJECT_ROOT_DIR |
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from src.agent_hackathon.logger import get_logger |
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from src.agent_hackathon.multiagent import MultiAgentWorkflow |
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nest_asyncio.apply() |
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logger = get_logger(log_name="multiagent", log_dir=PROJECT_ROOT_DIR / "logs") |
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PRIMARY_HEADING = """# ML Topics Deep Research""" |
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SECONDARY_HEADING = """### This multi agent framework queries a DB containing arxiv ML research papers from Jan 2020 - Jun 6th 2025 for select categories, and finds events/conferences related to the user's query. |
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For more details on the filtered arxiv ds refer [here](https://huggingface.co/datasets/Shamik/arxiv_cs_2020_07_2025) |
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""" |
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workflow = MultiAgentWorkflow() |
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_login_done = False |
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def run( |
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query: str, api_key: str, chat_history: list[dict[str, str | None]] |
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) -> tuple[str,list[dict[str, str | None]]] | None: |
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global _login_done |
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if not api_key or not api_key.startswith("hf"): |
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raise ValueError("Incorrect HuggingFace Inference API Key") |
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if not _login_done: |
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login(token=api_key) |
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_login_done = True |
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try: |
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result = asyncio.run(workflow.run(user_query=query)) |
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chat_history.append({"role": "user", "content": query}) |
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chat_history.append({"role": "assistant", "content": result}) |
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return "", chat_history |
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except Exception as err: |
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logger.error(f"Error during workflow execution: {err}") |
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return None |
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with gr.Blocks(fill_height=True) as demo: |
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gr.Markdown(value=PRIMARY_HEADING) |
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gr.Markdown(value=SECONDARY_HEADING) |
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gr.Markdown( |
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value="""<span style="color:red"> Please use a 🤗 Inference API Key </span>""" |
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) |
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api_key = gr.Textbox( |
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placeholder="Enter your HuggingFace Inference API KEY HERE", |
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label="🤗 Inference API Key", |
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show_label=True, |
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type="password", |
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) |
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chatbot = gr.Chatbot( |
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type="messages", label="DeepResearch", show_label=True, height=500, |
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show_copy_all_button=True, show_copy_button=True |
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) |
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msg = gr.Textbox( |
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placeholder="Type your message here and press enter...", |
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show_label=True, |
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label="Input", |
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submit_btn=True, |
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stop_btn=True, |
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) |
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clear = gr.ClearButton(components=[msg, chatbot]) |
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msg.submit(fn=run, inputs=[msg, api_key, chatbot], outputs=[msg, chatbot]) |
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demo.queue(max_size=1).launch(share=False) |
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