app.py

# References:

# https://www.gradio.app/guides/quickstart

import gradio.utils, os
import gradio as gr
from agents.crew import run_crew
from utils.utils import (
    DATASET_TYPE_GAIA,
    DATASET_TYPE_HLE,
    get_dataset
)

# Configuration

SPACE_ID = os.environ.get("SPACE_ID")

BASE_URL = f"https://huggingface.co/spaces/{SPACE_ID}/blob/main"

# MCP server functions

def ask(question, openai_api_key, gemini_api_key, anthropic_api_key, file_name = ""):
    """
    Ask General AI Assistant a question to answer.

    Args:
        question (str): The question to answer
        openai_api_key (str): OpenAI API key (always used)
        gemini_api_key (str): Gemini API key (always used)
        anthropic_api_key (str): Anthropic API key (only used by Stagehand tool)
        file_name (str): Optional file name

    Returns:
        str: The answer to the question
    """
    if not question:
        gr.Warning("Question is required.")
        return ""

    if not openai_api_key:
        gr.Warning("OpenAI API Key is required.")
        return ""
    
    if not gemini_api_key:
        gr.Warning("Gemini API Key is required.")
        return ""

    if not anthropic_api_key:
        gr.Warning("Anthropic API Key is required.")
        return ""
        
    if file_name:
        file_name = f"files/{file_name}"
    
    try:
        os.environ["OPENAI_API_KEY"] = openai_api_key
        os.environ["GEMINI_API_KEY"] = gemini_api_key
        os.environ["MODEL_API_KEY"] = anthropic_api_key
        
        return run_crew(question, file_name)
    except Exception as e:
        gr.Warning(str(e))
        return ""
    finally:
        for key in ["OPENAI_API_KEY", "GEMINI_API_KEY", "MODEL_API_KEY"]:
            os.environ.pop(key, None)

# Helper functions

def update_file_link(file_name):
    if file_name:
        return f"<a href='{BASE_URL}/files/{file_name}' target='_blank'>Open File</a>"
    
    return ""

def watchfn(*args, **kwargs):
    pass

gradio.utils.watchfn_spaces = watchfn

# Graphical user interface

DESCRIPTION = (
    f"<strong>Multi-agent, multi-modal, multi-model AI platform</strong> with high agency, "
    f"including code generation / execution, browser automation & multi-modal reasoning. "
    f"The system can solve <a href='https://arxiv.org/pdf/2311.12983'>GAIA Benchmark</a> "
    f"Level 1, 2, 3 and <a href='https://arxiv.org/pdf/2501.14249'>Humanity's Last Exam</a> "
    f"problems. To get started with the <strong>GUI</strong>, select from the examples below. "
    f"To use via <strong>API</strong> or <strong>MCP</strong>, see the link below. Bring your own API keys. "
    f"<a href='{BASE_URL}/README.md'>Documentation</a></p>"
)

DEFAULT_QUESTION = "In MCP's 1st Birthday Hackathon, hosted by Anthropic and Gradio, what percentage of participants submitted a solution so far?"

CSS_FULL_WIDTH = """
<style>
html,
body,
main,
.gradio-app {
    width: 100% !important;
    max-width: 100% !important;
    margin: 0 !important;
    padding: 0 !important;
    overflow-x: hidden !important;
}

.full-width-app {
    width: 100% !important;
    max-width: 100% !important;
    margin: 0 !important;
    padding: 0 !important;
}

.content-padding {
    padding: 0 1.5rem 0;
}
</style>
"""

with gr.Blocks(elem_classes=["full-width-app"]) as gaia:
    gr.HTML(CSS_FULL_WIDTH)

    with gr.Column(elem_classes=["content-padding"]):
        gr.Markdown("## General AI Assistant")

        gr.Markdown(DESCRIPTION)
        
        with gr.Row():
            with gr.Column(scale=3):
                with gr.Row():
                    question = gr.Textbox(
                        label="Question *",
                        placeholder=DEFAULT_QUESTION,
                        interactive=True,
                        lines=2,
                        max_lines=5
                    )
                with gr.Row():
                    ground_truth = gr.Textbox(
                        label="Ground Truth",
                        interactive=True,
                        lines=1,
                        max_lines=2
                    )
                    file_name = gr.Textbox(
                        label="File Name",
                        interactive=True,
                        scale=2,
                        lines=1,
                        max_lines=2
                    )
                    file_link = gr.HTML(
                        label="File Link",
                        value=""
                    )
                with gr.Row():
                    openai_api_key = gr.Textbox(
                        label="OpenAI API Key *",
                        type="password",
                        placeholder="sk‑...",
                        interactive=True
                    )
                    gemini_api_key = gr.Textbox(
                        label="Gemini API Key *",
                        type="password",
                        interactive=True
                    )
                    anthropic_api_key = gr.Textbox(
                        label="Anthropic API Key *",
                        type="password",
                        placeholder="sk-ant-...",
                        interactive=True
                    )
                with gr.Row():
                    clear_btn = gr.ClearButton(
                        components=[question, ground_truth, file_name, file_link]
                    )
                    submit_btn = gr.Button("Submit", variant="primary")
            with gr.Column(scale=1):
                answer = gr.Textbox(
                    label="Answer",
                    interactive=False,
                    lines=2,
                    max_lines=5
                )

        submit_btn.click(
            fn=ask,
            inputs=[question, openai_api_key, gemini_api_key, anthropic_api_key, file_name],
            outputs=answer
        )

        file_name.change(
            fn=update_file_link,
            inputs=[file_name],
            outputs=[file_link]
        )

        with gr.Tabs():
            with gr.TabItem("GAIA Benchmark Level 1"):
                gr.Examples(
                    examples=get_dataset(DATASET_TYPE_GAIA, 1),
                    inputs=[question, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
                    examples_per_page=3,
                    cache_examples=False
                )

            with gr.TabItem("GAIA Benchmark Level 2"):
                gr.Examples(
                    examples=get_dataset(DATASET_TYPE_GAIA, 2),
                    inputs=[question, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
                    examples_per_page=3,
                    cache_examples=False
                )

            with gr.TabItem("GAIA Benchmark Level 3"):
                gr.Examples(
                    examples=get_dataset(DATASET_TYPE_GAIA, 3),
                    inputs=[question, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
                    examples_per_page=3,
                    cache_examples=False
                )

            with gr.TabItem("Humanity's Last Exam"):
                gr.Examples(
                    examples=get_dataset(DATASET_TYPE_HLE, 0),
                    inputs=[question, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
                    examples_per_page=3,
                    cache_examples=False
                )

gaia.launch(mcp_server=True, ssr_mode=False)