app.py

# References:

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

import gradio.utils, os, sys
import gradio as gr
from agents.crew import run_crew
from contextlib import contextmanager
from io import StringIO
from utils.utils import (
    DATASET_TYPE_GAIA,
    DATASET_TYPE_HLE,
    get_dataset,
    is_valid
)

# Configuration

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

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

# Console output capture

@contextmanager
def capture_output():
    old_stdout = sys.stdout
    old_stderr = sys.stderr

    try:
        sys.stdout = StringIO()
        sys.stderr = StringIO()
        yield sys.stdout, sys.stderr
    finally:
        sys.stdout = old_stdout
        sys.stderr = old_stderr

# 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:
        tuple: (answer, console_logs) - The answer to the question and captured console output
    """
    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 "", ""

    is_valid, err_msg = validate_input(question, openai_api_key, gemini_api_key, anthropic_api_key, file_name)
    
    if not is_valid:
        gr.Warning(f"Invalid input: {err_msg}")
        return "", ""
    
    if file_name:
        file_name = f"files/{file_name}"
    
    try:
        # API keys are provided thanks to sponsor credit.
        
        openai_key = openai_api_key if openai_api_key and openai_api_key != "*" else os.environ.get("OPENAI_API_KEY")
        gemini_key = gemini_api_key if gemini_api_key and gemini_api_key != "*" else os.environ.get("GEMINI_API_KEY")
        anthropic_key = anthropic_api_key if anthropic_api_key and anthropic_api_key != "*" else os.environ.get("ANTHROPIC_API_KEY")
        
        os.environ["OPENAI_API_KEY"] = openai_key
        os.environ["GEMINI_API_KEY"] = gemini_key
        os.environ["ANTHROPIC_API_KEY"] = anthropic_key

        with capture_output() as (stdout, stderr):
            answer = run_crew(question, file_name)
            
        stdout_logs = stdout.getvalue()
        stderr_logs = stderr.getvalue()
        console_logs = stdout_logs + (stderr_logs if stderr_logs else "")
        
        return answer, console_logs
    except Exception as e:
        error_msg = str(e)
        gr.Warning(error_msg)
        return "", f"Error: {error_msg}"

# 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"Prototype <strong>multi-agent AI platform</strong> with high autonomy, "
    f"including code generation & execution, browser automation, and multi-modal reasoning. "
    f"The system can solve multiple <a href='https://arxiv.org/pdf/2311.12983'>GAIA Benchmark</a> "
    f"Level 1, 2, 3 and even <a href='https://arxiv.org/pdf/2501.14249'>Humanity's Last Exam</a> "
    f"problems. To get started, select from the examples below. "
    f"Processing can take minutes depending on question complexity. "
    f"Console logs are provided below for transparency. "
    f"API keys are provided temporarily thanks to sponsor credit. "
    f"<a href='{BASE_URL}/README.md'>Documentation</a></p>"
)

DEFAULT_QUESTION = "How many public GitHub repos does the person who submitted the 'General AI Assistant' solution in MCP's 1st Birthday Hackathon have?"

DEFAULT_GROUND_TRUTH = "18"

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 *",
                        value=DEFAULT_QUESTION,
                        interactive=True,
                        max_length = 500,
                        lines=1,
                        max_lines=5
                    )
                with gr.Row():
                    ground_truth = gr.Textbox(
                        label="Ground Truth",
                        value=DEFAULT_GROUND_TRUTH,
                        interactive=True,
                        max_length = 500,
                        lines=1,
                        max_lines=2
                    )
                    file_name = gr.Textbox(
                        label="File Name",
                        interactive=True,
                        max_length = 150,
                        lines=1,
                        max_lines=2,
                        scale=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‑...",
                        value="*", # API keys are provided thanks to sponsor credit
                        interactive=True,
                        max_length = 150
                    )
                    gemini_api_key = gr.Textbox(
                        label="Gemini API Key *",
                        type="password",
                        value="*", # API keys are provided thanks to sponsor credit
                        interactive=True,
                        max_length = 150
                    )
                    anthropic_api_key = gr.Textbox(
                        label="Anthropic API Key *",
                        type="password",
                        placeholder="sk-ant-...",
                        value="*", # API keys are provided thanks to sponsor credit
                        interactive=True,
                        max_length = 150
                    )
                with gr.Row():
                    submit_btn = gr.Button("Submit", variant="primary")
            with gr.Column(scale=1):
                answer = gr.Textbox(
                    label="Answer",
                    interactive=False,
                    lines=1,
                    max_lines=5
                )

        with gr.Accordion("Console Logs", open=False):
            console_logs = gr.Textbox(
                label="Output",
                interactive=False,
                lines=25,
                max_lines=25
            )
        
        with gr.Row():
            clear_btn = gr.ClearButton(
                components=[question, ground_truth, file_name, file_link, answer, console_logs]
            )

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

        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, "", "", ""],
                    examples_per_page=5,
                    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, "", "", ""],
                    examples_per_page=5,
                    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, "", "", ""],
                    examples_per_page=5,
                    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, "", "", ""],
                    examples_per_page=5,
                    cache_examples=False
                )

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