gaia / app.py
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Update app.py
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# 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
)
# 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 "", ""
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,
lines=1,
max_lines=1
)
with gr.Row():
ground_truth = gr.Textbox(
label="Ground Truth",
value=DEFAULT_GROUND_TRUTH,
interactive=True,
lines=1,
max_lines=1
)
file_name = gr.Textbox(
label="File Name",
interactive=True,
lines=1,
max_lines=1,
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
)
gemini_api_key = gr.Textbox(
label="Gemini API Key *",
type="password",
value="*", # API keys are provided thanks to sponsor credit
interactive=True
)
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
)
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=1
)
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)