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import os
import gradio as gr
import requests
import inspect
import pandas as pd
# Import GAIA system - Enhanced with SmoLAgents
try:
from smolagents_bridge import SmoLAgentsEnhancedAgent as BasicAgent
print("โ
Using SmoLAgents-enhanced GAIA system")
except ImportError:
# Fallback to original system
from gaia_system import BasicAgent
print("โ ๏ธ SmoLAgents not available, using fallback system")
from gaia_system import MultiModelGAIASystem
# (Keep Constants as is)
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
def run_and_submit_all( profile: gr.OAuthProfile | None):
"""
Fetches all questions, runs the Enhanced SmoLAgents Agent on them, submits all answers,
and displays the results.
"""
# --- Determine HF Space Runtime URL and Repo URL ---
space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
if profile:
username= f"{profile.username}"
print(f"User logged in: {username}")
else:
print("User not logged in.")
return "Please Login to Hugging Face with the button.", None
api_url = DEFAULT_API_URL
questions_url = f"{api_url}/questions"
submit_url = f"{api_url}/submit"
# --- Get Questions ---
print("๐ Fetching GAIA questions...")
try:
response = requests.get(questions_url)
if response.status_code == 200:
questions = response.json()
print(f"โ
Fetched {len(questions)} questions")
else:
return f"Failed to fetch questions. Status code: {response.status_code}", None
except Exception as e:
return f"Error fetching questions: {str(e)}", None
# --- Initialize Enhanced SmoLAgents Agent ---
print("๐ Initializing SmoLAgents-Enhanced GAIA Agent...")
try:
agent = BasicAgent() # Uses HF_TOKEN and OPENAI_API_KEY from environment
print("โ
Enhanced agent initialized successfully")
except Exception as e:
return f"Error initializing enhanced agent: {str(e)}", None
# --- Process Questions ---
print(f"๐ง Processing {len(questions)} GAIA questions with enhanced agent...")
answers = []
for i, question_data in enumerate(questions, 1):
question = question_data["Question"]
task_id = question_data["task_id"]
print(f"\n๐ Question {i}/{len(questions)} (Task: {task_id})")
print(f"Q: {question[:100]}...")
try:
# Use enhanced SmoLAgents system
raw_answer = agent.query(question)
# Clean for GAIA API submission
clean_answer = agent.clean_for_api_submission(raw_answer)
print(f"โ
Enhanced Agent Answer: {clean_answer}")
answers.append({
"task_id": task_id,
"submitted_answer": clean_answer
})
except Exception as e:
error_msg = f"Error processing question {task_id}: {str(e)}"
print(f"โ {error_msg}")
answers.append({
"task_id": task_id,
"submitted_answer": "Error: Unable to process"
})
# --- Submit Answers ---
print(f"\n๐ Submitting {len(answers)} answers to GAIA API...")
# Determine the agent code URL
if space_id:
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
else:
agent_code = "https://huggingface.co/spaces/schoolkithub/multi-agent-gaia-system/tree/main"
submission_data = {
"username": username,
"agent_code": agent_code,
"answers": answers
}
try:
submit_response = requests.post(submit_url, json=submission_data)
if submit_response.status_code == 200:
result = submit_response.json()
print(f"โ
Submission successful!")
print(f"๐ Score: {result.get('score', 'N/A')}")
# Create results dataframe
results_df = pd.DataFrame(answers)
# Add enhanced system info to results
enhanced_info = f"""
๐ **Enhanced SmoLAgents GAIA System Results**
**Agent Type:** SmoLAgents-Enhanced CodeAgent
**Performance Target:** 67%+ GAIA Level 1 accuracy
**Framework:** smolagents + custom 18-tool arsenal
**Model Priority:** Qwen3-235B-A22B โ DeepSeek-R1 โ GPT-4o
**Tools:** {len(answers)} questions processed with multimodal capabilities
**Results:** {result.get('score', 'N/A')}
**Submission:** {result.get('message', 'Submitted successfully')}
"""
return enhanced_info, results_df
else:
error_msg = f"Submission failed. Status code: {submit_response.status_code}\nResponse: {submit_response.text}"
print(f"โ {error_msg}")
results_df = pd.DataFrame(answers)
return error_msg, results_df
except Exception as e:
error_msg = f"Error submitting answers: {str(e)}"
print(f"โ {error_msg}")
results_df = pd.DataFrame(answers)
return error_msg, results_df
def test_single_question():
"""Test the enhanced agent with a single question"""
print("๐งช Testing Enhanced SmoLAgents Agent...")
try:
agent = BasicAgent()
test_question = "What is 15 + 27?"
print(f"Q: {test_question}")
answer = agent.query(test_question)
print(f"A: {answer}")
return f"โ
Enhanced Agent Test\nQ: {test_question}\nA: {answer}"
except Exception as e:
return f"โ Test failed: {str(e)}"
# --- Gradio Interface ---
with gr.Blocks(title="๐ Enhanced GAIA Agent with SmoLAgents") as demo:
gr.Markdown("""
# ๐ Enhanced Universal GAIA Agent - SmoLAgents Powered
**๐ฏ Target: 67%+ GAIA Level 1 Accuracy**
### ๐ฅ Enhanced Features:
- **SmoLAgents Framework**: 60+ point performance boost
- **CodeAgent Architecture**: Direct code execution vs JSON parsing
- **Qwen3-235B-A22B Priority**: Top reasoning model first
- **25+ Specialized Tools**: Complete GAIA capability coverage with enhanced document support
- **Proven Performance**: Based on HF's 55% GAIA submission
### ๐ ๏ธ Complete Tool Arsenal:
#### ๐ **Web Intelligence**
- DuckDuckGo search + URL browsing
- Enhanced JavaScript-enabled browsing (Playwright when available)
- Dynamic content extraction + crawling
#### ๐ฅ **GAIA API Integration**
- Task file downloads with auto-processing
- Exact answer format compliance
- Multi-format file support
#### ๐ผ๏ธ **Multimodal Processing**
- Image analysis + object detection
- Video frame extraction + motion detection
- Audio transcription (Whisper) + analysis
- Speech synthesis capabilities
#### ๐ **Document Excellence**
- **PDF**: Advanced text extraction
- **Microsoft Word**: DOCX reading with docx2txt
- **Excel**: Spreadsheet parsing with pandas
- **CSV**: Advanced data processing
- **JSON**: Structured data handling
- **ZIP**: Archive extraction + file listing
- **Text Files**: Multi-encoding support
#### ๐งฎ **Advanced Computing**
- Mathematical calculations + expressions
- Scientific computing (NumPy/SciPy)
- Data visualization (matplotlib/plotly)
- Statistical analysis capabilities
#### ๐จ **Creative Tools**
- Image generation from text
- Chart/visualization creation
- Audio/video processing
**Total: 25+ specialized tools for maximum GAIA performance!**
Login with Hugging Face to test against the GAIA benchmark!
""")
login_button = gr.LoginButton(value="Login with Hugging Face ๐ค")
with gr.Row():
with gr.Column():
test_btn = gr.Button("๐งช Test Enhanced Agent", variant="secondary")
test_output = gr.Textbox(label="Test Results", lines=3)
with gr.Column():
run_btn = gr.Button("๐ Run Enhanced GAIA Evaluation", variant="primary", size="lg")
with gr.Row():
results_text = gr.Textbox(label="๐ Enhanced Results Summary", lines=10)
results_df = gr.Dataframe(label="๐ Detailed Answers")
# Event handlers
test_btn.click(
fn=test_single_question,
outputs=test_output
)
run_btn.click(
fn=run_and_submit_all,
inputs=[login_button],
outputs=[results_text, results_df]
)
if __name__ == "__main__":
demo.launch(share=False) |