Spaces:
Sleeping
Sleeping
| """ | |
| Gradio Web Interface for CoDA. | |
| Provides a user-friendly web UI for the CoDA visualization system, | |
| designed for deployment on Hugging Face Spaces. | |
| """ | |
| import logging | |
| import os | |
| import tempfile | |
| from pathlib import Path | |
| from typing import Optional | |
| import gradio as gr | |
| logging.basicConfig( | |
| level=logging.INFO, | |
| format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" | |
| ) | |
| logger = logging.getLogger(__name__) | |
| def create_coda_interface(): | |
| """Create the Gradio interface for CoDA.""" | |
| def process_visualization( | |
| query: str, | |
| data_file, | |
| progress=gr.Progress() | |
| ) -> tuple[Optional[str], str, str]: | |
| """ | |
| Process a visualization request. | |
| Args: | |
| query: Natural language visualization query | |
| data_file: Uploaded data file | |
| progress: Gradio progress tracker | |
| Returns: | |
| Tuple of (image_path, status_message, details) | |
| """ | |
| if not query.strip(): | |
| return None, "❌ Error", "Please enter a visualization query." | |
| if data_file is None: | |
| return None, "❌ Error", "Please upload a data file." | |
| try: | |
| from coda.config import Config | |
| from coda.orchestrator import CodaOrchestrator | |
| except ImportError as e: | |
| return None, "❌ Import Error", f"Failed to import CoDA: {e}" | |
| groq_api_key = os.getenv("GROQ_API_KEY", "") | |
| if not groq_api_key: | |
| return ( | |
| None, | |
| "❌ Configuration Error", | |
| "GROQ_API_KEY environment variable is not set. " | |
| "Please add your API key in the Spaces settings." | |
| ) | |
| with tempfile.TemporaryDirectory() as temp_dir: | |
| data_path = Path(temp_dir) / Path(data_file.name).name | |
| with open(data_file.name, 'rb') as src: | |
| with open(data_path, 'wb') as dst: | |
| dst.write(src.read()) | |
| def update_progress(status: str, pct: float): | |
| progress(pct, desc=status) | |
| try: | |
| config = Config( | |
| groq_api_key=groq_api_key, | |
| ) | |
| orchestrator = CodaOrchestrator( | |
| config=config, | |
| progress_callback=update_progress, | |
| ) | |
| result = orchestrator.run( | |
| query=query, | |
| data_paths=[str(data_path)], | |
| ) | |
| if result.success and result.output_file: | |
| scores = result.scores or {} | |
| details = format_results(result, scores) | |
| return result.output_file, "✅ Success", details | |
| else: | |
| error_msg = result.error or "Unknown error occurred" | |
| return None, "❌ Failed", f"Visualization failed: {error_msg}" | |
| except Exception as e: | |
| logger.exception("Pipeline error") | |
| return None, "❌ Error", f"An error occurred: {str(e)}" | |
| def format_results(result, scores: dict) -> str: | |
| """Format the results for display.""" | |
| lines = [ | |
| f"**Iterations:** {result.iterations}", | |
| "", | |
| "### Quality Scores", | |
| ] | |
| if scores: | |
| for key, value in scores.items(): | |
| emoji = "🟢" if value >= 7 else "🟡" if value >= 5 else "🔴" | |
| lines.append(f"- {key.title()}: {emoji} {value:.1f}/10") | |
| if result.evaluation: | |
| if result.evaluation.strengths: | |
| lines.extend(["", "### Strengths"]) | |
| for s in result.evaluation.strengths[:3]: | |
| lines.append(f"- {s}") | |
| if result.evaluation.recommendations: | |
| lines.extend(["", "### Recommendations"]) | |
| for r in result.evaluation.recommendations[:3]: | |
| lines.append(f"- {r}") | |
| return "\n".join(lines) | |
| with gr.Blocks( | |
| title="CoDA - Collaborative Data Visualization", | |
| theme=gr.themes.Soft(), | |
| css=""" | |
| .main-title { | |
| text-align: center; | |
| margin-bottom: 1rem; | |
| } | |
| .status-box { | |
| padding: 1rem; | |
| border-radius: 8px; | |
| margin-top: 1rem; | |
| } | |
| """ | |
| ) as interface: | |
| gr.Markdown( | |
| """ | |
| # 🎨 CoDA: Collaborative Data Visualization Agents | |
| Transform your data into beautiful visualizations using natural language. | |
| Simply upload your data and describe what you want to see! | |
| """, | |
| elem_classes=["main-title"] | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| query_input = gr.Textbox( | |
| label="Visualization Query", | |
| placeholder="e.g., 'Create a line chart showing sales trends over time'", | |
| lines=3, | |
| ) | |
| file_input = gr.File( | |
| label="Upload Data File", | |
| file_types=[".csv", ".json", ".xlsx", ".xls", ".parquet"], | |
| ) | |
| submit_btn = gr.Button( | |
| "🚀 Generate Visualization", | |
| variant="primary", | |
| size="lg", | |
| ) | |
| gr.Markdown( | |
| """ | |
| ### Supported Formats | |
| - CSV, JSON, Excel (.xlsx, .xls), Parquet | |
| ### Example Queries | |
| - "Show me a bar chart of sales by category" | |
| - "Create a scatter plot of price vs quantity" | |
| - "Plot the distribution of ages as a histogram" | |
| """ | |
| ) | |
| with gr.Column(scale=2): | |
| output_image = gr.Image( | |
| label="Generated Visualization", | |
| type="filepath", | |
| ) | |
| with gr.Row(): | |
| status_output = gr.Textbox( | |
| label="Status", | |
| interactive=False, | |
| ) | |
| details_output = gr.Markdown( | |
| label="Details", | |
| ) | |
| gr.Examples( | |
| examples=[ | |
| ["Create a bar chart showing the top 10 values", None], | |
| ["Plot a line chart of trends over time", None], | |
| ["Show a scatter plot with correlation", None], | |
| ["Create a pie chart of category distribution", None], | |
| ], | |
| inputs=[query_input, file_input], | |
| ) | |
| submit_btn.click( | |
| fn=process_visualization, | |
| inputs=[query_input, file_input], | |
| outputs=[output_image, status_output, details_output], | |
| ) | |
| return interface | |
| app = create_coda_interface() | |
| if __name__ == "__main__": | |
| app.launch() | |