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import gradio as gr |
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import subprocess |
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import os |
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import re |
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from datetime import datetime |
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def run_evaluation(model_name): |
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results = [] |
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if "OPENROUTER_API_KEY" not in os.environ: |
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return "Error: OPENROUTER_API_KEY not found in environment variables." |
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try: |
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env = os.environ.copy() |
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env["OPENROUTER_API_KEY"] = os.environ["OPENROUTER_API_KEY"] |
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current_date = datetime.now().strftime("%Y%m%d") |
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inference_cmd = f""" |
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cd duckdb-nsql/ && |
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python eval/predict.py \ |
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predict \ |
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eval/data/dev.json \ |
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eval/data/tables.json \ |
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--output-dir output/ \ |
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--stop-tokens ';' \ |
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--max-tokens 30000 \ |
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--overwrite-manifest \ |
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--manifest-client openrouter \ |
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--manifest-engine {model_name} \ |
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--prompt-format duckdbinstgraniteshort |
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""" |
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inference_result = subprocess.run(inference_cmd, shell=True, check=True, capture_output=True, text=True, env=env) |
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results.append("Inference completed.") |
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json_path_match = re.search(r'(.*\.json)', inference_result.stdout) |
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if not json_path_match: |
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raise ValueError("Could not find JSON file path in inference output") |
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json_file = os.path.basename(json_path_match.group(1)) |
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results.append(f"Generated JSON file: {json_file}") |
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eval_cmd = f""" |
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cd duckdb-nsql/ && |
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python eval/evaluate.py evaluate \ |
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--gold eval/data/dev.json \ |
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--db eval/data/databases/ \ |
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--tables eval/data/tables.json \ |
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--output-dir output/ \ |
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--pred output/{json_file} |
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""" |
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eval_result = subprocess.run(eval_cmd, shell=True, check=True, capture_output=True, text=True) |
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metrics = eval_result.stdout |
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if metrics: |
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results.append(f"Evaluation completed:\n{metrics}") |
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else: |
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results.append("Evaluation completed, but couldn't get metrics.") |
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except subprocess.CalledProcessError as e: |
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results.append(f"Error occurred: {str(e)}") |
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results.append(f"Command output: {e.output}") |
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except Exception as e: |
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results.append(f"An unexpected error occurred: {str(e)}") |
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return "\n\n".join(results) |
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with gr.Blocks() as demo: |
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gr.Markdown("# DuckDB SQL Evaluation App (OpenRouter)") |
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model_name = gr.Textbox(label="Model Name (e.g., qwen/qwen-2.5-72b-instruct)") |
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start_btn = gr.Button("Start Evaluation") |
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output = gr.Textbox(label="Output", lines=20) |
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start_btn.click(fn=run_evaluation, inputs=[model_name], outputs=output) |
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demo.launch() |