(input_file, output_file, model_name, api_key, base_url)
| 61 | return False |
| 62 | |
| 63 | def process_json_file(input_file, output_file, model_name, api_key, base_url): |
| 64 | |
| 65 | with open(input_file, 'r') as f: |
| 66 | data = json.load(f) |
| 67 | |
| 68 | #data = data[:10] |
| 69 | |
| 70 | client = OpenAI(api_key=api_key, base_url=base_url) |
| 71 | |
| 72 | success_count = 0 |
| 73 | for entry in tqdm(data, desc="Processing entries"): |
| 74 | |
| 75 | if 'label_set' in entry: |
| 76 | del entry['label_set'] |
| 77 | if process_entry(model_name, client, entry): |
| 78 | success_count += 1 |
| 79 | |
| 80 | with open(output_file, 'w') as f: |
| 81 | json.dump(data, f, indent=2, ensure_ascii=False) |
| 82 | |
| 83 | print(f"\nProcessing completed. Success: {success_count}/{len(data)}") |
| 84 | |
| 85 | if __name__ == "__main__": |
| 86 | parser = argparse.ArgumentParser(description="Process emotion recognition results with GPT-4") |
no test coverage detected