| import json |
| import os |
| from tqdm import tqdm |
| from planner import PlannerCombine, PlannerCombineWithTrueSQL |
| import argparse |
| from multiprocessing import Pool |
|
|
| |
| parser = argparse.ArgumentParser() |
| parser.add_argument('--input_file', type=str, default='../data/sft_bird_with_evidence_train_text2sql.json') |
| parser.add_argument('--output_file', type=str, default='../data/planner/planner_select_bird_with_evidence_train.jsonl') |
| parser.add_argument('--endpoint_type', type=str, default='llamacpp', choices=['vllm', 'llamacpp', 'openai']) |
| parser.add_argument('--mode', type=str, choices=['select', 'condition', 'combine', 'combine_with_true_sql'], default='combine') |
| parser.add_argument('--prompt', choices=['few-shot', 'cot'], default='few-shot') |
| args = parser.parse_args() |
|
|
| if args.input_file.endswith('.json'): |
| data = json.load(open(args.input_file)) |
| elif args.input_file.endswith('.jsonl'): |
| data = [] |
| with open(args.input_file, 'r') as f: |
| for line in f: |
| data.append(json.loads(line)) |
|
|
| |
| if os.path.exists(args.output_file): |
| old_output = [] |
| with open(args.output_file, 'r') as f: |
| for line in f: |
| old_output.append(json.loads(line)) |
| data[:len(old_output)] = old_output |
| else: |
| old_output = [] |
|
|
| |
| |
| os.makedirs(os.path.dirname(args.output_file), exist_ok=True) |
| output_file = open(args.output_file, 'a+') |
|
|
| if args.mode == 'combine': |
| planner = PlannerCombine(endpoint_type=args.endpoint_type) |
| elif args.mode == 'combine_with_true_sql': |
| planner = PlannerCombineWithTrueSQL(endpoint_type=args.endpoint_type) |
|
|
| if args.prompt == 'cot': |
| planner.prompt_template = """{schema} |
| |
| Question: {question} |
| External knowledge: {evidence} |
| |
| Use this hidden True SQL query to write correct analysis that derives to the correct answer. The True SQL query cannot be used in the analysis. |
| Hidden True SQL query: {true_sql_query} |
| |
| Write your thought in short then write the final SQL query, answer in this format: |
| [your short thought step-by-step] |
| Final SQL query: |
| ``` |
| [SQL query] |
| ``` |
| """ |
|
|
| def process_sample(sample): |
| answer = planner.generate(sample) |
| sample[f'planner_{args.mode}'] = answer |
| return sample |
|
|
| def main(): |
| chunk_size = 4 |
| with open(args.output_file, 'a') as output_file: |
| for i in tqdm(range(len(old_output), len(data), chunk_size), total=(len(data) - len(old_output))//chunk_size): |
| chunk = data[i:i+chunk_size] |
| pool = Pool(chunk_size) |
| processed_samples = pool.map(process_sample, chunk) |
| pool.close() |
|
|
| if len(processed_samples) > 0: |
| print(processed_samples[0][f'planner_{args.mode}']) |
| |
| for sample in processed_samples: |
| output_file.write(json.dumps(sample, ensure_ascii=False) + '\n') |
|
|
| if __name__ == '__main__': |
| main() |
|
|