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Modifying SPO's README.md

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isaacJinyu 2025-02-07 15:58:48 +08:00
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10
examples/spo/README.md
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@ -21,7 +21,7 @@ ### 2. Define Your Iteration template 📝
Create a Iteration template file `metagpt/ext/spo/settings/task_name.yaml`:
```yaml
prompt: |
solve question.
Please solve the following problem.
requirements: |
...
@ -40,6 +40,14 @@ ### 2. Define Your Iteration template 📝
...
```
Notes:
- `prompt`: Initial prompt for iteration
- `requirements`: Desired effects/outcomes (e.g., generate more thinking, use more humorous language)
- `count`: Target word count for the generated prompt (e.g., 50). Set to None for no limit
- `faq`: QA pairs used for iteration, can include appropriate number of pairs (typically 3)
- `question`: Questions from the dataset used for iteration
- `answer`: Corresponding answers. Can contain desired thinking patterns or responses instead of actual answers, or can be left empty. See `metagpt/ext/spo/settings/Navigate.yaml` for reference
### 3. Implement the Optimizer 🔧
Use `metagpt/ext/spo/optimize.py` to execute:

48
examples/spo/optimize.py
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@ -7,32 +7,32 @@ def parse_args():
parser = argparse.ArgumentParser(description='SPO Optimizer CLI')
# LLM parameter
parser.add_argument('--optimize-model', type=str, default='claude-3-5-sonnet-20240620',
help='Model for optimization')
parser.add_argument('--optimize-temperature', type=float, default=0.7,
help='Temperature for optimization')
parser.add_argument('--evaluate-model', type=str, default='gpt-4o-mini',
help='Model for evaluation')
parser.add_argument('--evaluate-temperature', type=float, default=0.3,
help='Temperature for evaluation')
parser.add_argument('--execute-model', type=str, default='gpt-4o-mini',
help='Model for execution')
parser.add_argument('--execute-temperature', type=float, default=0,
help='Temperature for execution')
parser.add_argument('--opt-model', type=str, default='claude-3-5-sonnet-20240620',
help='Model for optimization')
parser.add_argument('--opt-temp', type=float, default=0.7,
help='Temperature for optimization')
parser.add_argument('--eval-model', type=str, default='gpt-4o-mini',
help='Model for evaluation')
parser.add_argument('--eval-temp', type=float, default=0.3,
help='Temperature for evaluation')
parser.add_argument('--exec-model', type=str, default='gpt-4o-mini',
help='Model for execution')
parser.add_argument('--exec-temp', type=float, default=0,
help='Temperature for execution')
# Optimizer parameter
parser.add_argument('--workspace', type=str, default='workspace',
help='Path for optimized output')
help='Path for optimized output')
parser.add_argument('--initial-round', type=int, default=1,
help='Initial round number')
help='Initial round number')
parser.add_argument('--max-rounds', type=int, default=10,
help='Maximum number of rounds')
help='Maximum number of rounds')
parser.add_argument('--template', type=str, default='Poem.yaml',
help='Template file name')
help='Template file name')
parser.add_argument('--name', type=str, default='Poem',
help='Project name')
help='Project name')
parser.add_argument('--no-iteration', action='store_false', dest='iteration',
help='Disable iteration mode')
help='Disable iteration mode')
return parser.parse_args()
@ -42,16 +42,16 @@ def main():
SPO_LLM.initialize(
optimize_kwargs={
"model": args.optimize_model,
"temperature": args.optimize_temperature
"model": args.opt_model,
"temperature": args.opt_temp
},
evaluate_kwargs={
"model": args.evaluate_model,
"temperature": args.evaluate_temperature
"model": args.eval_model,
"temperature": args.eval_temp
},
execute_kwargs={
"model": args.execute_model,
"temperature": args.execute_temperature
"model": args.exec_model,
"temperature": args.exec_temp
}
)