Commit History

  1. Update env/environment.py

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    1eb9a1b
  2. Update training/colab_notebook.py

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  3. Update env/environment.py

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  4. Update training/train_agent.py

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  5. Update training/train_agent.py

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    86abfc1
  6. Update training/train_agent.py

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    987f2db

  1. Upload reward_curve.png

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  2. Add Colab training notebook link

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  3. changes evalute_agent

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  1. updated readme

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  2. corrected

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  3. Reward curve: strategic +36.7pts vs random +0.0pts

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  1. changes

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  2. updated requirements

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  3. updated readme

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  4. prproject.toml and readme updated

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  5. Final Round 2: all checks passing, openenv validate OK

    f30d05a

  1. Fix gitignore - exclude pycache

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  2. Force add all env, dataset, api files - gitignore fix

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  3. Add db_simulator and scenario files

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  4. Round 2: SQL Database Engineer Agent - 24/24 tests passing

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  1. changed

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  2. changed

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  3. changed

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  4. changed

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  5. changed

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  6. changed

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  7. Use real LLM call for proxy check + baseline scores for task validation

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  8. Use real LLM calls through API_BASE_URL proxy

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  9. Clean inference.py using baseline scores strictly between 0 and 1

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  10. Normalize all rewards to strictly (0.001, 0.999) range in step()

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  11. Fix GraderResponse schema example score from 1 to 0.75

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  12. Clamp all reward scores strictly between 0.001 and 0.999

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  13. Clamp grader scores strictly between 0.001 and 0.999 in endpoint and model

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  14. Fix rewards never exactly 0.0 or 1.0 using proper normalization

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  15. Clamp all step rewards strictly between 0.001 and 0.999

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  1. Fix score - shift rewards to positive range, never 0.0 or 1.0

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  2. Ensure score never below 0.1 to fix out of range error

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  3. Fix score strictly between 0.001 and 0.999 - never 0.0 or 1.0

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  4. corrected everytihng

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  5. again fixed graders

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  6. fixed

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  7. again changed

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  8. new fixed

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  9. done

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  10. fixed

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  11. done

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  12. done

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  13. fixed new error

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  14. fixed

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