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Merge pull request #2208 from bluewave-labs/develop-saas
Develop saas -> Master saas (24 Sept)
2 parents 28dd3f5 + 57519b2 commit e28be45

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.claude/settings.local.json

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.env.dev

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EMAIL_ID=your-email@gmail.com
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# Your password from: https://myaccount.google.com/apppasswords
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EMAIL_PASSWORD="aaaa bbbb cccc dddd"
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# Encryption Settings
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ENCRYPTION_ALGORITHM=YOUR_ENCRYPTION_ALGORITHM
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ENCRYPTION_PASSWORD=YOUR_ENCRYPTION_PASSWORD

.env.prod

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EMAIL_ID=your-email@gmail.com
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# Your password from: https://myaccount.google.com/apppasswords
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EMAIL_PASSWORD="aaaa bbbb cccc dddd"
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# Encryption Settings
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ENCRYPTION_ALGORITHM=YOUR_ENCRYPTION_ALGORITHM
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ENCRYPTION_PASSWORD=YOUR_ENCRYPTION_PASSWORD

.gitignore

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.claude
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.github
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.kombai
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.vscode
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.vscode
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agent.md
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agent-output.md

.vscode/launch.json

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.vscode/prompts.json

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.vscode/settings.json

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BiasAndFairnessModule/check_environment.py

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# Dataset Configuration
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artifacts:
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inference_results_path: artifacts/cleaned_inference_results.csv
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postprocessed_results_path: artifacts/postprocessed_results.csv
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dataset:
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name: "adult-census-income"
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source: "scikit-learn/adult-census-income"
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split: "train"
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platform: "huggingface"
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name: adult-census-income
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platform: huggingface
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protected_attributes:
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- "sex"
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- "race"
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target_column: "income"
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- sex
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- race
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sampling:
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enabled: true
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n_samples: 50 # Increased for more meaningful evaluation
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n_samples: 50
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random_seed: 42
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# Post-processing Configuration
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post_processing:
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binary_mapping:
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favorable_outcome: ">50K"
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unfavorable_outcome: "<=50K"
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attribute_groups:
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sex:
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privileged: ["Male"]
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unprivileged: ["Female"]
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race:
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privileged: ["White"]
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unprivileged: ["Black", "Other"]
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# Model Configuration
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model:
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# Hugging Face model configuration
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huggingface:
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enabled: true
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model_id: "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
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device: "cuda" # or "cpu" for CPU-only inference
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max_new_tokens: 50
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temperature: 0.7
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top_p: 0.9
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system_prompt: "You are a strict classifier. You must answer with exactly one of these two strings: '>50K' or '<=50K'. No explanation. No formatting."
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# Metrics Configuration
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source: scikit-learn/adult-census-income
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split: train
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target_column: income
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metrics:
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# Fairness metrics for evaluation
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fairness:
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enabled: true
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metrics:
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- "demographic_parity"
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- "equalized_odds"
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- "predictive_parity"
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# Performance metrics
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- demographic_parity
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- equalized_odds
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performance:
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enabled: false
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enabled: true
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metrics:
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- "accuracy"
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- "precision"
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artifacts:
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inference_results_path: "artifacts/cleaned_inference_results.csv"
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postprocessed_results_path: "artifacts/postprocessed_results.csv"
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- accuracy
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model:
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huggingface:
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device: cpu
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enabled: true
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max_new_tokens: 50
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model_id: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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system_prompt:
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"You are a strict classifier. You must answer with exactly one
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of these two strings: '>50K' or '<=50K'. No explanation. No formatting."
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temperature: 0.7
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top_p: 0.9
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label_behavior: binary
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model_task: binary_classification
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post_processing:
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attribute_groups:
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race:
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privileged:
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- White
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unprivileged:
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- Black
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- Other
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sex:
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privileged:
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- Male
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unprivileged:
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- Female
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binary_mapping:
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favorable_outcome: ">50K"
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unfavorable_outcome: <=50K

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