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feat(wave12): Add 6 optimization examples for pyo3-dspy-optimization (~9.8k lines)
Complete optimization workflow examples demonstrating DSPy teleprompters, model versioning, evaluation, automated pipelines, and model comparison. Examples: 1. bootstrap-fewshot (5 files, ~1,810 lines) - Run BootstrapFewShot teleprompter from Rust - TrainingDataset with load/split methods - Progress tracking with callbacks - Model metadata and saving - 50 training examples included 2. mipro-optimization (6 files, ~1,944 lines) - Run MIPROv2 teleprompter from Rust - Multi-prompt instruction optimization - Temperature scheduling - Candidate tracking with statistics - Train/dev split handling (50/20 examples) 3. model-versioning (4 files, ~1,551 lines) - Semantic versioning with semver crate - ModelRegistry with HashMap storage - Promotion workflow (dev → staging → production) - Status history and audit trail - Model comparison and rollback - Registry statistics 4. evaluation-framework (5 files, ~1,962 lines) - EvaluationHarness with multiple metrics - 5 built-in metrics (Accuracy, ExactMatch, F1, BLEU, ROUGE) - Statistical analysis (mean, std, percentiles) - Multi-model comparison - Statistical significance testing (Welch's t-test) - 30 diverse test examples 5. automated-pipeline (5 files, ~1,925 lines) - End-to-end optimization pipeline - Cron-based scheduling - Four stages (DataPrep, Training, Validation, Deployment) - Quality gates with thresholds - Notification system (webhooks, Slack) - Automatic deployment and rollback - Pipeline state persistence 6. model-comparison (4 files, ~1,474 lines) - Systematic comparison of 2-5 models - Statistical testing (t-test, Cohen's d) - Winner determination with weighted criteria - ASCII table and HTML report generation - Multiple test set support Total: 29 files, ~10,666 lines All examples compile successfully and demonstrate production-ready optimization patterns.
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[package]
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name = "automated-pipeline"
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version = "0.1.0"
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edition = "2021"
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[dependencies]
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# PyO3 for Python-Rust interop
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pyo3 = { version = "0.20", features = ["auto-initialize"] }
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# Async runtime
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tokio = { version = "1.35", features = ["full"] }
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# Cron scheduling
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tokio-cron-scheduler = "0.10"
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# Error handling
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anyhow = "1.0"
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# Serialization
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serde = { version = "1.0", features = ["derive"] }
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serde_json = "1.0"
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serde_yaml = "0.9"
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# HTTP client for webhooks
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reqwest = { version = "0.11", features = ["json"] }
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# Logging
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tracing = "0.1"
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tracing-subscriber = { version = "0.3", features = ["env-filter"] }
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# Time handling
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chrono = { version = "0.4", features = ["serde"] }
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[[bin]]
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name = "automated-pipeline"
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path = "src/main.rs"
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[lib]
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name = "automated_pipeline"
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path = "src/lib.rs"

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