0bd9547 docs: [#339] add draft issue for AI dataset freshness verification (Jose Celano) fa12000 refactor: [#339] improve validation test module with ProcessRunner and helper functions (Jose Celano) 0938563 fix: [#339] complete dataset/ directory path updates (Jose Celano) f3a41a1 test: [#339] add render validation test for AI training examples (Jose Celano) 313e265 refactor: [#339] organize AI training materials under dataset/ directory (Jose Celano) 991d697 refactor: [#339] rename directories for better clarity (Jose Celano) e25a82c feat: [#339] add AI training outputs with complete input/output dataset (Jose Celano) bbbd642 docs: [#339] mark task 11.3 as completed in roadmap (Jose Celano) e8df992 docs: [#339] update progress - all phases complete (Jose Celano) c4a91c0 feat: [#339] add integration test for AI training examples (Jose Celano) cb77e8f feat: [#339] add comprehensive AI training documentation (Jose Celano) fecfcbf feat: [#339] add 15 example environment configurations (Jose Celano) 60734cd feat: [#339] add environment configuration questionnaire for AI agents (Jose Celano) 2e22521 feat: [#339] add optional description field to EnvironmentSection (Jose Celano) c4ad07d docs: mark task 10.3 (DNS resolution check) as completed in roadmap (Jose Celano) Pull request description: ## Overview This PR implements Issue #339, providing structured resources to help AI agents guide users through environment configuration creation. ## Implementation Summary All 6 phases completed: ### Phase 1: Schema Extension ✅ - Added optional `description` field to environment configuration schema - Updated JSON schema (`schemas/environment-config.json`) - Updated Rust DTO (`src/application/command_handlers/create/config/environment_config.rs`) - Maintained backward compatibility (configs without description still work) ### Phase 2: Questionnaire Template ✅ - Created comprehensive questionnaire at `docs/ai-training/questionnaire.md` (494 lines) - Full decision tree covering all configuration requirements - Includes validation rules and conditional logic ### Phase 3-4: Example Configurations ✅ - Created all 15 example scenarios covering common deployment patterns - All examples validated with `cargo run -- validate --env-file` - Each example includes descriptive explanation (2-3 sentences) - Examples use fixture keys only (no sensitive data) ### Phase 5: Documentation ✅ - Created comprehensive README at `docs/ai-training/README.md` (469 lines) - Includes scenarios table, usage instructions, customization guide - Documents common decision points and best practices ### Phase 6: Integration Test ✅ - Created integration test at `tests/validate_ai_training_examples.rs` - 4 test functions validating all aspects: - Configuration validation (all 15 examples) - File count verification (exactly 15 examples) - Naming convention enforcement (NN-descriptive-name.json pattern) - Description field presence validation - Added regex dependency for pattern matching - All linters passing ## Example Scenarios Coverage | ID | Scenario | Provider | Database | Trackers | HTTPS | Monitoring | Backup | | --- | ----------------------- | -------- | -------- | -------- | ----- | ---------- | ------ | | 01 | Minimal development | LXD | SQLite | UDP+HTTP | No | No | No | | 02 | Full-stack LXD | LXD | MySQL | 2U+2H | Yes | Yes | Yes | | 03 | Minimal Hetzner | Hetzner | SQLite | UDP+HTTP | No | No | No | | 04 | Full-stack Hetzner | Hetzner | MySQL | 2U+2H | Yes | Yes | Yes | | ... | (11 more scenarios) | ... | ... | ... | ... | ... | ... | ## Benefits **For AI Agents:** - Structured guidance through questionnaire - Few-shot learning from validated examples - Reduced hallucination with real configs as reference - Faster iteration with less trial-and-error **For Users:** - Examples serve as documentation and starting points - Clear mapping from requirements to configuration values - Understanding of common deployment patterns **For Training/RAG:** - Curated dataset with high-quality examples - Coverage of common and edge cases - Machine-readable JSON format - Versioned with deployer releases ## Testing - ✅ All linters pass: `cargo run --bin linter all` - ✅ All examples validated: `cargo run -- validate --env-file` - ✅ Integration tests pass: `cargo test --test validate_ai_training_examples` - ✅ Pre-commit checks pass: `./scripts/pre-commit.sh` ## Files Changed - `schemas/environment-config.json` - Added description field - `src/application/command_handlers/create/config/environment_config.rs` - EnvironmentSection with description - `docs/ai-training/questionnaire.md` - Decision tree questionnaire (494 lines) - `docs/ai-training/examples/*.json` - 15 validated example configurations - `docs/ai-training/README.md` - Comprehensive documentation (469 lines) - `tests/validate_ai_training_examples.rs` - Integration test suite - `Cargo.toml` - Added regex dev-dependency - `docs/issues/339-provide-config-examples-and-questionnaire-for-ai-agents.md` - Updated progress - `docs/roadmap.md` - Marked task 11.3 as completed ## Acceptance Criteria All criteria met: - [x] Optional description field added and validated - [x] Backward compatibility maintained - [x] Questionnaire template created - [x] All 15 examples created with descriptions - [x] Each example validated - [x] README with scenarios table and guidance - [x] Integration test created and passing - [x] All linters passing - [x] Examples use fixture keys only Closes #339 ACKs for top commit: josecelano: ACK 0bd9547 Tree-SHA512: d006c8c6afe77350593103520ca0f22b506ad563e2d55fb987fbacbc0fd2d5ce2de7a7e15a63650c7a669d43dcaaa86dde13b2b1026deb9eb52a61b96503ad51
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 email_address = "0.2.9"
 [dev-dependencies]
 +regex = "1.0"
 rstest = "0.26"
 tracing-test = "0.2"