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## Description `_strip_fenced_json` only stripped a markdown fence when the string *started with* ```` ``` ````. When the model prefixed prose before the fence (e.g. `Here is the JSON:\n\n```json ...`) despite being told to return JSON only, the guard was skipped and `json.loads` ran on the prose, raising `JSONDecodeError`. The claude-cli streaming path surfaced this as `returned unparseable output`, and `headroom learn` silently discarded the LLM analysis, degrading to "No actionable patterns found". This is the parsing-side cousin of the silent-degradation issue fixed in #373. Closes #1989. Related: #373. ## Type of Change - [x] Bug fix (non-breaking change that fixes an issue) - [ ] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [ ] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made - `headroom/learn/analyzer.py`: rewrote `_strip_fenced_json` to locate the fenced block wherever it appears, then fall back to the whole text, then to a first-`{` / last-`}` slice, only re-raising `JSONDecodeError` if nothing parses as a JSON object. Preserves the prior "first opening / last closing fence" behaviour and triple-backtick content inside the payload. Fixes all three call sites (non-streaming CLI, claude-cli streaming, litellm). - `tests/test_learn/test_analyzer.py`: added regression cases to `TestStripFencedJson` for preamble-before-fence, prose around a bare object, and triple-backticks inside the payload. ## Testing - [x] Unit tests pass (`pytest`) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom`) — scoped to the changed module (see Additional Notes) - [x] New tests added for new functionality - [x] Manual testing performed ### Test Output ```text $ pytest tests/test_learn/test_analyzer.py -q ........................................................................ [ 86%] ........... [100%] 83 passed, 1 warning in 2.18s $ ruff check headroom/learn/analyzer.py tests/test_learn/test_analyzer.py All checks passed! $ ruff format --check headroom/learn/analyzer.py tests/test_learn/test_analyzer.py 2 files already formatted $ mypy --ignore-missing-imports --follow-imports=silent headroom/learn/analyzer.py Success: no issues found in 1 source file ``` ## Real Behavior Proof - Environment: macOS, Python 3.13.12, headroom-ai at this branch (runtime deps from an installed 0.30.0 env). - Exact command / steps: ran the old vs new `_strip_fenced_json` on the exact failing model output (a prose preamble followed by a ```json fence), then applied the fix over an installed 0.30.0 and re-ran the previously failing `headroom learn --apply`. Input sample: `'The JSON is my deliverable for this analysis task. Here it is:\n\n```json\n{"context_file_rules": [], "memory_file_rules": []}\n```'` - Observed result: OLD raised `JSONDecodeError: Expecting value: line 1 column 1 (char 0)`; NEW returned `{'context_file_rules': [], 'memory_file_rules': []}`. The real `headroom learn --apply` run that had been failing with `returned unparseable output` then completed and consumed the LLM analysis instead of dropping it. Full transcript: ```text OLD: JSONDecodeError -> Expecting value: line 1 column 1 (char 0) NEW: {'context_file_rules': [], 'memory_file_rules': []} ``` - Not tested: full end-to-end `headroom learn --apply` was not re-run inside CI here (it shells out to a live `claude` CLI); the parser is exercised deterministically by the added unit tests and the before/after repro above. ## Review Readiness - [x] I have performed a self-review - [x] This PR is ready for human review ## Checklist - [x] My code follows the project's style guidelines - [x] I have performed a self-review of my code - [x] I have commented my code, particularly in hard-to-understand areas - [ ] I have made corresponding changes to the documentation (N/A — updated the function docstring only; no external docs affected) - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [ ] I have updated the CHANGELOG.md if applicable (N/A — no CHANGELOG entry convention observed for this fix; happy to add if maintainers prefer) ## Additional Notes - `mypy` was run against the changed module in isolation (`--ignore-missing-imports --follow-imports=silent`) rather than the full project, because I validated in an ad-hoc environment; the change keeps the existing `-> dict` signature and annotations, so it is type-neutral. - Not addressed here (possible follow-up): the failure is swallowed as a warning in `analyze()`, so users only see "No actionable patterns found" with no signal the LLM pass produced nothing — the same silent-degradation class as #373, on the parsing side. |
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| .. | ||
| __init__.py | ||
| test_analyzer.py | ||
| test_claude_config_dir.py | ||
| test_gemini_scanner.py | ||
| test_integration.py | ||
| test_loop_weighting.py | ||
| test_opencode_scanner.py | ||
| test_plugin_encoding.py | ||
| test_registry.py | ||
| test_rtk_loop_eval.py | ||
| test_scanner.py | ||
| test_subagent_scanning.py | ||
| test_writer.py | ||