- Added
validation_cyclesparameter (default: 3) - Implemented outer loop for answer validation checkpoints
- Implemented inner loop for fast Solr optimization
- Added pattern database integration for iteration tracking
- Added incremental learning (never revert changes)
- Added
iteration_contextparameter to multi-agent system
- Added
--validation-cyclesCLI parameter - Updated default to 3 cycles for correlation data collection
- Updated help text and display output
- Removed invalid
disable_mcp=Trueparameter - Added
iteration_contextparameter toget_optimized_suggestion() - Updated Synthesizer prompt to emphasize incremental improvement
- New script to analyze F1 vs answer_correctness correlation
- Generates visualizations and comprehensive reports
- Provides recommendations for validation strategies
$ uv run pytest tests/test_pattern_fix_logic.py -v
============================== 28 passed in 0.34s ==============================Tests cover:
- No-doc ticket handling
- Skip tag classification
- Pattern success criteria
- RAG quality warnings
- Composite score calculation
- Baseline improvement tracking
- Edge cases (empty patterns, single ticket, etc.)
$ uv run pytest tests/test_ticket_evaluation.py -v
============================== 33 passed in 0.32s ==============================Tests cover:
- TicketEvaluation: properties, scoring, variance, status
- PatternEvaluation: success rate, criteria, ticket classification
- Baseline comparison
- Edge cases
$ uv run pytest tests/test_solr_multi_agent.py -v
============================== 14 passed in 0.29s ==============================Tests cover:
- Initialization
- Solr Expert analysis
- Code Expert analysis
- Synthesizer logic
- Error handling
- Real-world scenarios
FIXED: Removed invalid disable_mcp=True parameter that was causing test failures.
File: tests/test_fix_pattern_database.py (needs new tests)
What to test:
record_iteration()correctly stores iteration dataget_iteration_context()formats context for multi-agent- Iteration JSONL file format is correct
- Context includes "BUILD ON" and "AVOID" sections
File: tests/test_nested_loop.py (NEW FILE NEEDED)
What to test:
- Outer loop runs
validation_cyclestimes - Inner loop exits early when F1 improves
- Answer validation checkpoint runs after each cycle
- Early exit when answer_correctness >= threshold
- Incremental learning (no reverts)
- Iteration context passed to multi-agent
File: tests/test_cli_parameters.py (NEW FILE NEEDED)
What to test:
--validation-cyclesparameter parsed correctly- Default value is 3
- Parameter passed to Python script
- Quick mode sets appropriate defaults
Before running production fix loop:
- Verify fix.sh accepts
--validation-cycles 3 - Verify
--helpshows new parameter - Test quick mode:
./runners/fix.sh --quick - Verify pattern database file created:
.diagnostics/{pattern_id}/{pattern_id}_iterations.jsonl - Verify correlation analysis script:
uv run python scripts/analyze_metric_correlations.py --all
- No existing iteration data: Correlation analysis requires data from new runs
- Pattern database tests incomplete: Need to add tests for
record_iteration()andget_iteration_context() - No integration test: Need end-to-end test of nested loop with mock data
- ✅ Fix bug in solr_multi_agent.py - DONE (removed invalid parameter)
- ✅ Update fix.sh - DONE (added --validation-cycles)
⚠️ Add tests for pattern database - RECOMMENDED⚠️ Add integration test for nested loop - NICE TO HAVE
Use default settings to collect correlation data:
./runners/fix.sh BOOTLOADER_GRUB_ISSUES --mode fullThis will:
- Run 3 validation cycles (outer loop)
- Run up to 10 Solr iterations per cycle (inner loop)
- Create
.diagnostics/BOOTLOADER_GRUB_ISSUES/BOOTLOADER_GRUB_ISSUES_iterations.jsonl - Potentially exit early if answer_correctness >= 0.85
- Take 1.5-3.5 hours depending on how quickly it converges
Analyze correlation:
uv run python scripts/analyze_metric_correlations.py BOOTLOADER_GRUB_ISSUES --report correlations.mdThis will tell you:
- Does F1 improvement predict answer_correctness improvement? (r > 0.7 = yes)
- Should you use fast validation strategy or keep full validations?
- Per-pattern recommendations for validation frequency
- Existing tests all pass
- Bug fixed (invalid parameter removed)
- CLI parameters properly added
- Core logic unchanged (pattern evaluation, scoring, etc.)
- Pattern database iteration tracking untested
- Nested loop logic not covered by existing tests
- Correlation analysis requires real data to validate
- Run on single pattern first (BOOTLOADER_GRUB_ISSUES)
- Monitor logs for errors
- Verify iteration JSONL file created correctly
- Check correlation analysis output manually
READY FOR PRODUCTION RUN with caveats:
✅ All existing tests pass
✅ Bug fixed in multi-agent system
✅ CLI properly configured
✅ Correlation analysis tool ready
Recommended action: Kick off first production run on BOOTLOADER_GRUB_ISSUES pattern to collect data, then analyze correlation results.