docs: add Session 9 summary - crash recovery and HF Space debugging

doc/activity.md

@@ -5440,3 +5440,140 @@ result = client.predict(run_date="2025-09-30", forecast_type="smoke_test")
 - `src/forecasting/chronos_inference.py` - Main logic
 - `src/forecasting/dynamic_forecast.py` - Data extraction
 - `app.py` - Gradio interface
+
+## Session 9: Crash Recovery & HF Space Debugging (Nov 14, 2025 19:00-21:00 UTC)
+
+### Crash Recovery
+
+**Context**: Claude Code crashed during Session 8 testing. Recovered workflow state from activity.md and git status.
+
+**Session State Before Crash**:
+- HF Space successfully deployed with Gradio API
+- Space was responding (58s inference times)
+- Forecast files being generated but empty (only timestamps, no predictions)
+- Testing/debugging in progress
+
+### Critical Bug Identified
+
+**NumPy Method Calls Error** (src/forecasting/chronos_inference.py:189-191):
+```python
+# WRONG (line 189-191)
+forecast_numpy.median(axis=0)  # NumPy arrays don't have .median() method
+forecast_numpy.quantile(0.1, axis=0)  # or .quantile() method
+
+# CORRECT
+np.median(forecast_numpy, axis=0)
+np.quantile(forecast_numpy, 0.1, axis=0)
+```
+
+**Root Cause**: NumPy functions were incorrectly called as array methods, causing silent failures in inference pipeline. Forecasts ran but produced no output.
+
+### Debugging Workflow
+
+**Attempt 1**: Fix NumPy calls + push → Space rebuild → Test
+- Result: Forecasts still empty (60 second runtime but no data)
+
+**Attempt 2**: Add diagnostic logging to track errors
+- Added console logging to export step
+- Still couldn't see Space stdout/stderr via API
+
+**Attempt 3**: Add debug file output
+- Modified run_inference() to write debug.txt with error details
+- Modified to return debug file if all forecasts fail
+- Result: Not receiving debug files (suggests Space hasn't rebuilt or forecasts "succeeding")
+
+**Attempt 4**: Create diagnostic endpoint
+- Created `diagnostic.py` (238 lines) - comprehensive environment test script
+- Modified `app.py` to add diagnostic endpoint with UI button
+- Tests: Python env, dependencies, dataset loading, model loading, full inference
+- Status: Deployed but Space rebuild not yet complete
+
+### Commits Made (4 total)
+
+1. `2c1d599`: fix: correct numpy median/quantile calls in inference pipeline
+2. `3f32d3a`: debug: add diagnostic logging to inference export step
+3. `7d5b63d`: debug: return debug file when all forecasts fail
+4. `2dc6653`: feat: add comprehensive diagnostic endpoint for Space debugging
+
+### Current Status
+
+**HF Space**:
+- API responding (evgueni-p-fbmc-chronos2.hf.space)
+- Only /forecast_api endpoint visible (diagnostic endpoint not yet deployed)
+- Space appears to still be rebuilding with latest changes
+- Forecast files generated but empty (168 rows × 1 column - timestamps only)
+
+**Diagnostic Tools Created**:
+- `diagnostic.py`: Standalone diagnostic script (tests all components)
+- App diagnostic endpoint: Will run full environment check when Space rebuilds
+- Enhanced logging throughout inference pipeline
+
+**Root Cause Uncertainty**:
+- NumPy bug fixed but forecasts still empty
+- Cannot see Space logs/errors through API
+- Multiple rebuild cycles may have delays or caching issues
+- Need diagnostic endpoint to become active for full diagnosis
+
+### Files Created
+
+- `diagnostic.py` (238 lines) - comprehensive environment test script
+- `test_api.py` (33 lines) - API connection test script
+- `validate_forecast.py` (49 lines) - forecast validation script
+- `run_smoke_test.py` (49 lines) - smoke test runner (obsolete)
+
+### Files Modified
+
+- `src/forecasting/chronos_inference.py`:
+  - Fixed NumPy method calls → function calls
+  - Added debug file output
+  - Enhanced export logging
+  - Debug file fallback return
+- `app.py`:
+  - Added run_diagnostic() function
+  - Added diagnostic UI button and endpoint
+
+### Next Session Actions
+
+**CRITICAL - Priority 1**: Wait for Space rebuild & run diagnostic endpoint
+```python
+from gradio_client import Client
+client = Client("evgueni-p/fbmc-chronos2", hf_token=HF_TOKEN)
+result = client.predict(api_name="/run_diagnostic")  # Will show all endpoints when ready
+# Read diagnostic report to identify actual errors
+```
+
+**Priority 2**: Once diagnosis complete, fix identified issues
+
+**Priority 3**: Validate smoke test works end-to-end
+
+**Priority 4**: Run full 38-border forecast
+
+**Priority 5**: Evaluate MAE on Oct 1-14 actuals
+
+**Priority 6**: Clean up test files (archive to `archive/testing/`)
+
+**Priority 7**: Document Day 3 completion in activity.md
+
+### Key Learnings
+
+1. **Remote debugging limitation**: Cannot see Space stdout/stderr through Gradio API
+2. **Solution**: Create diagnostic endpoint that returns report file
+3. **NumPy arrays vs functions**: Always use `np.function(array)` not `array.method()`
+4. **Space rebuild delays**: May take 3-5 minutes, hard to confirm completion status
+5. **File caching**: Clear Gradio client cache between tests
+
+### Session Metrics
+
+- Duration: ~2 hours
+- Bugs identified: 1 critical (NumPy methods)
+- Commits: 4
+- Space rebuilds triggered: 4
+- Diagnostic approach: Evolved from logs → debug files → full diagnostic endpoint
+
+---
+
+**Status**: [BLOCKED] Waiting for HF Space rebuild with diagnostic endpoint
+**Timestamp**: 2025-11-14 21:00 UTC
+**Next Session**: Run diagnostics, fix identified issues, complete Day 3 validation
+
+---