- Modified the `replace_activity_session_metrics` function to skip EAV inserts for parameters with a defined `source_field`, aligning with the existing logic in `upsert_session_metrics_from_csv_mapped`.
- Enhanced the frontend logic to filter out metrics associated with `source_field` during payload construction, improving data integrity and user experience.
- Added unit tests to validate the new behavior, ensuring that metrics with `source_field` are correctly excluded from inserts.
- Enhanced the `upsert_session_metrics_from_csv_mapped` function to skip EAV writes when a `source_field` is provided, ensuring canonical handling of activity logs.
- Updated the docstring to clarify the behavior regarding `source_field` and EAV logic.
- Added unit tests to validate the new behavior, ensuring correct functionality when `source_field` is set or not set during CSV imports.
- Replaced hardcoded keys in `activity_data_canon.py` with a dynamic retrieval method from the module registry, ensuring that `ACTIVITY_MODULE_REGISTRY_FIELD_KEYS` reflects the current configuration.
- Updated `activity_persistence_orchestrator.py` to utilize the new dynamic field retrieval function, enhancing consistency across the data layer.
- Modified `activity_session_metrics.py` to reference the dynamic field keys, improving maintainability and reducing redundancy in the codebase.
Reverts cd29c7d..026c51b per git revert. Alle zwischenliegenden Commits bleiben in Gitea sichtbar; der Arbeitsbaum entspricht wieder dem Stand von ca8cee9.
Made-with: Cursor
- Introduced `resolve_activity_attribute_schema_for_csv_import` to enhance the handling of training parameters during CSV imports, allowing for the inclusion of active parameters not present in the category/type profile.
- Updated `apply_activity_mapped_column_aliases` and `upsert_session_metrics_from_csv_mapped` to utilize the new CSV import function, ensuring comprehensive mapping and insertion of metrics.
- Added unit tests to validate the new functionality and ensure correct behavior when handling mapped training parameters during CSV imports.
- Updated the `_import_activity` function to include new metrics: duration_min, kcal_active, kcal_resting, hr_avg, hr_max, and distance_km during CSV imports.
- Modified the `insert_activity_csv_minimal` function to accept and store these additional metrics in the activity log.
- Enhanced the `run_activity_post_write_hooks_import` function to utilize the new metrics for auto-evaluation after activity imports.
- Updated the activity import router to pass the new metrics from the CSV file to the database functions, ensuring comprehensive data handling.
- Improved frontend handling of activity entry forms to accommodate the new metrics, enhancing user experience during activity log edits.
- Updated `ACTIVITY_PRODUCTION_ARCHITECTURE_AND_PHASES.md` to clarify the derivation of `ACTIVITY_MODULE_REGISTRY_FIELD_KEYS` from `csv_parser.module_registry`.
- Enhanced `activity_data_canon.py` to eliminate hardcoded key lists, ensuring all registry fields are derived dynamically.
- Refactored the `_import_activity` function to remove redundant parameters and streamline the import process.
- Improved the `insert_activity_csv_minimal` function to handle metrics exclusively through `update_activity_columns`, preventing hardcoded values.
- Updated frontend components to manage editable activity log fields more effectively, ensuring proper handling of metrics during CSV imports.
- Added unit tests to validate the new logic and ensure consistency in activity session metrics handling.
- Updated the `ACTIVITY_SESSION_METRICS_EAV_AGENT_GUIDE` with new details on CSV import processes and EAV handling, improving documentation clarity.
- Refactored the `_import_activity` function to utilize `apply_activity_mapped_column_aliases`, ensuring proper mapping of training parameters and reducing redundancy.
- Introduced validation for numeric bounds in the `activity_csv_registry_updates_from_mapped` function, enhancing data integrity during CSV imports.
- Added new utility functions to manage column aliasing and streamline the upsert process for session metrics, preventing duplicate entries.
- Implemented unit tests to validate the new aliasing logic and ensure correct behavior during session metrics updates.
- Updated the README to include new activity production architecture and phases, improving clarity on the development roadmap.
- Enhanced the `ACTIVITY_SESSION_METRICS_EAV_AGENT_GUIDE` with details on the target architecture and phase plan for production readiness.
- Introduced a new function `merge_column_backed_and_eav_metrics` to streamline the merging of metrics from column-backed and EAV sources, ensuring data integrity and reducing duplication.
- Refactored session metrics handling to eliminate deprecated synchronization methods, improving the overall efficiency of data processing.
- Added unit tests for the new merging logic, ensuring robust validation of metrics handling.
- Replaced the deprecated `resolve_activity_log_column_patch_from_csv` function with `activity_csv_registry_updates_from_mapped` to streamline updates from CSV mappings.
- Updated the `_import_activity` function to utilize the new registry updates, improving data integrity during activity imports.
- Enhanced the activity module registry by adding German labels for various fields, improving localization support.
- Refactored the session metrics handling to ensure only relevant fields are processed, enhancing the overall robustness of CSV imports.
- Enhanced the docstring for `upsert_session_metrics_from_csv_mapped` to clarify the handling of schema parameters and EAV logic.
- Modified the condition for skipping updates based on `source_field` to ensure only patchable columns are processed, improving data integrity during session metrics upsert operations.
- Introduced a new utility function `canonical_csv_header_label` to standardize CSV header labels, improving consistency in field mapping.
- Updated the `_lookup_db_field` function to support prefix matching for longer manual keys, enhancing the accuracy of field resolution.
- Added tests to validate handling of non-breaking space characters in CSV headers and ensure correct mapping to normalized keys, improving robustness of CSV parsing.
- Updated the `ACTIVITY_LOG_PATCHABLE_COLUMNS` and `ACTIVITY_LOG_PATCH_FORBIDDEN` sets to improve validation of CSV imports, ensuring only allowed fields are patched.
- Refactored the `_coerce_raw_value_for_parameter` function to handle string inputs for integer and float types, enhancing data coercion accuracy.
- Modified the `SessionMetricsFields` component to display orphan metrics that do not match the current schema, improving user visibility of imported data discrepancies.
- Enhanced the frontend to handle and display additional metrics, ensuring a more comprehensive representation of session data.
- Updated the CSV import logic to merge active training parameters with static fields for the activity module, improving field mapping accuracy.
- Enhanced validation functions to incorporate dynamic field definitions based on active training parameters, ensuring better data integrity during imports.
- Refactored related functions to streamline the process of handling CSV templates and field mappings, improving maintainability and clarity.
- Added new utility functions for resolving activity log column patches and upserting session metrics from CSV, enhancing the overall import functionality.
- Updated the `get_activity_detail` function to include session metrics in the activity detail output, allowing for enriched data representation.
- Refactored the activity import logic to streamline the process of inserting and updating activity records, utilizing new helper functions for better maintainability.
- Improved the handling of duplicate activity entries by implementing a more robust identification mechanism.
- Enhanced the metadata for activity detail registration to reflect the inclusion of EAV metrics and updated source tables.
- Added a new query parameter `collapseDuplicateSessions` to the activity listing endpoint to enable deduplication of sessions based on date, type, start time, duration, and calories.
- Enhanced backend logic to handle deduplication and return the most recent entry for duplicate sessions.
- Updated frontend to support the new deduplication feature, improving the clarity of displayed activity data.
- Modified API utility to include the new parameter in requests for activity data.
- Introduced a new query parameter for the activity listing endpoint to fetch entries by calendar month (format: YYYY-MM), excluding days and offset.
- Implemented backend validation for the month parameter to ensure correct format and range.
- Enhanced the frontend to support month selection, allowing users to load activities for specific months and dynamically update the displayed entries.
- Improved the user interface to show the selected month and the range of loaded months, enhancing user experience.
- Updated the `replace_activity_session_metrics` function to improve validation logic and error handling for required fields.
- Enhanced the activity listing query to order results by date, start time, and ID, ensuring consistent output.
- Modified the frontend to handle null values in metrics payload and improved the display of activity statistics, including total entries in profile and sample size.
- Added pagination support to the activity listing endpoint with `limit` and `offset` parameters.
- Introduced a `skip_quality_filter` option to allow retrieval of all entries without applying the quality filter.
- Updated the frontend to implement dynamic loading of activity entries and statistics without the quality filter.
- Improved user experience with a "Load More" button for fetching additional entries on the ActivityPage.
- Added new fields to the ActivityEntry model for improved tracking: hr_min, pace_min_per_km, cadence, avg_power, elevation_gain, temperature_celsius, humidity_percent, avg_hr_percent, and kcal_per_km.
- Updated the create_activity function to accommodate the new fields in the activity log.
- Modified session metrics handling to ensure accurate data retrieval and merging based on the updated schema.
- Added a new function to synchronize session metrics with activity log entries, ensuring data consistency.
- Updated the create and update activity endpoints to call the synchronization function after inserting or modifying activity logs.
- Introduced a set of allowed keys for activity log payloads to streamline data handling in the frontend.
- Improved data coercion logic for various data types in the frontend to ensure accurate data submission.
- Implemented a new endpoint to retrieve activity statistics for the last 30 entries, including total calories and duration by activity type.
- Added an endpoint to list activities without assigned training types, grouped by activity type.
- Removed deprecated versions of the statistics and uncategorized activities endpoints for cleaner code.
- Introduced new endpoints for updating training category and type parameters in the backend.
- Added corresponding update functions in the frontend API utility.
- Enhanced the Admin Activity Attribute Profiles page to support editing and saving changes for category and type parameters.
- Implemented state management for editing parameters and improved error handling during updates.
- Introduced Activity Session Metrics for enhanced tracking of session data.
- Updated backend to support new API endpoints for managing session metrics.
- Added new Pydantic models for activity metrics and replaced metrics functionality.
- Enhanced data layer to include session metrics in recent training session data.
- Updated documentation to reflect changes in session metrics handling.
- Added a function to calculate goal progress percentage based on start, target, and current values.
- Updated GoalsPage to display progress in a user-friendly format, including visual progress bars.
- Implemented error handling for goal progress updates in the backend to ensure robustness.
- Add name field to WorkflowNode model
- Extend node_label priority: node.name > prompt_slug > node_type-id
- No new fields in NodeExecutionState (uses existing debug_prompt_slug)
- Simpler approach than previous attempt to avoid 504 timeout
- Add name field to WorkflowNode model
- Add node_name field to NodeExecutionState
- Set node_name in execute_workflow from node.name
- Display priority: node_name > debug_prompt_slug > node_label > node_id
User sees 'Qualitätseinschätzung' instead of 'node_abc123'
- workflow_executor.py: Store prompt_slug or generated label in debug_prompt_slug for all nodes
- This makes it easy to identify nodes in the debug panel
- Example: 'wf_nutrition_basis' instead of 'node_5'
- Helps identify which node is which when debugging workflows
Backend changes:
- workflow_models.py: Add debug_prompt, debug_raw_response, debug_node_type, debug_prompt_slug, metadata fields to NodeExecutionState
- workflow_executor.py: Capture and store debug info for analysis, logic, and join nodes when enable_debug=True
- Analysis nodes: store full prompt + raw AI response
- Logic nodes: store expression + evaluation result
- Join nodes: store strategy + path statistics
Frontend changes:
- Analysis.jsx: Enable debug mode by default (debug=true) for all workflow executions
This allows developers to see exactly what prompt was sent to the AI, what response was received, and how each node was processed - essential for debugging workflow issues.
- workflow_executor.py: Generate node_label from prompt_slug or node.type (WorkflowNode has no label attribute)
- prompts.py: Fix INSERT statement - use 'created' column instead of 'created_at'
SSE endpoint now works correctly for workflow execution streaming.
Backend:
- workflow_executor.py: Add progress_callback parameter, emit events for execution_started, node_complete, execution_complete, execution_failed
- prompt_executor.py: Thread progress_callback through execute chain
- routers/prompts.py: New /execute-stream endpoint with asyncio Queue for SSE
Frontend:
- utils/api.js: New executeUnifiedPromptStream() function with EventSource
- pages/Analysis.jsx: Use SSE with live progress display (X/Y Nodes)
Fixes:
- No more gateway timeouts for complex workflows (10+ nodes)
- Live progress feedback for users
- Unlimited workflow complexity
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Bug: debug=true in URL was ignored because FastAPI expected it in
request body (POST without Query() expects body params by default).
Result: node_states were never returned, even with ?debug=true
Fix: Changed debug and save to Query parameters:
- debug: bool = Query(False, ...)
- save: bool = Query(False, ...)
Now ?debug=true in URL correctly enables debug output with node_states.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Root cause: UI saves LogicExpression directly as condition:
{operands: [...], operator: "and"}
But Pydantic model expected Condition with wrapped expression:
{expression: {operands: [...], operator: "and"}}
Result: Pydantic deserialized it as Condition with expression=None
→ Logic-Nodes failed with "'NoneType' object has no attribute 'operator'"
Fix:
1. Changed WorkflowNode.condition type from Condition to Any
2. Executor now handles both dict and Pydantic model formats
3. Detects UI format (operator+operands) vs legacy format (expression wrapper)
4. Converts dict to LogicExpression before evaluation
Fixes: Logic-Node execution failures in Training-Tiefenanalyse workflow
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Previous fix handled hasattr() but didn't check for None values.
Now explicitly checks that operator/expression is not None before using it.
Error was: "'NoneType' object has no attribute 'operator'"
Clearer error message: "condition is None or missing"
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Logic-Nodes were timing out because UI saves condition as:
{operands: [...], operator: "and"}
But Backend expected:
{expression: {operands: [...], operator: "and"}}
This caused node.condition.expression to be None, triggering:
- Logic-Node failures
- Join-Node wait_all timeout
- 504 Gateway Timeout
Fix: Accept both formats by checking for operator/operands attributes
directly on condition, falling back to condition.expression.
Fixes: 504 Gateway Timeout in Training-Tiefenanalyse workflow
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Problem: Logic nodes without logic_expression defined caused AttributeError
"'NoneType' object has no attribute 'operator'" when evaluating condition.
Solution: Check both node.condition AND node.condition.expression before
calling evaluate_logic_expression(). Return clear FAILED state with error
message instead of crashing.
Impact: Workflows with incomplete logic node definitions now fail gracefully
with clear error message instead of cryptic AttributeError.
Problem: Parser converted question IDs to lowercase ('qAnalyst' → 'qanalyst'),
causing normalization to fail because id_catalog lookup is case-sensitive.
Impact: All workflow question signals were lost - normalized_signals stayed empty,
so template placeholders like {{node_2.signal_qAnalyst}} remained unresolved.
Solution: Removed .lower() call in parse_decision_questions() to preserve
original case from AI response.
Root cause: Line 162 in result_container_parser.py
Fixes: Question augmentation signals not appearing in workflow end nodes
Problem: Workflows executed via /api/prompts/execute (not /api/workflows/execute)
were passing call_openrouter directly to execute_prompt_with_data, which then
passes it to workflow_executor. workflow_executor expects (prompt, model) signature
but call_openrouter has (prompt, max_tokens=4096) signature.
Previous fix in workflows.py was correct but unused - workflows use prompts.py endpoint.
Solution: Added workflow_llm_call() wrapper in execute_unified_prompt() endpoint
that matches expected (prompt, model) -> str signature.
Related: cb3aa48 (workflows.py fix for different endpoint)
Problem: workflow_executor calls openrouter_call_func(prompt, model) but
call_openrouter expects (prompt, max_tokens=4096). This caused the model string
'anthropic/claude-sonnet-4' to be passed as max_tokens, resulting in OpenRouter
requesting 64000 tokens and failing with 402 credit errors.
Solution: Added workflow_llm_call() wrapper in workflows.py that matches the
expected (prompt, model) -> str signature and calls call_openrouter correctly.
Fixes: All workflows failing with 402 'insufficient credits' errors
- Increased the maximum token limit in the `call_openrouter` function from 1500 to 4096 to allow for more extensive responses.
- Implemented robust error handling for API requests, including timeout and request errors, with detailed HTTP exceptions for better debugging.
- Improved JSON response handling to ensure valid data is returned, with specific error messages for missing content in the response.
- Enhanced the overall reliability of the OpenRouter API integration, providing clearer feedback for users in case of issues.
These changes improve the user experience by ensuring more comprehensive responses and clearer error reporting during API interactions.
- Updated the `_parse_float_auto` function in `type_converter.py` to better handle various decimal and thousand separators, particularly for cases with long decimal parts from sources like Apple Health.
- Enhanced the logic for splitting and processing numeric strings to ensure correct interpretation of values, including edge cases with multiple separators.
- Added handling for cases where numeric strings may contain both commas and periods, improving overall robustness in float parsing.
These changes enhance the accuracy of numeric conversions, ensuring more reliable data processing across the application.
