15 Commits

Author	SHA1	Message	Date
Lars	b17bec3340	fix: Load base prompt questions in workflow (Hybrid Model) ... Backend workflow_executor.py: - New function: load_prompt_questions() loads questions from base prompt - execute_node() now implements Hybrid Model correctly: * IF node has question_augmentations → use those (override) * ELSE load questions from referenced base prompt (fallback) - Normalization now uses `questions` variable (not node.question_augmentations) - This fixes base prompts having questions that were ignored in workflows Root Cause: - Phase 1 Hybrid Model was incomplete - Node-specific questions worked, but base prompt questions were ignored - augment_prompt_with_questions() was only called when node.question_augmentations existed Impact: - Analysis Nodes WITHOUT custom questions now use base prompt questions - LLM receives proper question augmentation - Decision signals are generated and normalized correctly Issue: Workflow questions not sent to LLM Version: 0.9p (workflow module) Part 3: End Node Template Engine - Critical Fix Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-09 18:18:08 +02:00
Lars	857c55aeb8	fix: Workflow placeholder resolution + complete catalog display ... Backend workflow_executor.py: - load_prompt_template() now uses modern resolve_placeholders() from prompt_executor - Calls get_placeholder_example_values() to populate ALL registered placeholders - Passes catalog for |d modifier support - Fixes issue where basis prompts had empty/null placeholder values in workflows Backend placeholder_resolver.py: - get_placeholder_catalog() now includes ALL placeholders from PLACEHOLDER_MAP - Uncategorized placeholders added to "Sonstiges" category - Fixes discrepancy: 111 total placeholders but only ~30 shown in picker Root Cause: - Workflow used old resolve_placeholders() (only PLACEHOLDER_MAP, no variables) - Isolated execution used modern resolve_placeholders() (full variables dict) - Catalog excluded non-registry placeholders from PLACEHOLDER_MAP Impact: - All placeholders now resolve correctly in workflow execution - PlaceholderPicker shows all 111+ placeholders (not just registry ones) Version: 0.9p (workflow module) Part 3: End Node Template Engine - Bug Fixes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-09 18:10:04 +02:00
Lars	fac76c28da	fix: Handle None workflow_id in success path ... Also use 'N/A' placeholder in ExecutionResult when workflow_id is None (when using graph_data directly instead of workflow_definitions). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-05 07:28:30 +02:00
Lars	6016eec250	fix: Add ON CONFLICT to workflow_executions insert ... Prevents duplicate key violation when save_execution_state is called multiple times with the same execution_id (e.g., during error handling). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-05 07:26:10 +02:00
Lars	c95b4e185d	fix: Edge format normalization and nullable workflow_id ... Fixes: 1. Edge Format Mismatch: - graph_data uses React Flow format (source/target) - WorkflowEdge expects backend format (from/to) - Added normalization in parse_workflow_graph() 2. UUID Validation Error: - workflow_id can be None when using graph_data (Phase 5) - save_execution_state now accepts Optional[str] - ExecutionResult uses "N/A" placeholder when None Changes: - workflow_engine.py: normalize edges before Pydantic validation - workflow_executor.py: Optional[str] for workflow_id parameter Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-05 07:22:32 +02:00
Lars	fe28cce921	fix: Workflow executor graph parsing and error handling ... Fixes: - graph_data was incorrectly json.dumps() encoded (should stay as dict) - workflow_id=None in error handler caused ValidationError - parse_workflow_graph expects Dict, not str Changes: - Use graph_dict directly instead of json.dumps(graph_data) - Set workflow_id="" when None in error handler Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-05 07:18:43 +02:00
Lars	b888f5d3c8	feat: Phase 4 - End Node Template Engine (v0.9n) ... Backend: - workflow_models.py: EndNodeOutputMode enum (AUTO, TEMPLATE) - workflow_executor.py: execute_end_node() with Jinja2 rendering - Template Context: {{node_id.analysis_core}}, {{node_id.decision_signals.key}} - Conditional Rendering: {% if node_id %} for optional paths - AUTO Mode: Backward compatible (concatenates all analyses) - TEMPLATE Mode: Custom Jinja2 templates with placeholders Features: - Access node results: {{node_id.analysis_core}} - Access signals: {{node_id.decision_signals.relevanz}} - Optional paths: {% if node_id %}...{% endif %} - Default values: {{node_id|default("N/A")}} Version: 0.9n Module: workflow 0.6.0 Konzept: konzept_workflow_engine_konsolidated.md (Section 11) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-05 07:07:49 +02:00
Lars	dc59596f01	feat: Phase 5 - Visual Workflow Editor (Option B) ... Backend (Mini-Backend 1-2h): - Migration 016: ai_prompts.graph_data JSONB column - workflow_executor: graph_data parameter support (backward-compatible) - prompt_executor: execute_workflow_prompt uses graph_data Frontend (Main effort 25-35h): - WorkflowCanvas: React Flow wrapper component - 5 Custom Nodes: Start, End, Analysis, Logic, Join - 4 Config Panels: QuestionAugmentation, LogicExpression, Fallback, Join - workflowValidation: Structural + logical validation - workflowSerializer: Canvas ↔ JSONB conversion - WorkflowEditorPage: Main orchestration (420 LOC) - Route: /workflow-editor/:id - CSS: workflowEditor.css (300 LOC) Architecture: - Option B: ai_prompts.type='workflow' (not separate table) - panels/ subdirectory for clean separation - WorkflowCanvas reusable component - User GUI identical (Workflows = Prompts) - Backward-compatible (type='pipeline' unchanged) Version: v0.9m → v0.9n (Phase 5 complete) Module: workflow 0.5.0 → 0.6.0 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-04 17:56:00 +02:00
Lars	c607cd1833	fix: Convert joined signals Dict to List for NodeExecutionState ... NodeExecutionState expects normalized_signals as List[NormalizedSignal], but join_evaluator returns Dict[str, NormalizedSignal]. Fix: Convert dict to list before returning NodeExecutionState. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-04 12:33:58 +02:00
Lars	e2a132353d	feat: Phase 4 - Join Nodes and Path Consolidation ... Backend Implementation (v0.9m, workflow 0.5.0): - join_evaluator.py (394 lines): Join-Strategie-Evaluator - evaluate_join_node(): Hauptlogik für Join-Node Execution - Join-Strategien: wait_all, wait_any, best_effort - Skip-Handling: ignore_skipped, use_placeholder, require_minimum - Result Consolidation: merge analysis_cores, combine signals - Partial Execution: korrekte Behandlung von SKIPPED/FAILED Pfaden - workflow_executor.py: execute_join_node() Integration - BFS-Traversierung erweitert für Join-Nodes - NodeExecutionState List → Dict Konvertierung für Signale - Signal-Name-Kollisionen via node_id Präfix gelöst Testing (49 Tests passing): - test_phase4_join_nodes.py: 18 neue Unit Tests - Join-Strategien (wait_all, wait_any, best_effort) - Skip-Handling (ignore, placeholder) - Result Consolidation (merge, combine) - Partial Execution (mixed status paths) - Helper Functions (collect, check, merge, combine) - Backward Compatibility: 31 Phase 2/3 Tests (alle passing) - test_phase2_workflow_executor.py: 1 Test aktualisiert - test_phase3_logic_evaluator.py: 20 Tests unverändert Konzept: konzept_workflow_engine_konsolidated.md (Sektion 8.8) Anforderungsanalyse: phase4_anforderungsanalyse.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-04 12:27:31 +02:00
Lars	2ce0874dcb	feat: Phase 3 - Logic Nodes + Conditional Branching ... Backend: - logic_evaluator.py (NEU, 307 Zeilen): Deterministischer Logic Evaluator - Vergleichsoperatoren: EQ, NEQ, IN, NOT_IN, GT, LT, GTE, LTE, CONTAINS - Logische Operatoren: AND, OR, NOT mit Verschachtelung - Resolve signal references (node_id.question_type) - Error handling für UNCLEAR/INVALID/NOT_DECIDABLE Signale - workflow_executor.py (ERWEITERT): - execute_logic_node(): Bedingungen evaluieren, Pfade aktivieren/deaktivieren - execute_workflow(): BFS-Traversierung mit Edge-Activation statt Sequential - _apply_fallback(): 4 Fallback-Strategien (CONSERVATIVE_SKIP, DEFAULT_PATH, UNCERTAINTY_PATH, DOCUMENT_ONLY) - _has_active_incoming_edge(): Prüft ob Node erreichbar ist - _get_edges_by_label(): Findet then/else/uncertainty Pfade - workflow_models.py (ERWEITERT): - LogicOperator.CONTAINS hinzugefügt - version.py: 0.9k → 0.9l, workflow 0.3.0 → 0.4.0 Tests: - test_phase3_logic_evaluator.py (NEU): 20 Unit Tests (alle passing) - Comparison operators (EQ, NEQ, IN, GT, LT, CONTAINS) - Logical operators (AND, OR, NOT) - Nested expressions - Error handling (missing refs, UNCLEAR/INVALID signals) - test_phase2_workflow_executor.py (AKTUALISIERT): 11 Tests (alle passing) - execute_node() graph parameter hinzugefügt (Phase 3 requirement) - test_execute_node_unknown_type: logic → join (logic jetzt implementiert) - test_phase3_workflow_branching.py (NEU): Integration Tests vorbereitet - Erfordert vollständige DB-Mock-Strategie (wird in E2E-Test nachgeholt) Phase 2 Backward Compatibility: ✅ Alle Phase 2 Tests bestehen weiterhin Konzept: .claude/task/Workflow_engine_prompting_engine/konzept_workflow_engine_konsolidated.md Anforderungsanalyse: .claude/task/Workflow_engine_prompting_engine/phase3_anforderungsanalyse.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-04 08:02:22 +02:00
Lars	c588372f3a	fix: Hybrid model - node-specific question spectrums override catalog (Phase 1 requirement)	2026-04-03 21:49:13 +02:00
Lars	585f189b13	fix: Remove extra_vars parameter from resolve_placeholders call - function doesn't support it yet	2026-04-03 21:44:39 +02:00
Lars	ac2e7cf5bb	fix: Use dict keys for all RealDictCursor row access in Phase 2 code	2026-04-03 21:36:44 +02:00
Lars	1f8791f4dd	feat: Phase 2 - Normalisierung + Workflow Executor ... Backend: - normalization_engine.py (200 Zeilen): Synonym-Mapping, 5 Statuswerte * normalize_decision_signal(): Kaskade (exact → case → synonym → invalid) * apply_synonym_mapping(): DB-basierte Synonyme (case-insensitive) * normalize_all_signals(): Batch-Processing gegen Katalog * load_question_catalog(): Lädt normalization_rules aus DB - workflow_executor.py (440 Zeilen): Sequenzielle Workflow-Ausführung * execute_workflow(): Traversiert DAG in topologischer Reihenfolge * execute_node(): Führt analysis nodes aus (start/end = no-op) * aggregate_results(): Kombiniert analysis_core + normalized_signals * save_execution_state(): Persistiert in workflow_executions - workflow_models.py: Erweitert um Phase 2 Models * SignalStatus Enum (valid, normalized, unclear, invalid, not_decidable) * NormalizedSignal (question_type, raw_value, normalized_value, status) * NodeExecutionState (node_id, status, analysis_core, normalized_signals) * ExecutionResult (execution_id, workflow_id, status, node_states, aggregated_result) - workflow_engine.py: Neue Funktion get_execution_order() * Flattened topological sort für sequenzielle Execution * Phase 7: Wird zu levels (parallele Execution) - prompt_executor.py: execute_workflow_prompt() Implementierung * Ruft workflow_executor.execute_workflow() auf * Konvertiert ExecutionResult zu API-Response - routers/workflows.py (230 Zeilen): Workflow Execution API * POST /api/workflows/{id}/execute (mit enable_debug) * GET /api/workflows/executions/{id} (lädt gespeicherten State) * GET /api/workflows (listet alle aktiven Workflows) * GET /api/workflows/{id} (lädt einzelnen Workflow mit Graph) - main.py: Router-Registrierung (workflows.router) Tests: - test_phase2_normalization.py (17 Tests): Alle Normalisierungs-Szenarien * Exact match, case-insensitive, synonym mapping, invalid, whitespace * Batch-Normalisierung, not_in_catalog, mixed validity - test_phase2_workflow_executor.py (10 Tests): Executor + Aggregation * aggregate_results mit verschiedenen Konstellationen * execute_node für start/end/analysis/unknown * Integration mit question_augmenter + result_container_parser Alle 27 Unit-Tests bestanden. version: 0.9k (backend) module: workflow 0.3.0 Konzept: .claude/task/Workflow_engine_prompting_engine/anforderungsanalyse_umsetzungsplan.md (Phase 2)	2026-04-03 21:20:23 +02:00