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e2a132353d
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feat: Phase 4 - Join Nodes and Path Consolidation
Deploy Development / deploy (push) Successful in 45s
Build Test / lint-backend (push) Successful in 0s
Build Test / build-frontend (push) Successful in 13s
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>
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2026-04-04 12:27:31 +02:00 |
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2ce0874dcb
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feat: Phase 3 - Logic Nodes + Conditional Branching
Deploy Development / deploy (push) Successful in 50s
Build Test / lint-backend (push) Successful in 0s
Build Test / build-frontend (push) Successful in 14s
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>
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2026-04-04 08:02:22 +02:00 |
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1f8791f4dd
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feat: Phase 2 - Normalisierung + Workflow Executor
Deploy Development / deploy (push) Successful in 44s
Build Test / lint-backend (push) Successful in 0s
Build Test / build-frontend (push) Successful in 14s
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)
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2026-04-03 21:20:23 +02:00 |
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