Lars/mitai-jinkendo
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Author SHA1 Message Date
Lars
e2a132353d feat: Phase 4 - Join Nodes and Path Consolidation
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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
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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
16dc08cd7d test: Add regression test for hybrid model - node spectrum overrides catalog
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2026-04-03 21:55:19 +02:00
Lars
1f8791f4dd feat: Phase 2 - Normalisierung + Workflow Executor
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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
Lars
ca562b7130 feat: Phase 1 - Fragenergänzung + Strukturierter Container
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Backend:
- question_augmenter.py (290 Zeilen): Hybrid-Modell für Fragenergänzungen
  * merge_question_augmentations(): Knotengebundene Fragen überschreiben Prompt-Defaults
  * augment_prompt_with_questions(): Markdown-formatierte Fragenergänzung
  * parse_question_augmentations_from_jsonb(): JSONB → QuestionAugmentation[]
- result_container_parser.py (250 Zeilen): Markdown-Sektionen-Parsing
  * parse_result_container(): Extrahiert Analysekern, Entscheidungsanteil, Begründungsanker
  * validate_decision_signal(): Normalisierung gegen answer_spectrum
  * Fallback-Parsing bei unstrukturierten Antworten
- routers/workflow_questions.py (236 Zeilen): CRUD für workflow_question_catalog
  * GET /api/workflow/questions (mit active_only Filter)
  * POST/PUT/DELETE (Admin only, Soft Delete)
- prompt_executor.py: Integration in execute_base_prompt()
  * Fragenergänzung vor LLM-Call (wenn node_questions oder catalog vorhanden)
  * Result-Container-Parsing nach LLM-Response
- main.py: Router-Registrierung (workflow_questions)

Tests:
- test_phase1_question_augmenter.py (8 Tests): Hybrid-Modell, Formatierung, JSONB-Parsing
- test_phase1_result_container_parser.py (17 Tests): Sektion-Extraktion, Decision-Parsing, Validierung

Alle 25 Unit-Tests bestanden.

version: 0.9j (backend)
module:  workflow 0.2.0

Konzept: .claude/task/Workflow_engine_prompting_engine/konzept_workflow_engine_konsolidated.md (Phase 1)
 2026-04-03 18:02:25 +02:00
Lars
b5be6e21a5 feat: Phase 0 - Workflow Engine Foundation
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Backend:
- DB-Migration 034: workflow_definitions, workflow_question_catalog, workflow_executions
- ai_prompts.question_augmentations JSONB-Spalte (Hybridmodell: Prompt-Defaults)
- 6 Grundtypen Fragenergänzungen mit Normalisierungsregeln (Seed-Daten)
- Pydantic-Modelle (16 Models, 11 Enums) in workflow_models.py
- Workflow-Engine: Graph-Parsing, Topologische Sortierung, DAG-Validierung
- Dispatcher-Erweiterung type='workflow' (Stub für Phase 1-3)
- Adjacency Lists, Erreichbarkeits-Prüfungen, Zyklen-Erkennung

Testing:
- 22 Unit-Tests (alle bestanden): Graph-Parsing, Validierung, Topologische Sortierung
- Fixtures: simple_valid_graph, parallel_graph, branching_graph

Version:
- APP_VERSION 0.9i
- DB_SCHEMA_VERSION 20260403
- Module: workflow 0.1.0

Anforderungsanalyse: .claude/task/Workflow_engine_prompting_engine/anforderungsanalyse_umsetzungsplan.md
Konzept-Basis: .claude/task/Workflow_engine_prompting_engine/konzept_workflow_engine_konsolidated.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-03 16:55:51 +02:00