[split-required] Split 500-850 LOC files (batch 2)
backend-lehrer (10 files): - game/database.py (785 → 5), correction_api.py (683 → 4) - classroom_engine/antizipation.py (676 → 5) - llm_gateway schools/edu_search already done in prior batch klausur-service (12 files): - orientation_crop_api.py (694 → 5), pdf_export.py (677 → 4) - zeugnis_crawler.py (676 → 5), grid_editor_api.py (671 → 5) - eh_templates.py (658 → 5), mail/api.py (651 → 5) - qdrant_service.py (638 → 5), training_api.py (625 → 4) website (6 pages): - middleware (696 → 8), mail (733 → 6), consent (628 → 8) - compliance/risks (622 → 5), export (502 → 5), brandbook (629 → 7) studio-v2 (3 components): - B2BMigrationWizard (848 → 3), CleanupPanel (765 → 2) - dashboard-experimental (739 → 2) admin-lehrer (4 files): - uebersetzungen (769 → 4), manager (670 → 2) - ChunkBrowserQA (675 → 6), dsfa/page (674 → 5) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
303
klausur-service/backend/training_routes.py
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303
klausur-service/backend/training_routes.py
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"""
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Training API — FastAPI route handlers.
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"""
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import uuid
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from datetime import datetime
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from typing import List
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from fastapi import APIRouter, HTTPException, BackgroundTasks, Request
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from fastapi.responses import StreamingResponse
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from training_models import (
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TrainingStatus,
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TrainingConfig,
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_state,
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)
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from training_simulation import (
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simulate_training_progress,
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training_metrics_generator,
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batch_ocr_progress_generator,
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)
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router = APIRouter(prefix="/api/v1/admin/training", tags=["Training"])
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# ============================================================================
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# TRAINING JOBS
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# ============================================================================
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@router.get("/jobs", response_model=List[dict])
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async def list_training_jobs():
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"""Get all training jobs."""
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return list(_state.jobs.values())
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@router.get("/jobs/{job_id}", response_model=dict)
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async def get_training_job(job_id: str):
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"""Get details for a specific training job."""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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return _state.jobs[job_id]
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@router.post("/jobs", response_model=dict)
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async def create_training_job(config: TrainingConfig, background_tasks: BackgroundTasks):
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"""Create and start a new training job."""
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# Check if there's already an active job
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if _state.active_job_id:
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active_job = _state.jobs.get(_state.active_job_id)
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if active_job and active_job["status"] in [
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TrainingStatus.TRAINING.value,
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TrainingStatus.PREPARING.value,
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]:
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raise HTTPException(
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status_code=409,
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detail="Another training job is already running"
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)
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# Create job
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job_id = str(uuid.uuid4())
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job = {
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"id": job_id,
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"name": config.name,
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"model_type": config.model_type.value,
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"status": TrainingStatus.QUEUED.value,
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"progress": 0,
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"current_epoch": 0,
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"total_epochs": config.epochs,
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"loss": 1.0,
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"val_loss": 1.0,
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"learning_rate": config.learning_rate,
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"documents_processed": 0,
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"total_documents": len(config.bundeslaender) * 50, # Estimate
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"started_at": None,
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"estimated_completion": None,
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"completed_at": None,
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"error_message": None,
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"metrics": {
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"precision": 0.0,
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"recall": 0.0,
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"f1_score": 0.0,
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"accuracy": 0.0,
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"loss_history": [],
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"val_loss_history": [],
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},
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"config": config.dict(),
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}
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_state.jobs[job_id] = job
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_state.active_job_id = job_id
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# Start training in background
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background_tasks.add_task(simulate_training_progress, job_id)
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return {"id": job_id, "status": "queued", "message": "Training job created"}
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@router.post("/jobs/{job_id}/pause", response_model=dict)
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async def pause_training_job(job_id: str):
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"""Pause a running training job."""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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job = _state.jobs[job_id]
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if job["status"] != TrainingStatus.TRAINING.value:
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raise HTTPException(status_code=400, detail="Job is not running")
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job["status"] = TrainingStatus.PAUSED.value
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return {"success": True, "message": "Training paused"}
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@router.post("/jobs/{job_id}/resume", response_model=dict)
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async def resume_training_job(job_id: str, background_tasks: BackgroundTasks):
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"""Resume a paused training job."""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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job = _state.jobs[job_id]
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if job["status"] != TrainingStatus.PAUSED.value:
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raise HTTPException(status_code=400, detail="Job is not paused")
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job["status"] = TrainingStatus.TRAINING.value
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_state.active_job_id = job_id
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background_tasks.add_task(simulate_training_progress, job_id)
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return {"success": True, "message": "Training resumed"}
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@router.post("/jobs/{job_id}/cancel", response_model=dict)
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async def cancel_training_job(job_id: str):
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"""Cancel a training job."""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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job = _state.jobs[job_id]
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job["status"] = TrainingStatus.CANCELLED.value
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job["completed_at"] = datetime.now().isoformat()
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if _state.active_job_id == job_id:
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_state.active_job_id = None
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return {"success": True, "message": "Training cancelled"}
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@router.delete("/jobs/{job_id}", response_model=dict)
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async def delete_training_job(job_id: str):
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"""Delete a training job."""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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job = _state.jobs[job_id]
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if job["status"] == TrainingStatus.TRAINING.value:
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raise HTTPException(status_code=400, detail="Cannot delete running job")
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del _state.jobs[job_id]
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return {"success": True, "message": "Job deleted"}
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# ============================================================================
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# MODEL VERSIONS
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# ============================================================================
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@router.get("/models", response_model=List[dict])
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async def list_model_versions():
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"""Get all trained model versions."""
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return list(_state.model_versions.values())
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@router.get("/models/{version_id}", response_model=dict)
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async def get_model_version(version_id: str):
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"""Get details for a specific model version."""
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if version_id not in _state.model_versions:
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raise HTTPException(status_code=404, detail="Model version not found")
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return _state.model_versions[version_id]
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@router.post("/models/{version_id}/activate", response_model=dict)
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async def activate_model_version(version_id: str):
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"""Set a model version as active."""
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if version_id not in _state.model_versions:
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raise HTTPException(status_code=404, detail="Model version not found")
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# Deactivate all other versions of same type
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model = _state.model_versions[version_id]
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for v in _state.model_versions.values():
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if v["model_type"] == model["model_type"]:
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v["is_active"] = False
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model["is_active"] = True
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return {"success": True, "message": "Model activated"}
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@router.delete("/models/{version_id}", response_model=dict)
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async def delete_model_version(version_id: str):
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"""Delete a model version."""
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if version_id not in _state.model_versions:
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raise HTTPException(status_code=404, detail="Model version not found")
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model = _state.model_versions[version_id]
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if model["is_active"]:
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raise HTTPException(status_code=400, detail="Cannot delete active model")
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del _state.model_versions[version_id]
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return {"success": True, "message": "Model deleted"}
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# ============================================================================
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# DATASET STATS & STATUS
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# ============================================================================
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@router.get("/dataset/stats", response_model=dict)
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async def get_dataset_stats():
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"""Get statistics about the training dataset."""
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from metrics_db import get_zeugnis_stats
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zeugnis_stats = await get_zeugnis_stats()
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return {
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"total_documents": zeugnis_stats.get("total_documents", 0),
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"total_chunks": zeugnis_stats.get("total_documents", 0) * 12,
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"training_allowed": zeugnis_stats.get("training_allowed_documents", 0),
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"by_bundesland": {
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bl["bundesland"]: bl.get("doc_count", 0)
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for bl in zeugnis_stats.get("per_bundesland", [])
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},
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"by_doc_type": {
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"verordnung": 150,
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"schulordnung": 80,
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"handreichung": 45,
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"erlass": 30,
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},
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}
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@router.get("/status", response_model=dict)
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async def get_training_status():
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"""Get overall training system status."""
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active_job = None
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if _state.active_job_id and _state.active_job_id in _state.jobs:
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active_job = _state.jobs[_state.active_job_id]
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return {
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"is_training": _state.active_job_id is not None and active_job is not None and
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active_job["status"] == TrainingStatus.TRAINING.value,
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"active_job_id": _state.active_job_id,
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"total_jobs": len(_state.jobs),
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"completed_jobs": sum(
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1 for j in _state.jobs.values()
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if j["status"] == TrainingStatus.COMPLETED.value
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),
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"failed_jobs": sum(
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1 for j in _state.jobs.values()
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if j["status"] == TrainingStatus.FAILED.value
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),
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"model_versions": len(_state.model_versions),
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"active_models": sum(1 for m in _state.model_versions.values() if m["is_active"]),
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}
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# ============================================================================
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# SSE ENDPOINTS
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# ============================================================================
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@router.get("/metrics/stream")
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async def stream_training_metrics(job_id: str, request: Request):
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"""
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SSE endpoint for streaming training metrics.
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Streams real-time training progress for a specific job.
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"""
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if job_id not in _state.jobs:
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raise HTTPException(status_code=404, detail="Job not found")
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return StreamingResponse(
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training_metrics_generator(job_id, request),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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)
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@router.get("/ocr/stream")
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async def stream_batch_ocr(images_count: int, request: Request):
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"""
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SSE endpoint for streaming batch OCR progress.
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Simulates batch OCR processing with progress updates.
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"""
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if images_count < 1 or images_count > 100:
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raise HTTPException(status_code=400, detail="images_count must be between 1 and 100")
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return StreamingResponse(
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batch_ocr_progress_generator(images_count, request),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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)
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