bd4b956e3c
klausur-service (11 files): - cv_gutter_repair, ocr_pipeline_regression, upload_api - ocr_pipeline_sessions, smart_spell, nru_worksheet_generator - ocr_pipeline_overlays, mail/aggregator, zeugnis_api - cv_syllable_detect, self_rag backend-lehrer (17 files): - classroom_engine/suggestions, generators/quiz_generator - worksheets_api, llm_gateway/comparison, state_engine_api - classroom/models (→ 4 submodules), services/file_processor - alerts_agent/api/wizard+digests+routes, content_generators/pdf - classroom/routes/sessions, llm_gateway/inference - classroom_engine/analytics, auth/keycloak_auth - alerts_agent/processing/rule_engine, ai_processor/print_versions agent-core (5 files): - brain/memory_store, brain/knowledge_graph, brain/context_manager - orchestrator/supervisor, sessions/session_manager admin-lehrer (5 components): - GridOverlay, StepGridReview, DevOpsPipelineSidebar - DataFlowDiagram, sbom/wizard/page website (2 files): - DependencyMap, lehrer/abitur-archiv Other: nibis_ingestion, grid_detection_service, export-doclayout-onnx Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
112 lines
2.8 KiB
Python
112 lines
2.8 KiB
Python
"""
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Request/Response Schemas fuer Alerts Agent API.
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"""
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from datetime import datetime
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from typing import Optional
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from pydantic import BaseModel, Field
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# ============================================================================
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# Request Models
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# ============================================================================
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class AlertIngestRequest(BaseModel):
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"""Request fuer manuelles Alert-Import."""
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title: str = Field(..., min_length=1, max_length=500)
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url: str = Field(..., min_length=1)
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snippet: Optional[str] = Field(default=None, max_length=2000)
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topic_label: str = Field(default="Manual Import")
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published_at: Optional[datetime] = None
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class AlertRunRequest(BaseModel):
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"""Request fuer Scoring-Pipeline."""
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limit: int = Field(default=50, ge=1, le=200)
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skip_scored: bool = Field(default=True)
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class FeedbackRequest(BaseModel):
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"""Request fuer Relevanz-Feedback."""
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alert_id: str
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is_relevant: bool
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reason: Optional[str] = None
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tags: list[str] = Field(default_factory=list)
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class ProfilePriorityRequest(BaseModel):
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"""Priority fuer Profile-Update."""
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label: str
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weight: float = Field(default=0.5, ge=0.0, le=1.0)
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keywords: list[str] = Field(default_factory=list)
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description: Optional[str] = None
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class ProfileUpdateRequest(BaseModel):
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"""Request fuer Profile-Update."""
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priorities: Optional[list[ProfilePriorityRequest]] = None
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exclusions: Optional[list[str]] = None
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policies: Optional[dict] = None
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# ============================================================================
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# Response Models
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# ============================================================================
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class AlertIngestResponse(BaseModel):
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"""Response fuer Alert-Import."""
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id: str
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status: str
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message: str
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class AlertRunResponse(BaseModel):
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"""Response fuer Scoring-Pipeline."""
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processed: int
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keep: int
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drop: int
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review: int
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errors: int
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duration_ms: int
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class InboxItem(BaseModel):
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"""Ein Item in der Inbox."""
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id: str
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title: str
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url: str
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snippet: Optional[str]
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topic_label: str
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published_at: Optional[datetime]
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relevance_score: Optional[float]
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relevance_decision: Optional[str]
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relevance_summary: Optional[str]
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status: str
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class InboxResponse(BaseModel):
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"""Response fuer Inbox-Abfrage."""
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items: list[InboxItem]
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total: int
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page: int
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page_size: int
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class FeedbackResponse(BaseModel):
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"""Response fuer Feedback."""
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success: bool
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message: str
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profile_updated: bool
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class ProfileResponse(BaseModel):
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"""Response fuer Profile."""
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id: str
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priorities: list[dict]
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exclusions: list[str]
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policies: dict
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total_scored: int
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total_kept: int
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total_dropped: int
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accuracy_estimate: Optional[float]
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