34da9f4cda
backend-lehrer (11 files): - llm_gateway/routes/schools.py (867 → 5), recording_api.py (848 → 6) - messenger_api.py (840 → 5), print_generator.py (824 → 5) - unit_analytics_api.py (751 → 5), classroom/routes/context.py (726 → 4) - llm_gateway/routes/edu_search_seeds.py (710 → 4) klausur-service (12 files): - ocr_labeling_api.py (845 → 4), metrics_db.py (833 → 4) - legal_corpus_api.py (790 → 4), page_crop.py (758 → 3) - mail/ai_service.py (747 → 4), github_crawler.py (767 → 3) - trocr_service.py (730 → 4), full_compliance_pipeline.py (723 → 4) - dsfa_rag_api.py (715 → 4), ocr_pipeline_auto.py (705 → 4) website (6 pages): - audit-checklist (867 → 8), content (806 → 6) - screen-flow (790 → 4), scraper (789 → 5) - zeugnisse (776 → 5), modules (745 → 4) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
138 lines
3.3 KiB
Python
138 lines
3.3 KiB
Python
"""
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DSFA RAG Pydantic Models.
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Request/Response models for the DSFA RAG API.
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"""
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from typing import List, Optional
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from pydantic import BaseModel, Field
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# =============================================================================
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# Response Models
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# =============================================================================
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class DSFASourceResponse(BaseModel):
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"""Response model for DSFA source."""
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id: str
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source_code: str
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name: str
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full_name: Optional[str] = None
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organization: Optional[str] = None
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source_url: Optional[str] = None
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license_code: str
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license_name: str
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license_url: Optional[str] = None
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attribution_required: bool
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attribution_text: str
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document_type: Optional[str] = None
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language: str = "de"
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class DSFAChunkResponse(BaseModel):
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"""Response model for a single chunk with attribution."""
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chunk_id: str
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content: str
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section_title: Optional[str] = None
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page_number: Optional[int] = None
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category: Optional[str] = None
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# Document info
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document_id: str
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document_title: Optional[str] = None
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# Attribution (always included)
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source_id: str
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source_code: str
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source_name: str
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attribution_text: str
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license_code: str
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license_name: str
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license_url: Optional[str] = None
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attribution_required: bool
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source_url: Optional[str] = None
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document_type: Optional[str] = None
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class DSFASearchResultResponse(BaseModel):
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"""Response model for search result."""
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chunk_id: str
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content: str
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score: float
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# Attribution
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source_code: str
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source_name: str
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attribution_text: str
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license_code: str
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license_name: str
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license_url: Optional[str] = None
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attribution_required: bool
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source_url: Optional[str] = None
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# Metadata
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document_type: Optional[str] = None
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category: Optional[str] = None
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section_title: Optional[str] = None
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page_number: Optional[int] = None
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class DSFASearchResponse(BaseModel):
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"""Response model for search endpoint."""
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query: str
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results: List[DSFASearchResultResponse]
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total_results: int
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# Aggregated licenses for footer
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licenses_used: List[str]
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attribution_notice: str
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class DSFASourceStatsResponse(BaseModel):
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"""Response model for source statistics."""
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source_id: str
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source_code: str
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name: str
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organization: Optional[str] = None
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license_code: str
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document_type: Optional[str] = None
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document_count: int
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chunk_count: int
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last_indexed_at: Optional[str] = None
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class DSFACorpusStatsResponse(BaseModel):
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"""Response model for corpus statistics."""
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sources: List[DSFASourceStatsResponse]
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total_sources: int
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total_documents: int
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total_chunks: int
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qdrant_collection: str
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qdrant_points_count: int
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qdrant_status: str
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class IngestRequest(BaseModel):
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"""Request model for ingestion."""
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document_url: Optional[str] = None
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document_text: Optional[str] = None
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title: Optional[str] = None
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class IngestResponse(BaseModel):
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"""Response model for ingestion."""
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source_code: str
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document_id: Optional[str] = None
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chunks_created: int
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message: str
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class LicenseInfo(BaseModel):
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"""License information."""
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code: str
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name: str
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url: Optional[str] = None
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attribution_required: bool
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modification_allowed: bool
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commercial_use: bool
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