5c1744d3a4
- 6.1-6.2: Entity visualization components (bar chart, pie chart, timeline) [in LysnrAI repo] - 6.3-6.4: Async job queue — POST /extract/jobs, GET /extract/jobs/:id, GET /extract/jobs - 6.5-6.6: Model registry with tier (standard/premium/free/mock) + GET /extract/models - 6.7-6.8: Multi-language detection (es/fr/de/pt/ja/zh/ko/ar) + prompt enrichment - ExtractMetadata.language field added to Python models - 46 TS tests passing, build clean
54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
"""
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Pydantic models for the extraction sidecar API.
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These mirror the Zod schemas in the TypeScript service.
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"""
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from __future__ import annotations
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from pydantic import BaseModel, Field
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class Extraction(BaseModel):
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extraction_class: str
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extraction_text: str
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attributes: dict[str, str] | None = None
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class ExtractionExample(BaseModel):
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text: str
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extractions: list[Extraction]
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class ExtractRequest(BaseModel):
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text: str = Field(..., min_length=1, max_length=50_000)
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task_id: str | None = None
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task_prompt: str | None = None
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examples: list[ExtractionExample] | None = None
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model_id: str | None = None
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extraction_passes: int | None = Field(None, ge=1, le=5)
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max_workers: int | None = Field(None, ge=1, le=50)
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max_char_buffer: int | None = Field(None, ge=100, le=10_000)
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class BatchExtractRequest(BaseModel):
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requests: list[ExtractRequest] = Field(..., min_length=1, max_length=50)
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class ExtractMetadata(BaseModel):
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model_id: str
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duration_ms: float
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token_count: int | None = None
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char_count: int
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language: str | None = None
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class ExtractResponse(BaseModel):
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extractions: list[Extraction]
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metadata: ExtractMetadata
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class HealthResponse(BaseModel):
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status: str = "ok"
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version: str = "0.1.0"
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sidecar: str = "langextract"
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