4211e587ee
- Add qa_models.py with TextQAItem, GenTextQARequest, QAPair, ImageQAItem, GenImageQARequest, ImageQAPair, TextQAResponse, ImageQAResponse - Implement gen_text_qa(): batch-formats triples into a single prompt, calls llm.chat(), parses JSON array via extract_json() - Implement gen_image_qa(): downloads cropped image from source-data bucket, base64-encodes inline (data URI), builds multimodal message, calls llm.chat_vision(), parses JSON; image_path preserved on ImageQAPair - Replace qa.py stub with full router: POST /qa/gen-text and /qa/gen-image using Depends(get_llm_client) and Depends(get_storage_client) - 15 new tests (8 service + 7 router), 53/53 total passing
48 lines
822 B
Python
48 lines
822 B
Python
from pydantic import BaseModel
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class TextQAItem(BaseModel):
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subject: str
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predicate: str
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object: str
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source_snippet: str
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class GenTextQARequest(BaseModel):
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items: list[TextQAItem]
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model: str | None = None
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prompt_template: str | None = None
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class QAPair(BaseModel):
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question: str
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answer: str
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class ImageQAItem(BaseModel):
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subject: str
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predicate: str
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object: str
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qualifier: str | None = None
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cropped_image_path: str
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class GenImageQARequest(BaseModel):
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items: list[ImageQAItem]
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model: str | None = None
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prompt_template: str | None = None
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class ImageQAPair(BaseModel):
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question: str
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answer: str
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image_path: str
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class TextQAResponse(BaseModel):
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pairs: list[QAPair]
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class ImageQAResponse(BaseModel):
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pairs: list[ImageQAPair]
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