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Trenton HandGitHub
0e5fbc973a
AI Suggestions previously invented near-duplicate metadata because the classification prompt had no knowledge of the installation's own taxonomy. This surfaces a small, ranked, permission-filtered set of existing tags/document types/correspondents/storage paths - drawn from the document's RAG neighbors plus its own already-assigned metadata - so the model prefers reusing what already exists. The LLM response schema now returns existing_ids (IDs of reused candidates) separately from new_names (genuinely new suggestions). Only new_names goes through localization and fuzzy name-matching; existing_ids is resolved deterministically and never touched by the localization pass, so exact matches can no longer be silently corrupted by translation.
52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
from typing import TypedDict
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from pydantic import BaseModel
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from pydantic import Field
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class TaxonomyChoice(BaseModel):
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"""One taxonomy category's suggestions: IDs the model matched to a
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candidate it was shown in the prompt, plus names for values it believes
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are genuinely new. existing_ids are never localized - only new_names is.
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Pydantic enforces this shape on whatever the LLM returns; the rest of the
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pipeline passes the `.model_dump()`-ed plain dict around, typed as
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TaxonomyChoiceDict below.
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"""
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existing_ids: list[int] = Field(default_factory=list)
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new_names: list[str] = Field(default_factory=list)
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class DocumentClassifierSchema(BaseModel):
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"""Schema for document classification suggestions."""
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title: str
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tags: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
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correspondents: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
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document_types: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
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storage_paths: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
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dates: list[str] = Field(default_factory=list)
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class TaxonomyChoiceDict(TypedDict):
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"""Plain-dict counterpart of TaxonomyChoice - what
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TaxonomyChoice.model_dump() actually produces, typed for callers that
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work with the dumped dict rather than the pydantic instance."""
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existing_ids: list[int]
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new_names: list[str]
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class ClassificationSuggestions(TypedDict):
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"""Plain-dict counterpart of DocumentClassifierSchema.model_dump() -
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the shape threaded through parse_ai_response, build_localization_prompt,
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get_ai_document_classification, and the ai_suggestions view."""
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title: str
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tags: TaxonomyChoiceDict
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correspondents: TaxonomyChoiceDict
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document_types: TaxonomyChoiceDict
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storage_paths: TaxonomyChoiceDict
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dates: list[str]
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