* feat: introduce hindsight-api-slim and hindsight-all-slim packages Closes #552 - Move all source code from hindsight-api/ to new hindsight-api-slim/ - hindsight-api-slim has heavy ML deps (torch, sentence-transformers, transformers, einops, flashrank, mlx, mlx-lm, safetensors) and pg0-embedded as optional extras: [local-ml], [embedded-db], [all] - hindsight-api becomes a zero-code meta-package depending on hindsight-api-slim[all] for full backward compatibility - Add hindsight-all-slim meta-package: hindsight-api-slim + client + embed - hindsight-all updated to depend on hindsight-api-slim[all] - pg0.py: lazy-import pg0 with clear ImportError pointing to [embedded-db] - Dockerfile: replace sed hack with proper uv sync --extra flags - Update release.yml, test.yml, lint.sh, release.sh, CLAUDE.md and all path references throughout the repo * refactor: rename hindsight/ directory to hindsight-all/ * docs: document hindsight-api-slim and hindsight-all-slim package variants Add package variants table and extras explanation to installation.md * docs: remove emojis from installation.md, use professional tone * docs: link Docker slim variant to pip package variants section * docs: consolidate Docker image variants into single table * ci: fix working-directory paths after package restructure - Replace all hindsight-api → hindsight-api-slim in test.yml - Replace hindsight → hindsight-all in test.yml - Add --extra embedded-db to test-embed API install step * ci: add local-ml and embedded-db extras to API sync steps These extras were previously implicit in the old hindsight-api package (which bundled everything). Now that hindsight-api-slim uses optional extras, we must explicitly request local-ml and embedded-db in CI. * ci: add API install step with embedded-db to test-embed smoke test The smoke test starts hindsight-api as a daemon, which requires pg0-embedded. Add a dedicated install step for hindsight-api-slim with embedded-db extra so the daemon can start successfully. * ci: remove --no-install-project when using optional extras When --no-install-project is combined with --extra, the optional deps are not installed because extras require the project to be active. Remove --no-install-project from steps that need local-ml or embedded-db. * ci: fix ordering of uv sync steps to preserve optional extras When uv sync runs for a different workspace member, it removes optional extras installed for other members. Fix by always running extra-requiring API sync last, after other workspace member syncs. Also remove --no-install-project from embedded-db sync in test-embed, as --no-install-project prevents optional extras from being active. * ci: add local-ml extra to test-embed API install for smoke test The smoke test starts the full API server which needs sentence-transformers for local embeddings (default provider). Add local-ml extra to the install. * ci: simplify extras with --all-extras and add slim pip smoke test - Replace explicit --extra local-ml --extra embedded-db with --all-extras for cleaner, more maintainable sync steps - Add test-pip-slim job: tests hindsight-api-slim[embedded-db] without local ML models, using Cohere for embeddings/reranking (mirrors Docker slim smoke test approach) * ci: simplify slim smoke test to health check only (mirrors Docker test)
194 lines
6.3 KiB
Python
194 lines
6.3 KiB
Python
"""
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Entity labels models and helpers for retain pipeline.
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Defines a controlled vocabulary of key:value classification labels
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(e.g., 'pedagogy:scaffolding', 'interest:active') that are extracted
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at retain time and stored as entities.
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"""
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from typing import Literal
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from pydantic import BaseModel, Field, create_model
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class LabelValue(BaseModel):
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"""A single allowed value for a label group."""
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value: str
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description: str = ""
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class LabelGroup(BaseModel):
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"""A label group (dimension) with its type and allowed values."""
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key: str
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description: str = ""
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type: Literal["value", "multi-values", "text"] = "value"
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optional: bool = True
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tag: bool = False
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values: list[LabelValue] = []
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class EntityLabelsConfig(BaseModel):
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"""Entity labels configuration for a bank (controlled vocabulary)."""
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attributes: list[LabelGroup] = []
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def parse_entity_labels(raw: dict | list | None) -> EntityLabelsConfig | None:
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"""
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Parse raw entity labels config into EntityLabelsConfig.
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Accepts:
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- None → returns None
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- list → list of attribute dicts (each may use legacy free_values/multi_value or new type field)
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- dict → {attributes: [...]}
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Legacy migration (backward-compat):
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- free_values=True → type="text"
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- multi_value=True → type="multi-values"
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- neither / free_values=False → type="value"
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Args:
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raw: Raw entity labels config from bank config
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Returns:
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EntityLabelsConfig or None if raw is None/empty
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"""
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if raw is None:
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return None
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if isinstance(raw, list):
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if not raw:
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return None
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attributes = [LabelGroup.model_validate(_migrate_label_group(a)) for a in raw]
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return EntityLabelsConfig(attributes=attributes)
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if isinstance(raw, dict):
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attrs_raw = raw.get("attributes", [])
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if not attrs_raw:
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return None
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attributes = [LabelGroup.model_validate(_migrate_label_group(a)) for a in attrs_raw]
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return EntityLabelsConfig(attributes=attributes)
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return None
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def _migrate_label_group(raw: dict) -> dict:
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"""Migrate legacy free_values/multi_value fields to the new type field."""
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if not isinstance(raw, dict) or "type" in raw:
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return raw
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patched = dict(raw)
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if patched.get("free_values"):
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patched["type"] = "text"
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elif patched.get("multi_value"):
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patched["type"] = "multi-values"
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else:
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patched["type"] = "value"
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# Remove legacy keys so Pydantic doesn't error on unknown fields
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patched.pop("free_values", None)
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patched.pop("multi_value", None)
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return patched
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def build_labels_model(labels_cfg: EntityLabelsConfig) -> type[BaseModel] | None:
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"""
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Build a dynamic Pydantic model for structured label extraction.
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Each LabelGroup becomes a typed field based on its type:
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- type="text" → str | None (always optional)
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- type="value", optional=True → Literal["v1","v2"] | None
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- type="value", optional=False → Literal["v1","v2"] (required)
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- type="multi-values" → list[Literal["v1","v2"]]
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Args:
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labels_cfg: Parsed EntityLabelsConfig
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Returns:
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Dynamic Pydantic model class, or None if no groups defined
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"""
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fields: dict = {}
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for group in labels_cfg.attributes:
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if not group.key:
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continue
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description = group.description or group.key
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if group.type == "text":
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# Free-form: any string value accepted, always optional
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fields[group.key] = (str | None, Field(default=None, description=description))
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else:
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# Enum-constrained: must have defined values
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if not group.values:
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continue
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values = tuple(v.value for v in group.values if v.value)
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if not values:
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continue
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# Literal[("v1", "v2")] is equivalent to Literal["v1", "v2"] in Python 3.11+
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literal_type = Literal[values] # type: ignore[valid-type]
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if group.type == "multi-values":
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fields[group.key] = (
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list[literal_type], # type: ignore[valid-type]
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Field(default_factory=list, description=description),
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)
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elif group.optional:
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fields[group.key] = (
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literal_type | None, # type: ignore[valid-type]
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Field(default=None, description=description),
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)
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else:
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fields[group.key] = (
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literal_type, # type: ignore[valid-type]
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Field(description=description),
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)
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if not fields:
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return None
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return create_model("Labels", **fields)
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def is_label_entity(text: str, labels_cfg: EntityLabelsConfig, labels_lookup: set[str]) -> bool:
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"""
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Return True if entity text belongs to any configured label group.
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For enum groups: checks the pre-built lookup set.
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For text groups: checks that the text starts with a known key prefix.
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"""
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if text.lower() in labels_lookup:
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return True
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for group in labels_cfg.attributes:
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if group.type == "text" and group.key and text.lower().startswith(f"{group.key.lower()}:"):
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return True
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return False
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def build_labels_lookup(labels_cfg: EntityLabelsConfig | list | None) -> set[str]:
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"""
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Build a set of valid 'key:value' label strings (lowercase) for fast lookup.
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Accepts either EntityLabelsConfig or raw list/None for backwards compatibility.
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Args:
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labels_cfg: EntityLabelsConfig, raw list of attribute dicts, or None
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Returns:
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Set of lowercase 'key:value' strings
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"""
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if labels_cfg is None:
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return set()
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# Accept raw list/dict for backwards compatibility
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if not isinstance(labels_cfg, EntityLabelsConfig):
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parsed = parse_entity_labels(labels_cfg)
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if parsed is None:
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return set()
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labels_cfg = parsed
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valid = set()
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for group in labels_cfg.attributes:
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if group.type == "text":
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continue # No fixed vocabulary — all values accepted in post-processing
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for v in group.values:
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if group.key and v.value:
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valid.add(f"{group.key}:{v.value}".lower())
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return valid
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