fleet-memory/hindsight-api-slim/hindsight_api/engine/retain/entity_labels.py
Nicolò Boschi 15ea23d5d6
feat: introduce hindsight-api-slim and hindsight-all-slim packages (#560)
* 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)
2026-03-13 13:50:03 +01:00

194 lines
6.3 KiB
Python

"""
Entity labels models and helpers for retain pipeline.
Defines a controlled vocabulary of key:value classification labels
(e.g., 'pedagogy:scaffolding', 'interest:active') that are extracted
at retain time and stored as entities.
"""
from typing import Literal
from pydantic import BaseModel, Field, create_model
class LabelValue(BaseModel):
"""A single allowed value for a label group."""
value: str
description: str = ""
class LabelGroup(BaseModel):
"""A label group (dimension) with its type and allowed values."""
key: str
description: str = ""
type: Literal["value", "multi-values", "text"] = "value"
optional: bool = True
tag: bool = False
values: list[LabelValue] = []
class EntityLabelsConfig(BaseModel):
"""Entity labels configuration for a bank (controlled vocabulary)."""
attributes: list[LabelGroup] = []
def parse_entity_labels(raw: dict | list | None) -> EntityLabelsConfig | None:
"""
Parse raw entity labels config into EntityLabelsConfig.
Accepts:
- None → returns None
- list → list of attribute dicts (each may use legacy free_values/multi_value or new type field)
- dict → {attributes: [...]}
Legacy migration (backward-compat):
- free_values=True → type="text"
- multi_value=True → type="multi-values"
- neither / free_values=False → type="value"
Args:
raw: Raw entity labels config from bank config
Returns:
EntityLabelsConfig or None if raw is None/empty
"""
if raw is None:
return None
if isinstance(raw, list):
if not raw:
return None
attributes = [LabelGroup.model_validate(_migrate_label_group(a)) for a in raw]
return EntityLabelsConfig(attributes=attributes)
if isinstance(raw, dict):
attrs_raw = raw.get("attributes", [])
if not attrs_raw:
return None
attributes = [LabelGroup.model_validate(_migrate_label_group(a)) for a in attrs_raw]
return EntityLabelsConfig(attributes=attributes)
return None
def _migrate_label_group(raw: dict) -> dict:
"""Migrate legacy free_values/multi_value fields to the new type field."""
if not isinstance(raw, dict) or "type" in raw:
return raw
patched = dict(raw)
if patched.get("free_values"):
patched["type"] = "text"
elif patched.get("multi_value"):
patched["type"] = "multi-values"
else:
patched["type"] = "value"
# Remove legacy keys so Pydantic doesn't error on unknown fields
patched.pop("free_values", None)
patched.pop("multi_value", None)
return patched
def build_labels_model(labels_cfg: EntityLabelsConfig) -> type[BaseModel] | None:
"""
Build a dynamic Pydantic model for structured label extraction.
Each LabelGroup becomes a typed field based on its type:
- type="text" → str | None (always optional)
- type="value", optional=True → Literal["v1","v2"] | None
- type="value", optional=False → Literal["v1","v2"] (required)
- type="multi-values" → list[Literal["v1","v2"]]
Args:
labels_cfg: Parsed EntityLabelsConfig
Returns:
Dynamic Pydantic model class, or None if no groups defined
"""
fields: dict = {}
for group in labels_cfg.attributes:
if not group.key:
continue
description = group.description or group.key
if group.type == "text":
# Free-form: any string value accepted, always optional
fields[group.key] = (str | None, Field(default=None, description=description))
else:
# Enum-constrained: must have defined values
if not group.values:
continue
values = tuple(v.value for v in group.values if v.value)
if not values:
continue
# Literal[("v1", "v2")] is equivalent to Literal["v1", "v2"] in Python 3.11+
literal_type = Literal[values] # type: ignore[valid-type]
if group.type == "multi-values":
fields[group.key] = (
list[literal_type], # type: ignore[valid-type]
Field(default_factory=list, description=description),
)
elif group.optional:
fields[group.key] = (
literal_type | None, # type: ignore[valid-type]
Field(default=None, description=description),
)
else:
fields[group.key] = (
literal_type, # type: ignore[valid-type]
Field(description=description),
)
if not fields:
return None
return create_model("Labels", **fields)
def is_label_entity(text: str, labels_cfg: EntityLabelsConfig, labels_lookup: set[str]) -> bool:
"""
Return True if entity text belongs to any configured label group.
For enum groups: checks the pre-built lookup set.
For text groups: checks that the text starts with a known key prefix.
"""
if text.lower() in labels_lookup:
return True
for group in labels_cfg.attributes:
if group.type == "text" and group.key and text.lower().startswith(f"{group.key.lower()}:"):
return True
return False
def build_labels_lookup(labels_cfg: EntityLabelsConfig | list | None) -> set[str]:
"""
Build a set of valid 'key:value' label strings (lowercase) for fast lookup.
Accepts either EntityLabelsConfig or raw list/None for backwards compatibility.
Args:
labels_cfg: EntityLabelsConfig, raw list of attribute dicts, or None
Returns:
Set of lowercase 'key:value' strings
"""
if labels_cfg is None:
return set()
# Accept raw list/dict for backwards compatibility
if not isinstance(labels_cfg, EntityLabelsConfig):
parsed = parse_entity_labels(labels_cfg)
if parsed is None:
return set()
labels_cfg = parsed
valid = set()
for group in labels_cfg.attributes:
if group.type == "text":
continue # No fixed vocabulary — all values accepted in post-processing
for v in group.values:
if group.key and v.value:
valid.add(f"{group.key}:{v.value}".lower())
return valid