fleet-memory/hindsight-all/hindsight/api_namespaces.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

193 lines
5.8 KiB
Python

"""
API namespace classes for organizing client methods.
These classes provide organized access to different parts of the Hindsight API
while ensuring the daemon is running before each call.
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from .embedded import HindsightEmbedded
class BanksAPI:
"""Namespace for bank-related operations."""
def __init__(self, embedded: "HindsightEmbedded"):
self._embedded = embedded
def create(
self,
bank_id: str,
name: str | None = None,
mission: str | None = None,
disposition: dict[str, Any] | None = None,
):
"""Create a new bank."""
self._embedded._ensure_started()
return self._embedded._client.create_bank(
bank_id=bank_id,
name=name,
mission=mission,
disposition=disposition,
)
def delete(self, bank_id: str):
"""Delete a bank."""
self._embedded._ensure_started()
return self._embedded._client.delete_bank(bank_id=bank_id)
def set_mission(self, bank_id: str, mission: str):
"""Set or update the mission for a bank."""
self._embedded._ensure_started()
return self._embedded._client.set_mission(bank_id=bank_id, mission=mission)
def set_disposition(self, bank_id: str, disposition: dict[str, Any]):
"""Set or update the disposition for a bank."""
self._embedded._ensure_started()
return self._embedded._client.set_disposition(bank_id=bank_id, disposition=disposition)
class MentalModelsAPI:
"""Namespace for mental model operations."""
def __init__(self, embedded: "HindsightEmbedded"):
self._embedded = embedded
def create(
self,
bank_id: str,
name: str,
content: str,
tags: list[str] | None = None,
):
"""Create a new mental model."""
self._embedded._ensure_started()
return self._embedded._client.create_mental_model(
bank_id=bank_id,
name=name,
content=content,
tags=tags,
)
def list(self, bank_id: str, tags: list[str] | None = None):
"""List all mental models for a bank."""
self._embedded._ensure_started()
return self._embedded._client.list_mental_models(bank_id=bank_id, tags=tags)
def get(self, bank_id: str, mental_model_id: str):
"""Get a specific mental model."""
self._embedded._ensure_started()
return self._embedded._client.get_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
def refresh(self, bank_id: str, mental_model_id: str):
"""Refresh a mental model."""
self._embedded._ensure_started()
return self._embedded._client.refresh_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
def update(
self,
bank_id: str,
mental_model_id: str,
name: str | None = None,
content: str | None = None,
tags: list[str] | None = None,
):
"""Update a mental model."""
self._embedded._ensure_started()
return self._embedded._client.update_mental_model(
bank_id=bank_id,
mental_model_id=mental_model_id,
name=name,
content=content,
tags=tags,
)
def delete(self, bank_id: str, mental_model_id: str):
"""Delete a mental model."""
self._embedded._ensure_started()
return self._embedded._client.delete_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
class DirectivesAPI:
"""Namespace for directive operations."""
def __init__(self, embedded: "HindsightEmbedded"):
self._embedded = embedded
def create(
self,
bank_id: str,
name: str,
content: str,
tags: list[str] | None = None,
):
"""Create a new directive."""
self._embedded._ensure_started()
return self._embedded._client.create_directive(
bank_id=bank_id,
name=name,
content=content,
tags=tags,
)
def list(self, bank_id: str, tags: list[str] | None = None):
"""List all directives for a bank."""
self._embedded._ensure_started()
return self._embedded._client.list_directives(bank_id=bank_id, tags=tags)
def get(self, bank_id: str, directive_id: str):
"""Get a specific directive."""
self._embedded._ensure_started()
return self._embedded._client.get_directive(bank_id=bank_id, directive_id=directive_id)
def update(
self,
bank_id: str,
directive_id: str,
name: str | None = None,
content: str | None = None,
tags: list[str] | None = None,
):
"""Update a directive."""
self._embedded._ensure_started()
return self._embedded._client.update_directive(
bank_id=bank_id,
directive_id=directive_id,
name=name,
content=content,
tags=tags,
)
def delete(self, bank_id: str, directive_id: str):
"""Delete a directive."""
self._embedded._ensure_started()
return self._embedded._client.delete_directive(bank_id=bank_id, directive_id=directive_id)
class MemoriesAPI:
"""Namespace for memory operations."""
def __init__(self, embedded: "HindsightEmbedded"):
self._embedded = embedded
def list(
self,
bank_id: str,
type: str | None = None,
search_query: str | None = None,
limit: int = 100,
offset: int = 0,
):
"""List memories in a bank."""
self._embedded._ensure_started()
return self._embedded._client.list_memories(
bank_id=bank_id,
type=type,
search_query=search_query,
limit=limit,
offset=offset,
)