fleet-memory/hindsight-api-slim/hindsight_api/engine/task_backend.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

266 lines
8.3 KiB
Python

"""
Task backend for distributed task processing.
This provides an abstraction for task storage and execution:
- BrokerTaskBackend: Uses PostgreSQL as broker (production)
- SyncTaskBackend: Executes tasks immediately (testing/embedded)
"""
import json
import logging
from abc import ABC, abstractmethod
from collections.abc import Awaitable, Callable
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
import asyncpg
logger = logging.getLogger(__name__)
def fq_table(table: str, schema: str | None = None) -> str:
"""Get fully-qualified table name with optional schema prefix."""
if schema:
return f'"{schema}".{table}'
return table
class TaskBackend(ABC):
"""
Abstract base class for task execution backends.
Implementations must:
1. Store/publish task events (as serializable dicts)
2. Execute tasks through a provided executor callback (optional)
The backend treats tasks as pure dictionaries that can be serialized
and stored in the database. The executor (typically MemoryEngine.execute_task)
receives the dict and routes it to the appropriate handler.
"""
def __init__(self):
"""Initialize the task backend."""
self._executor: Callable[[dict[str, Any]], Awaitable[None]] | None = None
self._initialized = False
def set_executor(self, executor: Callable[[dict[str, Any]], Awaitable[None]]):
"""
Set the executor callback for processing tasks.
Args:
executor: Async function that takes a task dict and executes it
"""
self._executor = executor
@abstractmethod
async def initialize(self):
"""
Initialize the backend (e.g., connect to database).
"""
pass
@abstractmethod
async def submit_task(self, task_dict: dict[str, Any]):
"""
Submit a task for execution.
Args:
task_dict: Task as a dictionary (must be serializable)
"""
pass
@abstractmethod
async def shutdown(self):
"""
Shutdown the backend gracefully.
"""
pass
async def _execute_task(self, task_dict: dict[str, Any]):
"""
Execute a task through the registered executor.
Args:
task_dict: Task dictionary to execute
"""
if self._executor is None:
task_type = task_dict.get("type", "unknown")
logger.warning(f"No executor registered, skipping task {task_type}")
return
try:
await self._executor(task_dict)
except Exception as e:
task_type = task_dict.get("type", "unknown")
logger.error(f"Error executing task {task_type}: {e}")
import traceback
traceback.print_exc()
class SyncTaskBackend(TaskBackend):
"""
Synchronous task backend that executes tasks immediately.
This is useful for tests and embedded/CLI usage where we don't want
background workers. Tasks are executed inline rather than being queued.
"""
async def initialize(self):
"""No-op for sync backend."""
self._initialized = True
logger.debug("SyncTaskBackend initialized")
async def submit_task(self, task_dict: dict[str, Any]):
"""
Execute the task immediately (synchronously).
Args:
task_dict: Task dictionary to execute
"""
if not self._initialized:
await self.initialize()
await self._execute_task(task_dict)
async def shutdown(self):
"""No-op for sync backend."""
self._initialized = False
logger.debug("SyncTaskBackend shutdown")
class BrokerTaskBackend(TaskBackend):
"""
Task backend using PostgreSQL as broker.
submit_task() stores task_payload in async_operations table.
Actual polling and execution is handled separately by WorkerPoller.
This backend is used by the API to store tasks. Workers poll
the database separately to claim and execute tasks.
"""
def __init__(
self,
pool_getter: Callable[[], "asyncpg.Pool"],
schema: str | None = None,
schema_getter: Callable[[], str | None] | None = None,
):
"""
Initialize the broker task backend.
Args:
pool_getter: Callable that returns the asyncpg connection pool
schema: Database schema for multi-tenant support (optional, static)
schema_getter: Callable that returns current schema dynamically (optional).
If set, takes precedence over static schema for submit_task.
"""
super().__init__()
self._pool_getter = pool_getter
self._schema = schema
self._schema_getter = schema_getter
async def initialize(self):
"""Initialize the backend."""
self._initialized = True
logger.info("BrokerTaskBackend initialized")
async def submit_task(self, task_dict: dict[str, Any]):
"""
Store task payload in async_operations table.
The task_dict should contain an 'operation_id' if updating an existing
operation record, otherwise a new operation will be created.
Args:
task_dict: Task dictionary to store (must be JSON serializable)
"""
if not self._initialized:
await self.initialize()
pool = self._pool_getter()
operation_id = task_dict.get("operation_id")
task_type = task_dict.get("type", "unknown")
bank_id = task_dict.get("bank_id")
# Custom encoder to handle datetime objects
from datetime import datetime
def datetime_encoder(obj):
if isinstance(obj, datetime):
return obj.isoformat()
raise TypeError(f"Object of type {type(obj).__name__} is not JSON serializable")
payload_json = json.dumps(task_dict, default=datetime_encoder)
schema = self._schema_getter() if self._schema_getter else self._schema
table = fq_table("async_operations", schema)
if operation_id:
# Update existing operation with task payload
await pool.execute(
f"""
UPDATE {table}
SET task_payload = $1::jsonb, updated_at = now()
WHERE operation_id = $2
""",
payload_json,
operation_id,
)
logger.debug(f"Updated task payload for operation {operation_id}")
else:
# Insert new operation (for tasks without pre-created records)
# e.g., access_count_update tasks
import uuid
new_id = uuid.uuid4()
await pool.execute(
f"""
INSERT INTO {table} (operation_id, bank_id, operation_type, status, task_payload)
VALUES ($1, $2, $3, 'pending', $4::jsonb)
""",
new_id,
bank_id,
task_type,
payload_json,
)
logger.debug(f"Created new operation {new_id} for task type {task_type}")
async def shutdown(self):
"""Shutdown the backend."""
self._initialized = False
logger.info("BrokerTaskBackend shutdown")
async def wait_for_pending_tasks(self, timeout: float = 120.0):
"""
Wait for pending tasks to be processed.
In the broker model, this polls the database to check if tasks
for this process have been completed. This is useful in tests
when worker_enabled=True (API processes its own tasks).
Args:
timeout: Maximum time to wait in seconds
"""
import asyncio
pool = self._pool_getter()
schema = self._schema_getter() if self._schema_getter else self._schema
table = fq_table("async_operations", schema)
start_time = asyncio.get_event_loop().time()
while asyncio.get_event_loop().time() - start_time < timeout:
# Check if there are any pending tasks with payloads
count = await pool.fetchval(
f"""
SELECT COUNT(*) FROM {table}
WHERE status = 'pending' AND task_payload IS NOT NULL
"""
)
if count == 0:
return
await asyncio.sleep(0.5)
logger.warning(f"Timeout waiting for pending tasks after {timeout}s")