trustgraph/trustgraph-base/trustgraph/base/collection_config_handler.py
cybermaggedon d35473f7f7
feat: workspace-based multi-tenancy, replacing user as tenancy axis (#840)
Introduces `workspace` as the isolation boundary for config, flows,
library, and knowledge data. Removes `user` as a schema-level field
throughout the code, API specs, and tests; workspace provides the
same separation more cleanly at the trusted flow.workspace layer
rather than through client-supplied message fields.

Design
------
- IAM tech spec (docs/tech-specs/iam.md) documents current state,
  proposed auth/access model, and migration direction.
- Data ownership model (docs/tech-specs/data-ownership-model.md)
  captures the workspace/collection/flow hierarchy.

Schema + messaging
------------------
- Drop `user` field from AgentRequest/Step, GraphRagQuery,
  DocumentRagQuery, Triples/Graph/Document/Row EmbeddingsRequest,
  Sparql/Rows/Structured QueryRequest, ToolServiceRequest.
- Keep collection/workspace routing via flow.workspace at the
  service layer.
- Translators updated to not serialise/deserialise user.

API specs
---------
- OpenAPI schemas and path examples cleaned of user fields.
- Websocket async-api messages updated.
- Removed the unused parameters/User.yaml.

Services + base
---------------
- Librarian, collection manager, knowledge, config: all operations
  scoped by workspace. Config client API takes workspace as first
  positional arg.
- `flow.workspace` set at flow start time by the infrastructure;
  no longer pass-through from clients.
- Tool service drops user-personalisation passthrough.

CLI + SDK
---------
- tg-init-workspace and workspace-aware import/export.
- All tg-* commands drop user args; accept --workspace.
- Python API/SDK (flow, socket_client, async_*, explainability,
  library) drop user kwargs from every method signature.

MCP server
----------
- All tool endpoints drop user parameters; socket_manager no longer
  keyed per user.

Flow service
------------
- Closure-based topic cleanup on flow stop: only delete topics
  whose blueprint template was parameterised AND no remaining
  live flow (across all workspaces) still resolves to that topic.
  Three scopes fall out naturally from template analysis:
    * {id} -> per-flow, deleted on stop
    * {blueprint} -> per-blueprint, kept while any flow of the
      same blueprint exists
    * {workspace} -> per-workspace, kept while any flow in the
      workspace exists
    * literal -> global, never deleted (e.g. tg.request.librarian)
  Fixes a bug where stopping a flow silently destroyed the global
  librarian exchange, wedging all library operations until manual
  restart.

RabbitMQ backend
----------------
- heartbeat=60, blocked_connection_timeout=300. Catches silently
  dead connections (broker restart, orphaned channels, network
  partitions) within ~2 heartbeat windows, so the consumer
  reconnects and re-binds its queue rather than sitting forever
  on a zombie connection.

Tests
-----
- Full test refresh: unit, integration, contract, provenance.
- Dropped user-field assertions and constructor kwargs across
  ~100 test files.
- Renamed user-collection isolation tests to workspace-collection.
2026-04-21 23:23:01 +01:00

153 lines
5.3 KiB
Python

"""
Handler for storage services to process collection configuration from config push
"""
import json
import logging
from typing import Dict, Set
logger = logging.getLogger(__name__)
class CollectionConfigHandler:
"""
Handles collection configuration from config push messages for storage services.
Storage services should:
1. Inherit from this class along with their service base class
2. Call register_config_handler(self.on_collection_config) in __init__
3. Implement create_collection(workspace, collection, metadata) method
4. Implement delete_collection(workspace, collection) method
"""
def __init__(self, **kwargs):
# Track known collections: {(workspace, collection): metadata_dict}
self.known_collections: Dict[tuple, dict] = {}
# Pass remaining kwargs up the inheritance chain
super().__init__(**kwargs)
async def on_collection_config(
self, workspace: str, config: dict, version: int
):
"""
Handle config push messages and extract collection information
for a single workspace.
Args:
workspace: Workspace the config applies to
config: Configuration dictionary from ConfigPush message
version: Configuration version number
"""
logger.info(
f"Processing collection configuration "
f"(version {version}, workspace {workspace})"
)
# Extract collections from config (treat missing key as empty).
# Each config key IS the collection name — config is already
# partitioned by workspace, so no workspace prefix is needed
# on the key.
collection_config = config.get("collection", {})
# Track which collections we've seen in this config
current_collections: Set[tuple] = set()
for collection, value_json in collection_config.items():
try:
current_collections.add((workspace, collection))
metadata = json.loads(value_json)
key = (workspace, collection)
if key not in self.known_collections:
logger.info(
f"New collection detected: {workspace}/{collection}"
)
await self.create_collection(
workspace, collection, metadata
)
self.known_collections[key] = metadata
else:
if self.known_collections[key] != metadata:
logger.info(
f"Collection metadata updated: "
f"{workspace}/{collection}"
)
self.known_collections[key] = metadata
except Exception as e:
logger.error(
f"Error processing collection config for "
f"{workspace}/{collection}: {e}",
exc_info=True,
)
# Find collections for THIS workspace that were deleted (in
# known but not in current). Only compare collections owned by
# this workspace — other workspaces' collections are not
# affected by this config update.
known_for_ws = {
(w, c) for (w, c) in self.known_collections.keys()
if w == workspace
}
deleted_collections = known_for_ws - current_collections
for ws, collection in deleted_collections:
logger.info(f"Collection deleted: {ws}/{collection}")
try:
# Remove from known_collections FIRST to immediately
# reject new writes
del self.known_collections[(ws, collection)]
await self.delete_collection(ws, collection)
except Exception as e:
logger.error(
f"Error deleting collection {ws}/{collection}: {e}",
exc_info=True,
)
logger.debug(
f"Collection config processing complete. "
f"Known collections: {len(self.known_collections)}"
)
async def create_collection(
self, workspace: str, collection: str, metadata: dict,
):
"""
Create a collection in the storage backend.
Subclasses must implement this method.
Args:
workspace: Workspace ID
collection: Collection ID
metadata: Collection metadata dictionary
"""
raise NotImplementedError(
"Storage service must implement create_collection method"
)
async def delete_collection(self, workspace: str, collection: str):
"""
Delete a collection from the storage backend.
Subclasses must implement this method.
Args:
workspace: Workspace ID
collection: Collection ID
"""
raise NotImplementedError(
"Storage service must implement delete_collection method"
)
def collection_exists(self, workspace: str, collection: str) -> bool:
"""
Check if a collection is known to exist.
Args:
workspace: Workspace ID
collection: Collection ID
Returns:
True if collection exists, False otherwise
"""
return (workspace, collection) in self.known_collections