mirror of
https://github.com/trustgraph-ai/trustgraph.git
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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.
149 lines
4 KiB
Python
149 lines
4 KiB
Python
"""
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TrustGraph Collection Management
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This module provides interfaces for managing data collections in TrustGraph.
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Collections provide logical grouping within a workspace.
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"""
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import logging
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from . types import CollectionMetadata
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from . exceptions import *
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logger = logging.getLogger(__name__)
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class Collection:
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"""
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Collection management client.
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Provides methods for managing data collections within the configured
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workspace, including listing, updating metadata, and deleting
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collections.
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"""
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def __init__(self, api):
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"""
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Initialize Collection client.
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Args:
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api: Parent Api instance for making requests
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"""
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self.api = api
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def request(self, request):
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"""
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Make a collection-scoped API request.
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Args:
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request: Request payload dictionary
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Returns:
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dict: Response object
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"""
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return self.api.request(f"collection-management", request)
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def list_collections(self, tag_filter=None):
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"""
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List all collections in this workspace.
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Args:
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tag_filter: Optional list of tags to filter collections
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Returns:
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list[CollectionMetadata]: List of collection metadata objects
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"""
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input = {
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"operation": "list-collections",
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"workspace": self.api.workspace,
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}
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if tag_filter:
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input["tag_filter"] = tag_filter
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object = self.request(input)
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try:
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if object is None or "collections" not in object:
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return []
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collections = object.get("collections", [])
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if collections is None:
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return []
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return [
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CollectionMetadata(
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collection = v["collection"],
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name = v["name"],
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description = v["description"],
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tags = v["tags"]
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)
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for v in collections
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]
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except Exception as e:
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logger.error("Failed to parse collection list response", exc_info=True)
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raise ProtocolException(f"Response not formatted correctly")
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def update_collection(self, collection, name=None, description=None, tags=None):
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"""
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Update collection metadata.
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Args:
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collection: Collection identifier
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name: New collection name (optional)
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description: New collection description (optional)
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tags: New list of tags (optional)
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Returns:
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CollectionMetadata: Updated collection metadata, or None if not found
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"""
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input = {
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"operation": "update-collection",
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"workspace": self.api.workspace,
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"collection": collection,
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}
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if name is not None:
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input["name"] = name
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if description is not None:
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input["description"] = description
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if tags is not None:
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input["tags"] = tags
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object = self.request(input)
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try:
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if "collections" in object and object["collections"]:
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v = object["collections"][0]
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return CollectionMetadata(
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collection = v["collection"],
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name = v["name"],
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description = v["description"],
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tags = v["tags"]
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)
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return None
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except Exception as e:
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logger.error("Failed to parse collection update response", exc_info=True)
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raise ProtocolException(f"Response not formatted correctly")
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def delete_collection(self, collection):
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"""
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Delete a collection.
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Args:
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collection: Collection identifier to delete
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Returns:
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dict: Empty response object
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"""
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input = {
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"operation": "delete-collection",
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"workspace": self.api.workspace,
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"collection": collection,
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}
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self.request(input)
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return {}
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