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feat: workspace-based multi-tenancy, replacing user as tenancy axis

Browse source 
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.
This commit is contained in:
Cyber MacGeddon 2026-04-18 23:07:26 +01:00
parent 9332089b3d
commit bade8fba1b
377 changed files with 6868 additions and 5785 deletions
Download patch file Download diff file Expand all files Collapse all files

30
trustgraph-base/trustgraph/api/async_socket_client.py
View file

@ -22,10 +22,14 @@ class AsyncSocketClient:
Or call connect()/aclose() manually.
"""
def __init__(self, url: str, timeout: int, token: Optional[str]):
def __init__(
self, url: str, timeout: int, token: Optional[str],
workspace: str = "default",
):
self.url = self._convert_to_ws_url(url)
self.timeout = timeout
self.token = token
self.workspace = workspace
self._request_counter = 0
self._socket = None
self._connect_cm = None
@ -117,6 +121,7 @@ class AsyncSocketClient:
try:
message = {
"id": request_id,
"workspace": self.workspace,
"service": service,
"request": request
}
@ -149,6 +154,7 @@ class AsyncSocketClient:
try:
message = {
"id": request_id,
"workspace": self.workspace,
"service": service,
"request": request
}
@ -251,13 +257,12 @@ class AsyncSocketFlowInstance:
self.client = client
self.flow_id = flow_id
async def agent(self, question: str, user: str, state: Optional[Dict[str, Any]] = None,
async def agent(self, question: str, state: Optional[Dict[str, Any]] = None,
group: Optional[str] = None, history: Optional[list] = None,
streaming: bool = False, **kwargs) -> Union[Dict[str, Any], AsyncIterator]:
"""Agent with optional streaming"""
request = {
"question": question,
"user": user,
"streaming": streaming
}
if state is not None:
@ -303,13 +308,12 @@ class AsyncSocketFlowInstance:
if isinstance(chunk, RAGChunk):
yield chunk
async def graph_rag(self, query: str, user: str, collection: str,
async def graph_rag(self, query: str, collection: str,
max_subgraph_size: int = 1000, max_subgraph_count: int = 5,
max_entity_distance: int = 3, streaming: bool = False, **kwargs):
"""Graph RAG with optional streaming"""
request = {
"query": query,
"user": user,
"collection": collection,
"max-subgraph-size": max_subgraph_size,
"max-subgraph-count": max_subgraph_count,
@ -330,12 +334,11 @@ class AsyncSocketFlowInstance:
if hasattr(chunk, 'content'):
yield chunk.content
async def document_rag(self, query: str, user: str, collection: str,
async def document_rag(self, query: str, collection: str,
doc_limit: int = 10, streaming: bool = False, **kwargs):
"""Document RAG with optional streaming"""
request = {
"query": query,
"user": user,
"collection": collection,
"doc-limit": doc_limit,
"streaming": streaming
@ -375,14 +378,13 @@ class AsyncSocketFlowInstance:
if hasattr(chunk, 'content'):
yield chunk.content
async def graph_embeddings_query(self, text: str, user: str, collection: str, limit: int = 10, **kwargs):
async def graph_embeddings_query(self, text: str, collection: str, limit: int = 10, **kwargs):
"""Query graph embeddings for semantic search"""
emb_result = await self.embeddings(texts=[text])
vector = emb_result.get("vectors", [[]])[0]
request = {
"vector": vector,
"user": user,
"collection": collection,
"limit": limit
}
@ -397,7 +399,7 @@ class AsyncSocketFlowInstance:
return await self.client._send_request("embeddings", self.flow_id, request)
async def triples_query(self, s=None, p=None, o=None, user=None, collection=None, limit=100, **kwargs):
async def triples_query(self, s=None, p=None, o=None, collection=None, limit=100, **kwargs):
"""Triple pattern query"""
request = {"limit": limit}
if s is not None:
@ -406,20 +408,17 @@ class AsyncSocketFlowInstance:
request["p"] = str(p)
if o is not None:
request["o"] = str(o)
if user is not None:
request["user"] = user
if collection is not None:
request["collection"] = collection
request.update(kwargs)
return await self.client._send_request("triples", self.flow_id, request)
async def rows_query(self, query: str, user: str, collection: str, variables: Optional[Dict] = None,
async def rows_query(self, query: str, collection: str, variables: Optional[Dict] = None,
operation_name: Optional[str] = None, **kwargs):
"""GraphQL query against structured rows"""
request = {
"query": query,
"user": user,
"collection": collection
}
if variables:
@ -441,7 +440,7 @@ class AsyncSocketFlowInstance:
return await self.client._send_request("mcp-tool", self.flow_id, request)
async def row_embeddings_query(
self, text: str, schema_name: str, user: str = "trustgraph",
self, text: str, schema_name: str,
collection: str = "default", index_name: Optional[str] = None,
limit: int = 10, **kwargs
):
@ -452,7 +451,6 @@ class AsyncSocketFlowInstance:
request = {
"vector": vector,
"schema_name": schema_name,
"user": user,
"collection": collection,
"limit": limit
}