trustgraph/trustgraph-base/trustgraph/base/request_response_spec.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

150 lines
4.3 KiB
Python

from __future__ import annotations
import uuid
import asyncio
import logging
from typing import Any
from . subscriber import Subscriber
from . producer import Producer
from . spec import Spec
from . metrics import ConsumerMetrics, ProducerMetrics, SubscriberMetrics
# Module logger
logger = logging.getLogger(__name__)
class RequestResponse(Subscriber):
def __init__(
self, backend, subscription, consumer_name,
request_topic, request_schema,
request_metrics,
response_topic, response_schema,
response_metrics,
):
super(RequestResponse, self).__init__(
backend = backend,
subscription = subscription,
consumer_name = consumer_name,
topic = response_topic,
schema = response_schema,
metrics = response_metrics,
)
self.producer = Producer(
backend = backend,
topic = request_topic,
schema = request_schema,
metrics = request_metrics,
)
async def start(self):
await self.producer.start()
await super(RequestResponse, self).start()
async def stop(self):
await self.producer.stop()
await super(RequestResponse, self).stop()
async def request(self, req, timeout=300, recipient=None):
id = str(uuid.uuid4())
q = await self.subscribe(id)
try:
await self.producer.send(
req,
properties={"id": id}
)
except Exception as e:
logger.error(f"Exception sending request: {e}", exc_info=True)
raise e
try:
while True:
resp = await asyncio.wait_for(
q.get(),
timeout=timeout
)
if recipient is None:
# If no recipient handler, just return the first
# response we get
return resp
else:
# Recipient handler gets to decide when we're done b
# returning a boolean
fin = await recipient(resp)
# If done, return the last result otherwise loop round for
# next response
if fin:
return resp
else:
continue
except Exception as e:
logger.error(f"Exception processing response: {e}", exc_info=True)
raise e
finally:
await self.unsubscribe(id)
# This deals with the request/response case. The caller needs to
# use another service in request/response mode. Uses two topics:
# - we send on the request topic as a producer
# - we receive on the response topic as a subscriber
class RequestResponseSpec(Spec):
def __init__(
self, request_name, request_schema, response_name,
response_schema, impl=RequestResponse
):
self.request_name = request_name
self.request_schema = request_schema
self.response_name = response_name
self.response_schema = response_schema
self.impl = impl
def add(self, flow: Any, processor: Any, definition: dict[str, Any]) -> None:
request_metrics = ProducerMetrics(
processor = flow.id, flow = flow.name, name = self.request_name
)
response_metrics = SubscriberMetrics(
processor = flow.id, flow = flow.name, name = self.request_name
)
rr = self.impl(
backend = processor.pubsub,
# Make subscription names unique, so that all subscribers get
# to see all response messages
subscription = (
processor.id + "--" + flow.workspace + "--" +
flow.name + "--" + self.request_name + "--" +
str(uuid.uuid4())
),
consumer_name = flow.id,
request_topic = definition["topics"][self.request_name],
request_schema = self.request_schema,
request_metrics = request_metrics,
response_topic = definition["topics"][self.response_name],
response_schema = self.response_schema,
response_metrics = response_metrics,
)
flow.consumer[self.request_name] = rr