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.

tests/integration/test_nlp_query_integration.py

@@ -72,7 +72,7 @@ class TestNLPQueryServiceIntegration:
         )
         
         # Set up schemas
-        proc.schemas = sample_schemas
+        proc.schemas = {"default": dict(sample_schemas)}
         
         # Mock the client method
         proc.client = MagicMock()
@@ -94,6 +94,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -173,6 +174,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -229,7 +231,7 @@ class TestNLPQueryServiceIntegration:
         }
         
         # Act - Update configuration
-        await integration_processor.on_schema_config(new_schema_config, "v2")
+        await integration_processor.on_schema_config("default", new_schema_config, "v2")
         
         # Arrange - Test query using new schema
         request = QuestionToStructuredQueryRequest(
@@ -243,6 +245,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -272,7 +275,7 @@ class TestNLPQueryServiceIntegration:
         await integration_processor.on_message(msg, consumer, flow)
         
         # Assert
-        assert "inventory" in integration_processor.schemas
+        assert "inventory" in integration_processor.schemas["default"]
         response_call = flow_response.send.call_args
         response = response_call[0][0]
         assert response.detected_schemas == ["inventory"]
@@ -293,6 +296,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -334,7 +338,7 @@ class TestNLPQueryServiceIntegration:
             graphql_generation_template="custom-graphql-generator"
         )
         
-        custom_processor.schemas = sample_schemas
+        custom_processor.schemas = {"default": dict(sample_schemas)}
         custom_processor.client = MagicMock()
         
         request = QuestionToStructuredQueryRequest(
@@ -348,6 +352,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -394,7 +399,7 @@ class TestNLPQueryServiceIntegration:
                 ] + [SchemaField(name=f"field_{j}", type="string") for j in range(5)]
             )
         
-        integration_processor.schemas.update(large_schema_set)
+        integration_processor.schemas["default"].update(large_schema_set)
         
         request = QuestionToStructuredQueryRequest(
             question="Show me data from table_05 and table_12",
@@ -407,6 +412,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response
         
@@ -462,6 +468,7 @@ class TestNLPQueryServiceIntegration:
             msg.properties.return_value = {"id": f"concurrent-test-{i}"}
             
             flow = MagicMock()
+            flow.workspace = "default"
             flow_response = AsyncMock()
             flow.return_value = flow_response
             
@@ -532,6 +539,7 @@ class TestNLPQueryServiceIntegration:
         
         consumer = MagicMock()
         flow = MagicMock()
+        flow.workspace = "default"
         flow_response = AsyncMock()
         flow.return_value = flow_response