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.
132 lines
No EOL
5.1 KiB
Python
132 lines
No EOL
5.1 KiB
Python
"""
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Unit test for DocumentRAG service parameter passing fix.
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Tests that the collection parameter from the message is correctly
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passed to the DocumentRag.query() method.
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"""
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import pytest
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from unittest.mock import MagicMock, AsyncMock, patch, ANY
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from trustgraph.retrieval.document_rag.rag import Processor
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from trustgraph.schema import DocumentRagQuery, DocumentRagResponse
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class TestDocumentRagService:
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"""Test DocumentRAG service parameter passing"""
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@patch('trustgraph.retrieval.document_rag.rag.DocumentRag')
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@pytest.mark.asyncio
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async def test_collection_parameter_passed_to_query(self, mock_document_rag_class):
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"""
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Test that collection from message is passed to DocumentRag.query().
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This is a regression test for the bug where the collection parameter
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was ignored, causing wrong collection names like 'd_trustgraph_default_384'
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instead of one that reflects the requested collection.
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"""
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# Setup processor
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processor = Processor(
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taskgroup=MagicMock(),
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id="test-processor",
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doc_limit=10
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)
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# Setup mock DocumentRag instance
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mock_rag_instance = AsyncMock()
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mock_document_rag_class.return_value = mock_rag_instance
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mock_rag_instance.query.return_value = ("test response", {"in_token": None, "out_token": None, "model": None})
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# Setup message with custom collection
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msg = MagicMock()
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msg.value.return_value = DocumentRagQuery(
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query="test query",
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collection="test_coll_1", # Custom collection (not default "default")
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doc_limit=5
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)
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msg.properties.return_value = {"id": "test-id"}
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# Setup flow mock
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consumer = MagicMock()
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flow = MagicMock()
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# Mock flow to return AsyncMock for clients and response producer
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mock_producer = AsyncMock()
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def flow_router(service_name):
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if service_name == "response":
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return mock_producer
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return AsyncMock() # embeddings, doc-embeddings, prompt clients
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flow.side_effect = flow_router
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# Execute
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await processor.on_request(msg, consumer, flow)
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# Verify: DocumentRag.query was called with correct parameters
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mock_rag_instance.query.assert_called_once_with(
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"test query",
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workspace=ANY, # Workspace comes from flow.workspace (mock)
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collection="test_coll_1", # Must be from message, not hardcoded default
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doc_limit=5,
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explain_callback=ANY, # Explainability callback is always passed
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save_answer_callback=ANY, # Librarian save callback is always passed
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)
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# Verify response was sent
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mock_producer.send.assert_called_once()
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sent_response = mock_producer.send.call_args[0][0]
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assert isinstance(sent_response, DocumentRagResponse)
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assert sent_response.response == "test response"
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assert sent_response.error is None
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@patch('trustgraph.retrieval.document_rag.rag.DocumentRag')
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@pytest.mark.asyncio
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async def test_non_streaming_mode_sets_end_of_stream_true(self, mock_document_rag_class):
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"""
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Test that non-streaming mode sets end_of_stream=True in response.
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This is a regression test for the bug where non-streaming responses
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didn't set end_of_stream, causing clients to hang waiting for more data.
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"""
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# Setup processor
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processor = Processor(
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taskgroup=MagicMock(),
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id="test-processor",
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doc_limit=10
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)
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# Setup mock DocumentRag instance
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mock_rag_instance = AsyncMock()
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mock_document_rag_class.return_value = mock_rag_instance
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mock_rag_instance.query.return_value = ("A document about cats.", {"in_token": None, "out_token": None, "model": None})
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# Setup message with non-streaming request
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msg = MagicMock()
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msg.value.return_value = DocumentRagQuery(
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query="What is a cat?",
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collection="default",
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doc_limit=10,
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streaming=False # Non-streaming mode
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)
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msg.properties.return_value = {"id": "test-id"}
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# Setup flow mock
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consumer = MagicMock()
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flow = MagicMock()
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mock_producer = AsyncMock()
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def flow_router(service_name):
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if service_name == "response":
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return mock_producer
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return AsyncMock()
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flow.side_effect = flow_router
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# Execute
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await processor.on_request(msg, consumer, flow)
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# Verify: response was sent with end_of_stream=True
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mock_producer.send.assert_called_once()
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sent_response = mock_producer.send.call_args[0][0]
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assert isinstance(sent_response, DocumentRagResponse)
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assert sent_response.response == "A document about cats."
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assert sent_response.end_of_stream is True, "Non-streaming response must have end_of_stream=True"
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assert sent_response.end_of_session is True
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assert sent_response.error is None |