mirror of
https://github.com/trustgraph-ai/trustgraph.git
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d35473f7f7
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.
258 lines
8.5 KiB
Python
258 lines
8.5 KiB
Python
"""
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Contract tests for document embeddings message schemas and translators
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Ensures that message formats remain consistent across services
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"""
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import pytest
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from unittest.mock import MagicMock
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from trustgraph.schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse, ChunkMatch, Error
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from trustgraph.messaging.translators.embeddings_query import (
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DocumentEmbeddingsRequestTranslator,
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DocumentEmbeddingsResponseTranslator
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)
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class TestDocumentEmbeddingsRequestContract:
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"""Test DocumentEmbeddingsRequest schema contract"""
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def test_request_schema_fields(self):
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"""Test that DocumentEmbeddingsRequest has expected fields"""
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request = DocumentEmbeddingsRequest(
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vector=[0.1, 0.2, 0.3],
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limit=10,
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collection="test_collection"
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)
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assert hasattr(request, 'vector')
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assert hasattr(request, 'limit')
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assert hasattr(request, 'collection')
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assert request.vector == [0.1, 0.2, 0.3]
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assert request.limit == 10
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assert request.collection == "test_collection"
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def test_request_translator_decode(self):
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"""Test request translator converts dict to Pulsar schema"""
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translator = DocumentEmbeddingsRequestTranslator()
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data = {
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"vector": [0.1, 0.2, 0.3, 0.4],
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"limit": 5,
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"collection": "custom_collection"
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}
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result = translator.decode(data)
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assert isinstance(result, DocumentEmbeddingsRequest)
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assert result.vector == [0.1, 0.2, 0.3, 0.4]
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assert result.limit == 5
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assert result.collection == "custom_collection"
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def test_request_translator_decode_with_defaults(self):
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"""Test request translator uses correct defaults"""
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translator = DocumentEmbeddingsRequestTranslator()
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data = {
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"vector": [0.1, 0.2]
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# No limit or collection provided
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}
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result = translator.decode(data)
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assert isinstance(result, DocumentEmbeddingsRequest)
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assert result.vector == [0.1, 0.2]
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assert result.limit == 10 # Default
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assert result.collection == "default" # Default
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def test_request_translator_encode(self):
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"""Test request translator converts Pulsar schema to dict"""
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translator = DocumentEmbeddingsRequestTranslator()
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request = DocumentEmbeddingsRequest(
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vector=[0.5, 0.6],
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limit=20,
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collection="test_collection"
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)
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result = translator.encode(request)
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assert isinstance(result, dict)
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assert result["vector"] == [0.5, 0.6]
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assert result["limit"] == 20
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assert result["collection"] == "test_collection"
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class TestDocumentEmbeddingsResponseContract:
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"""Test DocumentEmbeddingsResponse schema contract"""
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def test_response_schema_fields(self):
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"""Test that DocumentEmbeddingsResponse has expected fields"""
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# Create a response with chunks
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response = DocumentEmbeddingsResponse(
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error=None,
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chunks=[
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ChunkMatch(chunk_id="chunk1", score=0.9),
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ChunkMatch(chunk_id="chunk2", score=0.8),
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ChunkMatch(chunk_id="chunk3", score=0.7)
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]
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)
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# Verify all expected fields exist
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assert hasattr(response, 'error')
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assert hasattr(response, 'chunks')
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# Verify field values
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assert response.error is None
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assert len(response.chunks) == 3
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assert response.chunks[0].chunk_id == "chunk1"
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assert response.chunks[0].score == 0.9
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def test_response_schema_with_error(self):
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"""Test response schema with error"""
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error = Error(
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type="query_error",
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message="Database connection failed"
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)
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response = DocumentEmbeddingsResponse(
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error=error,
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chunks=[]
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)
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assert response.error == error
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assert response.chunks == []
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def test_response_translator_encode_with_chunks(self):
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"""Test response translator converts Pulsar schema with chunks to dict"""
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translator = DocumentEmbeddingsResponseTranslator()
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response = DocumentEmbeddingsResponse(
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error=None,
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chunks=[
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ChunkMatch(chunk_id="doc1/c1", score=0.95),
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ChunkMatch(chunk_id="doc2/c2", score=0.85),
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ChunkMatch(chunk_id="doc3/c3", score=0.75)
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]
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)
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result = translator.encode(response)
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assert isinstance(result, dict)
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assert "chunks" in result
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assert len(result["chunks"]) == 3
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assert result["chunks"][0]["chunk_id"] == "doc1/c1"
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assert result["chunks"][0]["score"] == 0.95
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def test_response_translator_encode_with_empty_chunks(self):
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"""Test response translator handles empty chunks list"""
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translator = DocumentEmbeddingsResponseTranslator()
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response = DocumentEmbeddingsResponse(
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error=None,
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chunks=[]
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)
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result = translator.encode(response)
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assert isinstance(result, dict)
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assert "chunks" in result
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assert result["chunks"] == []
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def test_response_translator_encode_with_none_chunks(self):
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"""Test response translator handles None chunks"""
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translator = DocumentEmbeddingsResponseTranslator()
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response = MagicMock()
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response.chunks = None
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result = translator.encode(response)
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assert isinstance(result, dict)
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assert "chunks" not in result or result.get("chunks") is None
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def test_response_translator_encode_with_completion(self):
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"""Test response translator with completion flag"""
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translator = DocumentEmbeddingsResponseTranslator()
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response = DocumentEmbeddingsResponse(
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error=None,
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chunks=[
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ChunkMatch(chunk_id="chunk1", score=0.9),
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ChunkMatch(chunk_id="chunk2", score=0.8)
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]
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)
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result, is_final = translator.encode_with_completion(response)
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assert isinstance(result, dict)
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assert "chunks" in result
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assert len(result["chunks"]) == 2
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assert result["chunks"][0]["chunk_id"] == "chunk1"
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assert is_final is True # Document embeddings responses are always final
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def test_response_translator_decode_not_implemented(self):
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"""Test that decode raises NotImplementedError for responses"""
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translator = DocumentEmbeddingsResponseTranslator()
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with pytest.raises(NotImplementedError):
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translator.decode({"chunks": [{"chunk_id": "test", "score": 0.9}]})
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class TestDocumentEmbeddingsMessageCompatibility:
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"""Test compatibility between request and response messages"""
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def test_request_response_flow(self):
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"""Test complete request-response flow maintains data integrity"""
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# Create request
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request_data = {
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"vector": [0.1, 0.2, 0.3],
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"limit": 5,
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"collection": "test_collection"
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}
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# Convert to Pulsar request
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req_translator = DocumentEmbeddingsRequestTranslator()
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pulsar_request = req_translator.decode(request_data)
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# Simulate service processing and creating response
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response = DocumentEmbeddingsResponse(
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error=None,
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chunks=[
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ChunkMatch(chunk_id="doc1/c1", score=0.95),
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ChunkMatch(chunk_id="doc2/c2", score=0.85)
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]
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)
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# Convert response back to dict
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resp_translator = DocumentEmbeddingsResponseTranslator()
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response_data = resp_translator.encode(response)
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# Verify data integrity
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assert isinstance(pulsar_request, DocumentEmbeddingsRequest)
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assert isinstance(response_data, dict)
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assert "chunks" in response_data
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assert len(response_data["chunks"]) == 2
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def test_error_response_flow(self):
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"""Test error response flow"""
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# Create error response
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error = Error(
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type="vector_db_error",
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message="Collection not found"
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)
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response = DocumentEmbeddingsResponse(
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error=error,
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chunks=[]
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)
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# Convert response to dict
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translator = DocumentEmbeddingsResponseTranslator()
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response_data = translator.encode(response)
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# Verify error handling
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assert isinstance(response_data, dict)
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# The translator doesn't include error in the dict, only chunks
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assert "chunks" in response_data
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assert response_data["chunks"] == []
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