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.
302 lines
10 KiB
Python
302 lines
10 KiB
Python
"""
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Tests for null embedding protection: empty/None vector skipping, entity
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validation, dimension-aware collection creation, and query-time empty
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vector handling.
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Tests the pure functions and logic without Qdrant connections.
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"""
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import pytest
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from unittest.mock import MagicMock, patch, AsyncMock
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from trustgraph.schema import Term, IRI, LITERAL, BLANK
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# ---------------------------------------------------------------------------
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# Graph embeddings: get_term_value
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# ---------------------------------------------------------------------------
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class TestGraphEmbeddingsGetTermValue:
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def test_iri_returns_iri(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import get_term_value
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t = Term(type=IRI, iri="http://example.org/x")
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assert get_term_value(t) == "http://example.org/x"
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def test_literal_returns_value(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import get_term_value
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t = Term(type=LITERAL, value="hello")
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assert get_term_value(t) == "hello"
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def test_blank_returns_id(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import get_term_value
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t = Term(type=BLANK, id="_:b0")
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assert get_term_value(t) == "_:b0"
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def test_none_returns_none(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import get_term_value
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assert get_term_value(None) is None
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def test_blank_with_value_fallback(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import get_term_value
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t = Term(type=BLANK, id="", value="fallback")
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assert get_term_value(t) == "fallback"
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# ---------------------------------------------------------------------------
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# Document embeddings: null vector protection
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# ---------------------------------------------------------------------------
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class TestDocEmbeddingsNullProtection:
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@pytest.mark.asyncio
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async def test_empty_vector_skipped(self):
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"""Embeddings with empty vectors should be silently skipped."""
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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# Mock collection_exists for config check
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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emb = MagicMock()
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emb.chunk_id = "chunk-1"
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emb.vector = [] # Empty vector
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msg.chunks = [emb]
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await proc.store_document_embeddings("user1", msg)
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# No upsert should be called
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_none_vector_skipped(self):
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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emb = MagicMock()
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emb.chunk_id = "chunk-1"
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emb.vector = None # None vector
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msg.chunks = [emb]
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await proc.store_document_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_empty_chunk_id_skipped(self):
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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emb = MagicMock()
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emb.chunk_id = "" # Empty chunk ID
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emb.vector = [0.1, 0.2, 0.3]
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msg.chunks = [emb]
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await proc.store_document_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_valid_embedding_upserted(self):
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.qdrant.collection_exists.return_value = True
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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emb = MagicMock()
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emb.chunk_id = "chunk-1"
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emb.vector = [0.1, 0.2, 0.3]
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msg.chunks = [emb]
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await proc.store_document_embeddings("user1", msg)
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proc.qdrant.upsert.assert_called_once()
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@pytest.mark.asyncio
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async def test_dimension_in_collection_name(self):
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"""Collection name should include vector dimension."""
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.qdrant.collection_exists.return_value = True
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "docs"
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emb = MagicMock()
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emb.chunk_id = "c1"
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emb.vector = [0.0] * 384 # 384-dim vector
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msg.chunks = [emb]
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await proc.store_document_embeddings("alice", msg)
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call_args = proc.qdrant.upsert.call_args
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assert "d_alice_docs_384" in call_args[1]["collection_name"]
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# ---------------------------------------------------------------------------
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# Graph embeddings: null entity and vector protection
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# ---------------------------------------------------------------------------
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class TestGraphEmbeddingsNullProtection:
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@pytest.mark.asyncio
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async def test_empty_entity_skipped(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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entity = MagicMock()
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entity.entity = Term(type=IRI, iri="") # Empty IRI
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entity.vector = [0.1, 0.2, 0.3]
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msg.entities = [entity]
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await proc.store_graph_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_none_entity_skipped(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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entity = MagicMock()
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entity.entity = None # Null entity
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entity.vector = [0.1, 0.2, 0.3]
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msg.entities = [entity]
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await proc.store_graph_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_empty_vector_skipped(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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entity = MagicMock()
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entity.entity = Term(type=IRI, iri="http://example.org/x")
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entity.vector = [] # Empty vector
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msg.entities = [entity]
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await proc.store_graph_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_valid_entity_and_vector_upserted(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.qdrant.collection_exists.return_value = True
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "col1"
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entity = MagicMock()
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entity.entity = Term(type=IRI, iri="http://example.org/Alice")
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entity.vector = [0.1, 0.2, 0.3]
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entity.chunk_id = "c1"
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msg.entities = [entity]
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await proc.store_graph_embeddings("user1", msg)
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proc.qdrant.upsert.assert_called_once()
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@pytest.mark.asyncio
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async def test_lazy_collection_creation_on_new_dimension(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.qdrant.collection_exists.return_value = False
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proc.collection_exists = MagicMock(return_value=True)
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msg = MagicMock()
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msg.metadata.collection = "graphs"
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entity = MagicMock()
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entity.entity = Term(type=IRI, iri="http://example.org/x")
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entity.vector = [0.0] * 768
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entity.chunk_id = ""
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msg.entities = [entity]
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await proc.store_graph_embeddings("alice", msg)
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# Collection should be created with correct dimension
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proc.qdrant.create_collection.assert_called_once()
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create_args = proc.qdrant.create_collection.call_args
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assert create_args[1]["collection_name"] == "t_alice_graphs_768"
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# ---------------------------------------------------------------------------
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# Collection validation — deleted-while-in-flight protection
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# ---------------------------------------------------------------------------
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class TestCollectionValidation:
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@pytest.mark.asyncio
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async def test_doc_embeddings_dropped_for_deleted_collection(self):
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from trustgraph.storage.doc_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=False)
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msg = MagicMock()
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msg.metadata.collection = "deleted-col"
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msg.chunks = [MagicMock()]
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await proc.store_document_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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@pytest.mark.asyncio
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async def test_graph_embeddings_dropped_for_deleted_collection(self):
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from trustgraph.storage.graph_embeddings.qdrant.write import Processor
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proc = Processor.__new__(Processor)
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proc.qdrant = MagicMock()
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proc.collection_exists = MagicMock(return_value=False)
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msg = MagicMock()
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msg.metadata.collection = "deleted-col"
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msg.entities = [MagicMock()]
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await proc.store_graph_embeddings("user1", msg)
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proc.qdrant.upsert.assert_not_called()
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