trustgraph/tests/contract/test_translator_completion_flags.py

294 lines
9.9 KiB
Python
Raw Normal View History

"""
Contract tests for message translator completion flag behavior.
These tests verify that translators correctly compute the is_final flag
based on message fields like end_of_stream and end_of_dialog.
"""
import pytest
from trustgraph.schema import (
GraphRagResponse, DocumentRagResponse, AgentResponse, Error
)
from trustgraph.messaging import TranslatorRegistry
@pytest.mark.contract
class TestRAGTranslatorCompletionFlags:
"""Contract tests for RAG response translator completion flags"""
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
def test_graph_rag_translator_is_final_with_end_of_session_true(self):
"""
Test that GraphRagResponseTranslator returns is_final=True
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
when end_of_session=True.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("graph-rag")
response = GraphRagResponse(
response="A small domesticated mammal.",
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
message_type="chunk",
end_of_stream=True,
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
end_of_session=True,
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
assert is_final is True, "is_final must be True when end_of_session=True"
assert response_dict["response"] == "A small domesticated mammal."
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
assert response_dict["end_of_session"] is True
assert response_dict["message_type"] == "chunk"
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
def test_graph_rag_translator_is_final_with_end_of_session_false(self):
"""
Test that GraphRagResponseTranslator returns is_final=False
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
when end_of_session=False (even if end_of_stream=True).
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("graph-rag")
response = GraphRagResponse(
response="Chunk 1",
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
message_type="chunk",
end_of_stream=False,
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
end_of_session=False,
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
assert is_final is False, "is_final must be False when end_of_session=False"
assert response_dict["response"] == "Chunk 1"
GraphRAG Query-Time Explainability (#677) Implements full explainability pipeline for GraphRAG queries, enabling traceability from answers back to source documents. Renamed throughout for clarity: - provenance_callback → explain_callback - provenance_id → explain_id - provenance_collection → explain_collection - message_type "provenance" → "explain" - Queue name "provenance" → "explainability" GraphRAG queries now emit explainability events as they execute: 1. Session - query text and timestamp 2. Retrieval - edges retrieved from subgraph 3. Selection - selected edges with LLM reasoning (JSONL with id + reasoning) 4. Answer - reference to synthesized response Events stream via explain_callback during query(), enabling real-time UX. - Answers stored in librarian service (not inline in graph - too large) - Document ID as URN: urn:trustgraph:answer:{session_id} - Graph stores tg:document reference (IRI) to librarian document - Added librarian producer/consumer to graph-rag service - get_labelgraph() now returns (labeled_edges, uri_map) - uri_map maps edge_id(label_s, label_p, label_o) → (uri_s, uri_p, uri_o) - Explainability data stores original URIs, not labels - Enables tracing edges back to reifying statements via tg:reifies - Added serialize_triple() to query service (matches storage format) - get_term_value() now handles TRIPLE type terms - Enables querying by quoted triple in object position: ?stmt tg:reifies <<s p o>> - Displays real-time explainability events during query - Resolves rdfs:label for edge components (s, p, o) - Traces source chain via prov:wasDerivedFrom to root document - Output: "Source: Chunk 1 → Page 2 → Document Title" - Label caching to avoid repeated queries GraphRagResponse: - explain_id: str | None - explain_collection: str | None - message_type: str ("chunk" or "explain") - end_of_session: bool trustgraph-base/trustgraph/provenance/: - namespaces.py - Added TG_DOCUMENT predicate - triples.py - answer_triples() supports document_id reference - uris.py - Added edge_selection_uri() trustgraph-base/trustgraph/schema/services/retrieval.py: - GraphRagResponse with explain_id, explain_collection, end_of_session trustgraph-flow/trustgraph/retrieval/graph_rag/: - graph_rag.py - URI preservation, streaming answer accumulation - rag.py - Librarian integration, real-time explain emission trustgraph-flow/trustgraph/query/triples/cassandra/service.py: - Quoted triple serialization for query matching trustgraph-cli/trustgraph/cli/invoke_graph_rag.py: - Full explainability display with label resolution and source tracing
2026-03-10 10:00:01 +00:00
assert response_dict["end_of_session"] is False
def test_graph_rag_translator_provenance_message(self):
"""
Test that GraphRagResponseTranslator handles provenance messages.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("graph-rag")
response = GraphRagResponse(
response="",
message_type="explain",
explain_id="urn:trustgraph:session:abc123",
end_of_stream=False,
end_of_session=False,
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is False
assert response_dict["message_type"] == "explain"
assert response_dict["explain_id"] == "urn:trustgraph:session:abc123"
def test_graph_rag_translator_end_of_stream_not_final(self):
"""
Test that end_of_stream=True alone does NOT make is_final=True.
The session continues with provenance messages after LLM stream completes.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("graph-rag")
response = GraphRagResponse(
response="Final chunk",
message_type="chunk",
end_of_stream=True,
end_of_session=False, # Session continues with provenance
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is False, "end_of_stream=True should NOT make is_final=True"
assert response_dict["end_of_stream"] is True
assert response_dict["end_of_session"] is False
def test_document_rag_translator_is_final_with_end_of_stream_true(self):
"""
Test that DocumentRagResponseTranslator returns is_final=True
when end_of_stream=True.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("document-rag")
response = DocumentRagResponse(
response="A document about cats.",
end_of_stream=True,
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is True, "is_final must be True when end_of_stream=True"
assert response_dict["response"] == "A document about cats."
assert response_dict["end_of_stream"] is True
def test_document_rag_translator_is_final_with_end_of_stream_false(self):
"""
Test that DocumentRagResponseTranslator returns is_final=False
when end_of_stream=False.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("document-rag")
response = DocumentRagResponse(
response="Chunk 1",
end_of_stream=False,
error=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is False, "is_final must be False when end_of_stream=False"
assert response_dict["response"] == "Chunk 1"
assert response_dict["end_of_stream"] is False
@pytest.mark.contract
class TestAgentTranslatorCompletionFlags:
"""Contract tests for Agent response translator completion flags"""
def test_agent_translator_is_final_with_end_of_dialog_true(self):
"""
Test that AgentResponseTranslator returns is_final=True
when end_of_dialog=True.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("agent")
response = AgentResponse(
answer="4",
error=None,
thought=None,
observation=None,
end_of_message=True,
end_of_dialog=True
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is True, "is_final must be True when end_of_dialog=True"
assert response_dict["answer"] == "4"
assert response_dict["end_of_dialog"] is True
def test_agent_translator_is_final_with_end_of_dialog_false(self):
"""
Test that AgentResponseTranslator returns is_final=False
when end_of_dialog=False.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("agent")
response = AgentResponse(
answer=None,
error=None,
thought="I need to solve this.",
observation=None,
end_of_message=True,
end_of_dialog=False
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is False, "is_final must be False when end_of_dialog=False"
assert response_dict["thought"] == "I need to solve this."
assert response_dict["end_of_dialog"] is False
def test_agent_translator_is_final_fallback_with_answer(self):
"""
Test that AgentResponseTranslator returns is_final=True
when answer is present (fallback for legacy responses).
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("agent")
# Legacy response without end_of_dialog flag
response = AgentResponse(
answer="4",
error=None,
thought=None,
observation=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is True, "is_final must be True when answer is present (legacy fallback)"
assert response_dict["answer"] == "4"
def test_agent_translator_intermediate_message_is_not_final(self):
"""
Test that intermediate messages (thought/observation) return is_final=False.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("agent")
# Test thought message
thought_response = AgentResponse(
answer=None,
error=None,
thought="Processing...",
observation=None,
end_of_message=True,
end_of_dialog=False
)
# Act
thought_dict, thought_is_final = translator.from_response_with_completion(thought_response)
# Assert
assert thought_is_final is False, "Thought message must not be final"
# Test observation message
observation_response = AgentResponse(
answer=None,
error=None,
thought=None,
observation="Result found",
end_of_message=True,
end_of_dialog=False
)
# Act
obs_dict, obs_is_final = translator.from_response_with_completion(observation_response)
# Assert
assert obs_is_final is False, "Observation message must not be final"
def test_agent_translator_streaming_format_with_end_of_dialog(self):
"""
Test that streaming format messages use end_of_dialog for is_final.
"""
# Arrange
translator = TranslatorRegistry.get_response_translator("agent")
# Streaming format with end_of_dialog=True
response = AgentResponse(
chunk_type="answer",
content="",
end_of_message=True,
end_of_dialog=True,
answer=None,
error=None,
thought=None,
observation=None
)
# Act
response_dict, is_final = translator.from_response_with_completion(response)
# Assert
assert is_final is True, "Streaming format must use end_of_dialog for is_final"
assert response_dict["end_of_dialog"] is True