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Add unified explainability support and librarian storage for (#693)
Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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24 changed files with 2736 additions and 846 deletions
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@ -59,6 +59,15 @@ class AgentResponseTranslator(MessageTranslator):
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result["end_of_message"] = getattr(obj, "end_of_message", False)
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result["end_of_dialog"] = getattr(obj, "end_of_dialog", False)
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# Include explainability fields if present
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explain_id = getattr(obj, "explain_id", None)
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if explain_id:
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result["explain_id"] = explain_id
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explain_graph = getattr(obj, "explain_graph", None)
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if explain_graph is not None:
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result["explain_graph"] = explain_graph
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# Always include error if present
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if hasattr(obj, 'error') and obj.error and obj.error.message:
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result["error"] = {"message": obj.error.message, "code": obj.error.code}
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@ -34,7 +34,12 @@ class DocumentRagResponseTranslator(MessageTranslator):
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def from_pulsar(self, obj: DocumentRagResponse) -> Dict[str, Any]:
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result = {}
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# Include response content (even if empty string)
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# Include message_type for distinguishing chunk vs explain messages
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message_type = getattr(obj, "message_type", "")
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if message_type:
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result["message_type"] = message_type
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# Include response content for chunk messages
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if obj.response is not None:
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result["response"] = obj.response
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@ -48,9 +53,12 @@ class DocumentRagResponseTranslator(MessageTranslator):
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if explain_graph is not None:
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result["explain_graph"] = explain_graph
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# Include end_of_stream flag
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# Include end_of_stream flag (LLM stream complete)
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result["end_of_stream"] = getattr(obj, "end_of_stream", False)
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# Include end_of_session flag (entire session complete)
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result["end_of_session"] = getattr(obj, "end_of_session", False)
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# Always include error if present
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if hasattr(obj, 'error') and obj.error and obj.error.message:
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result["error"] = {"message": obj.error.message, "type": obj.error.type}
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@ -59,7 +67,8 @@ class DocumentRagResponseTranslator(MessageTranslator):
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def from_response_with_completion(self, obj: DocumentRagResponse) -> Tuple[Dict[str, Any], bool]:
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"""Returns (response_dict, is_final)"""
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is_final = getattr(obj, 'end_of_stream', False)
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# Session is complete when end_of_session is True
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is_final = getattr(obj, 'end_of_session', False)
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return self.from_pulsar(obj), is_final
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