Adding explainability to the ReACT agent (#689)

* Added tech spec

* Add provenance recording to React agent loop

Enables agent sessions to be traced and debugged using the same
explainability infrastructure as GraphRAG. Agent traces record:
- Session start with query and timestamp
- Each iteration's thought, action, arguments, and observation
- Final answer with derivation chain

Changes:
- Add session_id and collection fields to AgentRequest schema
- Add agent predicates (TG_THOUGHT, TG_ACTION, etc.) to namespaces
- Create agent provenance triple generators in provenance/agent.py
- Register explainability producer in agent service
- Emit provenance triples during agent execution
- Update CLI tools to detect and render agent traces alongside GraphRAG

* Updated explainability taxonomy:

GraphRAG: tg:Question → tg:Exploration → tg:Focus → tg:Synthesis

Agent: tg:Question → tg:Analysis(s) → tg:Conclusion

All entities also have their PROV-O type (prov:Activity or prov:Entity).

Updated commit message:

Add provenance recording to React agent loop

Enables agent sessions to be traced and debugged using the same
explainability infrastructure as GraphRAG.

Entity types follow human reasoning patterns:
- tg:Question - the user's query (shared with GraphRAG)
- tg:Analysis - each think/act/observe cycle
- tg:Conclusion - the final answer

Also adds explicit TG types to GraphRAG entities:
- tg:Question, tg:Exploration, tg:Focus, tg:Synthesis

All types retain their PROV-O base types (prov:Activity, prov:Entity).

Changes:
- Add session_id and collection fields to AgentRequest schema
- Add explainability entity types to namespaces.py
- Create agent provenance triple generators
- Register explainability producer in agent service
- Emit provenance triples during agent execution
- Update CLI tools to detect and render both trace types

* Document RAG explainability is now complete. Here's a summary of the
changes made:

Schema Changes:
- trustgraph-base/trustgraph/schema/services/retrieval.py: Added
  explain_id and explain_graph fields to DocumentRagResponse
- trustgraph-base/trustgraph/messaging/translators/retrieval.py:
  Updated translator to handle explainability fields

Provenance Changes:
- trustgraph-base/trustgraph/provenance/namespaces.py: Added
  TG_CHUNK_COUNT and TG_SELECTED_CHUNK predicates
- trustgraph-base/trustgraph/provenance/uris.py: Added
  docrag_question_uri, docrag_exploration_uri, docrag_synthesis_uri
  generators
- trustgraph-base/trustgraph/provenance/triples.py: Added
  docrag_question_triples, docrag_exploration_triples,
  docrag_synthesis_triples builders
- trustgraph-base/trustgraph/provenance/__init__.py: Exported all
  new Document RAG functions and predicates

Service Changes:
- trustgraph-flow/trustgraph/retrieval/document_rag/document_rag.py:
  Added explainability callback support and triple emission at each
  phase (Question → Exploration → Synthesis)
- trustgraph-flow/trustgraph/retrieval/document_rag/rag.py:
  Registered explainability producer and wired up the callback

Documentation:
- docs/tech-specs/agent-explainability.md: Added Document RAG entity
  types and provenance model documentation

Document RAG Provenance Model:
Question (urn:trustgraph:docrag:{uuid})
    │
    │  tg:query, prov:startedAtTime
    │  rdf:type = prov:Activity, tg:Question
    │
    ↓ prov:wasGeneratedBy
    │
Exploration (urn:trustgraph:docrag:{uuid}/exploration)
    │
    │  tg:chunkCount, tg:selectedChunk (multiple)
    │  rdf:type = prov:Entity, tg:Exploration
    │
    ↓ prov:wasDerivedFrom
    │
Synthesis (urn:trustgraph:docrag:{uuid}/synthesis)
    │
    │  tg:content = "The answer..."
    │  rdf:type = prov:Entity, tg:Synthesis

* Specific subtype that makes the retrieval mechanism immediately
obvious:

System: GraphRAG
TG Types on Question: tg:Question, tg:GraphRagQuestion
URI Pattern: urn:trustgraph:question:{uuid}
────────────────────────────────────────
System: Document RAG
TG Types on Question: tg:Question, tg:DocRagQuestion
URI Pattern: urn:trustgraph:docrag:{uuid}
────────────────────────────────────────
System: Agent
TG Types on Question: tg:Question, tg:AgentQuestion
URI Pattern: urn:trustgraph:agent:{uuid}
Files modified:
- trustgraph-base/trustgraph/provenance/namespaces.py - Added
TG_GRAPH_RAG_QUESTION, TG_DOC_RAG_QUESTION, TG_AGENT_QUESTION
- trustgraph-base/trustgraph/provenance/triples.py - Added subtype to
question_triples and docrag_question_triples
- trustgraph-base/trustgraph/provenance/agent.py - Added subtype to
agent_session_triples
- trustgraph-base/trustgraph/provenance/__init__.py - Exported new types
- docs/tech-specs/agent-explainability.md - Documented the subtypes

This allows:
- Query all questions: ?q rdf:type tg:Question
- Query only GraphRAG: ?q rdf:type tg:GraphRagQuestion
- Query only Document RAG: ?q rdf:type tg:DocRagQuestion
- Query only Agent: ?q rdf:type tg:AgentQuestion

* Fixed tests

trustgraph-base/trustgraph/provenance/namespaces.py

@@ -59,7 +59,7 @@ TG_SOURCE_TEXT = TG + "sourceText"
 TG_SOURCE_CHAR_OFFSET = TG + "sourceCharOffset"
 TG_SOURCE_CHAR_LENGTH = TG + "sourceCharLength"
 
-# Query-time provenance predicates
+# Query-time provenance predicates (GraphRAG)
 TG_QUERY = TG + "query"
 TG_EDGE_COUNT = TG + "edgeCount"
 TG_SELECTED_EDGE = TG + "selectedEdge"
@@ -68,6 +68,30 @@ TG_REASONING = TG + "reasoning"
 TG_CONTENT = TG + "content"
 TG_DOCUMENT = TG + "document"  # Reference to document in librarian
 
+# Query-time provenance predicates (DocumentRAG)
+TG_CHUNK_COUNT = TG + "chunkCount"
+TG_SELECTED_CHUNK = TG + "selectedChunk"
+
+# Explainability entity types (shared)
+TG_QUESTION = TG + "Question"
+TG_EXPLORATION = TG + "Exploration"
+TG_FOCUS = TG + "Focus"
+TG_SYNTHESIS = TG + "Synthesis"
+TG_ANALYSIS = TG + "Analysis"
+TG_CONCLUSION = TG + "Conclusion"
+
+# Question subtypes (to distinguish retrieval mechanism)
+TG_GRAPH_RAG_QUESTION = TG + "GraphRagQuestion"
+TG_DOC_RAG_QUESTION = TG + "DocRagQuestion"
+TG_AGENT_QUESTION = TG + "AgentQuestion"
+
+# Agent provenance predicates
+TG_THOUGHT = TG + "thought"
+TG_ACTION = TG + "action"
+TG_ARGUMENTS = TG + "arguments"
+TG_OBSERVATION = TG + "observation"
+TG_ANSWER = TG + "answer"
+
 # Named graph URIs for RDF datasets
 # These separate different types of data while keeping them in the same collection
 GRAPH_DEFAULT = ""                       # Core knowledge facts (triples extracted from documents)