Split Analysis into Analysis+ToolUse and Observation, add message_id (#747)

Refactor agent provenance so that the decision (thought + tool
selection) and the result (observation) are separate DAG entities:

  Question ← Analysis+ToolUse ← Observation ← ... ← Conclusion

Analysis gains tg:ToolUse as a mixin RDF type and is emitted
before tool execution via an on_action callback in react().
This ensures sub-traces (e.g. GraphRAG) appear after their
parent Analysis in the streaming event order.

Observation becomes a standalone prov:Entity with tg:Observation
type, emitted after tool execution. The linear DAG chain runs
through Observation — subsequent iterations and the Conclusion
derive from it, not from the Analysis.

message_id is populated on streaming AgentResponse for thought
and observation chunks, using the provenance URI of the entity
being built. This lets clients group streamed chunks by entity.

Wire changes:
- provenance/agent.py: Add ToolUse type, new
  agent_observation_triples(), remove observation from iteration
- agent_manager.py: Add on_action callback between reason() and
  tool execution
- orchestrator/pattern_base.py: Split emit, wire message_id,
  chain through observation URIs
- orchestrator/react_pattern.py: Emit Analysis via on_action
  before tool runs
- agent/react/service.py: Same for non-orchestrator path
- api/explainability.py: New Observation class, updated dispatch
  and chain walker
- api/types.py: Add message_id to AgentThought/AgentObservation
- cli: Render Observation separately, [analysis: tool] labels

trustgraph-base/trustgraph/schema/services/retrieval.py

@@ -18,6 +18,7 @@ class GraphRagQuery:
     edge_score_limit: int = 0
     edge_limit: int = 0
     streaming: bool = False
+    parent_uri: str = ""
 
 @dataclass
 class GraphRagResponse: