Minor agent tweaks (#692)

Update RAG and Agent clients for streaming message handling

GraphRAG now sends multiple message types in a stream:
- 'explain' messages with explain_id and explain_graph for
  provenance
- 'chunk' messages with response text fragments
- end_of_session marker for stream completion

Updated all clients to handle this properly:

CLI clients (trustgraph-base/trustgraph/clients/):
- graph_rag_client.py: Added chunk_callback and explain_callback
- document_rag_client.py: Added chunk_callback and explain_callback
- agent_client.py: Added think, observe, answer_callback,
  error_callback

Internal clients (trustgraph-base/trustgraph/base/):
- graph_rag_client.py: Async callbacks for streaming
- agent_client.py: Async callbacks for streaming

All clients now:
- Route messages by chunk_type/message_type
- Stream via optional callbacks for incremental delivery
- Wait for proper completion signals
(end_of_dialog/end_of_session/end_of_stream)
- Accumulate and return complete response for callers not using
  callbacks

Updated callers:
- extract/kg/agent/extract.py: Uses new invoke(question=...) API
- tests/integration/test_agent_kg_extraction_integration.py:
  Updated mocks

This fixes the agent infinite loop issue where knowledge_query was
returning the first 'explain' message (empty response) instead of
waiting for the actual answer chunks.

Concurrency in triples query

trustgraph-flow/trustgraph/extract/kg/agent/extract.py

@@ -183,24 +183,8 @@ class Processor(FlowProcessor):
 
             logger.debug(f"Agent prompt: {prompt}")
 
-            async def handle(response):
-
-                logger.debug(f"Agent response: {response}")
-
-                if response.error is not None:
-                    if response.error.message:
-                        raise RuntimeError(str(response.error.message))
-                    else:
-                        raise RuntimeError(str(response.error))
-
-                if response.answer is not None:
-                    return True
-                else:
-                    return False
-            
             # Send to agent API
             agent_response = await flow("agent-request").invoke(
-                recipient = handle,
                 question = prompt
             )