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Add deep QA rich artifacts with research process

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Yiorgis Gozadinos 2025-10-10 15:01:30 +03:00
parent 9aad6b65b8
commit e53fb868df
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1 changed files with 59 additions and 11 deletions
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70
src/haiku/rag/a2a.py
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@ -393,7 +393,9 @@ def create_a2a_app(db_path: Path):
async with HaikuRAG(db_path) as client:
if skill == "deep-qa":
# Run deep QA graph
deep_result = await self.run_deep_qa(client, question)
deep_result, deep_state = await self.run_deep_qa(
client, question
)
# Build response message
response_message = Message(
@ -403,14 +405,10 @@ def create_a2a_app(db_path: Path):
message_id=str(uuid.uuid4()),
)
# Build artifacts (basic for now, will be enhanced in commit 3)
artifacts = [
Artifact(
artifact_id=str(uuid.uuid4()),
name="answer",
parts=[TextPart(kind="text", text=deep_result.answer)],
)
]
# Build rich artifacts with research breakdown
artifacts = self.build_deep_qa_artifacts(
deep_result, deep_state
)
await self.storage.update_task(
task["id"],
@ -477,7 +475,7 @@ def create_a2a_app(db_path: Path):
question: User's question
Returns:
DeepQAAnswer with answer and sources
Tuple of (DeepQAAnswer, DeepQAState) with answer and state
"""
graph = build_deep_qa_graph()
context = DeepQAContext(original_question=question, use_citations=False)
@ -488,7 +486,7 @@ def create_a2a_app(db_path: Path):
)
result = await graph.run(start_node=start_node, state=state, deps=deps)
return result.output
return result.output, state
async def cancel_task(self, params: TaskIdParams) -> None:
"""Cancel a task - not implemented for this worker."""
@ -512,6 +510,56 @@ def create_a2a_app(db_path: Path):
)
]
def build_deep_qa_artifacts(self, result, state: DeepQAState) -> list[Artifact]:
"""Build rich artifacts from deep QA result.
Args:
result: DeepQAAnswer with final answer
state: DeepQAState with research process details
Returns:
List of artifacts including answer and research breakdown
"""
artifacts = [
# Final answer artifact
Artifact(
artifact_id=str(uuid.uuid4()),
name="answer",
parts=[TextPart(kind="text", text=result.answer)],
)
]
# Add research process artifact with sub-questions and answers
if state.context.qa_responses:
research_data = {
"original_question": state.context.original_question,
"iterations": state.iterations,
"sub_questions_answered": [
{
"question": qa.query,
"answer": qa.answer,
"sources": qa.sources,
}
for qa in state.context.qa_responses
],
}
artifacts.append(
Artifact(
artifact_id=str(uuid.uuid4()),
name="research_process",
parts=[
DataPart(
kind="data",
data=research_data,
metadata={"type": "deep_qa_research"},
)
],
)
)
return artifacts
worker = ConversationalWorker(storage=storage, broker=broker)
# Create FastA2A app with custom worker lifecycle