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feat: separate agent payload from hivemind payload! #40
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,19 @@ | ||
| from pydantic import BaseModel, Field | ||
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| class AgentQueryPayload(BaseModel): | ||
| community_id: str = Field( | ||
| ..., description="the community id data to use for answering" | ||
| ) | ||
| query: str = Field(..., description="the user query to ask llm") | ||
| enable_answer_skipping: bool = Field( | ||
| False, | ||
| description=( | ||
| "skip answering questions with non-relevant retrieved information" | ||
| "having this, it could provide `None` for response and source_nodes" | ||
| ), | ||
| ) | ||
| chat_id: str = Field( | ||
| default="", | ||
| description="the chat id to use for answering", | ||
| ) |
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Activity accepts AgentQueryPayload but workflow passes HivemindQueryPayload — type contract broken
run_hivemind_agent_activitynow expectsAgentQueryPayload, yet the workflow below still calls it with aHivemindQueryPayloadinstance (see lines 219-224). At runtime this “works” thanks to duck typing, but:• type checkers will flag an error
• field sets can silently diverge, causing subtle bugs
Align both sides to the same model.
and remove the stale
HivemindQueryPayloadimport if no longer needed.📝 Committable suggestion
🤖 Prompt for AI Agents