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lambda_agent/agent.py
@@ -96,8 +96,9 @@ def chat(self, user_input: str) -> str:
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# 4. Send ALL the tool responses back to the model
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# so it can continue reasoning based on the new information
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+ tool_content = types.Content(role="tool", parts=tool_responses)
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with Spinner():
- response = self.chat_session.send_message(tool_responses)
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+ response = self.chat_session.send_message(tool_content)
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continue # Start the loop over to see if it calls more tools
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else:
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# No more tool calls; the LLM has generated a final text response.
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