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[bugfix] no shield_call when there's no shields configured (#642)
# What does this PR do? **Why** - When AgentConfig has no `input_shields` / `output_shields` defined, we still outputs a shield_call step with violation=None. This is impossible to distinguish the case b/w (1) no violation from running shields v.s. (2) no shields call **What** - We should not have a shield_call step when no `input_shields` / `output_shields` are defined. - Also removes a never reached try/catch code block in agent loop. `run_multiple_shields` is never called in the try block (verified by stacktrace print) **Side Note** - pre-commit fix ## Test Plan Tested w/ DirectClient via: https://gist.github.com/yanxi0830/b48f2a53b6f5391b9ff1e39992bc05b3 **No Shields** <img width="858" alt="image" src="https://github.com/user-attachments/assets/67319370-329f-4954-bd16-d21ce54c6ebf" /> **With Input + Output Shields** <img width="854" alt="image" src="https://github.com/user-attachments/assets/75ab1bee-3ba9-4549-ab51-23210be83da7" /> **Input Shields Only** <img width="858" alt="image" src="https://github.com/user-attachments/assets/1897206b-13dd-4ea5-92c2-b39bf68e9286" /> E2E pytest ``` LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v ./tests/client-sdk/agents/test_agents.py ``` ## Sources Please link relevant resources if necessary. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests.
This commit is contained in:
Xi Yan
GitHub
parent
c2f7905fa4
commit
99f331f5c8
3 changed files with 84 additions and 113 deletions
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@ -239,13 +239,14 @@ class ChatAgent(ShieldRunnerMixin):
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# return a "final value" for the `yield from` statement. we simulate that by yielding a
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# final boolean (to see whether an exception happened) and then explicitly testing for it.
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async for res in self.run_multiple_shields_wrapper(
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turn_id, input_messages, self.input_shields, "user-input"
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):
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if isinstance(res, bool):
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return
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else:
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yield res
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if len(self.input_shields) > 0:
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async for res in self.run_multiple_shields_wrapper(
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turn_id, input_messages, self.input_shields, "user-input"
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):
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if isinstance(res, bool):
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return
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else:
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yield res
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async for res in self._run(
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session_id, turn_id, input_messages, attachments, sampling_params, stream
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@ -262,13 +263,14 @@ class ChatAgent(ShieldRunnerMixin):
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# for output shields run on the full input and output combination
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messages = input_messages + [final_response]
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async for res in self.run_multiple_shields_wrapper(
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turn_id, messages, self.output_shields, "assistant-output"
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):
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if isinstance(res, bool):
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return
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else:
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yield res
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if len(self.output_shields) > 0:
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async for res in self.run_multiple_shields_wrapper(
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turn_id, messages, self.output_shields, "assistant-output"
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):
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if isinstance(res, bool):
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return
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else:
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yield res
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yield final_response
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@ -531,106 +533,72 @@ class ChatAgent(ShieldRunnerMixin):
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input_messages = input_messages + [message]
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else:
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log.info(f"{str(message)}")
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try:
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tool_call = message.tool_calls[0]
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tool_call = message.tool_calls[0]
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name = tool_call.tool_name
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if not isinstance(name, BuiltinTool):
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yield message
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return
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step_id = str(uuid.uuid4())
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepStartPayload(
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step_type=StepType.tool_execution.value,
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step_id=step_id,
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)
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)
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)
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.tool_execution.value,
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step_id=step_id,
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tool_call=tool_call,
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)
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)
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)
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with tracing.span(
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"tool_execution",
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{
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"tool_name": tool_call.tool_name,
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"input": message.model_dump_json(),
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},
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) as span:
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result_messages = await execute_tool_call_maybe(
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self.tools_dict,
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[message],
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)
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assert (
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len(result_messages) == 1
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), "Currently not supporting multiple messages"
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result_message = result_messages[0]
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span.set_attribute("output", result_message.model_dump_json())
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepCompletePayload(
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step_type=StepType.tool_execution.value,
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step_details=ToolExecutionStep(
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step_id=step_id,
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turn_id=turn_id,
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tool_calls=[tool_call],
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tool_responses=[
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ToolResponse(
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call_id=result_message.call_id,
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tool_name=result_message.tool_name,
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content=result_message.content,
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)
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],
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),
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)
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)
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)
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# TODO: add tool-input touchpoint and a "start" event for this step also
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# but that needs a lot more refactoring of Tool code potentially
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepCompletePayload(
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step_type=StepType.shield_call.value,
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step_details=ShieldCallStep(
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step_id=str(uuid.uuid4()),
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turn_id=turn_id,
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violation=None,
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),
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)
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)
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)
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except SafetyException as e:
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepCompletePayload(
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step_type=StepType.shield_call.value,
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step_details=ShieldCallStep(
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step_id=str(uuid.uuid4()),
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turn_id=turn_id,
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violation=e.violation,
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),
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)
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)
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)
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yield CompletionMessage(
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content=str(e),
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stop_reason=StopReason.end_of_turn,
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)
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yield False
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name = tool_call.tool_name
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if not isinstance(name, BuiltinTool):
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yield message
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return
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step_id = str(uuid.uuid4())
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepStartPayload(
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step_type=StepType.tool_execution.value,
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step_id=step_id,
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)
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)
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)
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.tool_execution.value,
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step_id=step_id,
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tool_call=tool_call,
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)
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)
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)
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with tracing.span(
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"tool_execution",
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{
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"tool_name": tool_call.tool_name,
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"input": message.model_dump_json(),
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},
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) as span:
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result_messages = await execute_tool_call_maybe(
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self.tools_dict,
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[message],
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)
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assert (
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len(result_messages) == 1
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), "Currently not supporting multiple messages"
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result_message = result_messages[0]
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span.set_attribute("output", result_message.model_dump_json())
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepCompletePayload(
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step_type=StepType.tool_execution.value,
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step_details=ToolExecutionStep(
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step_id=step_id,
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turn_id=turn_id,
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tool_calls=[tool_call],
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tool_responses=[
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ToolResponse(
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call_id=result_message.call_id,
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tool_name=result_message.tool_name,
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content=result_message.content,
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)
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],
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),
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)
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)
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)
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# TODO: add tool-input touchpoint and a "start" event for this step also
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# but that needs a lot more refactoring of Tool code potentially
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if out_attachment := interpret_content_as_attachment(
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result_message.content
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):
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@ -7,6 +7,7 @@
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from typing import * # noqa: F403
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import json
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import uuid
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from botocore.client import BaseClient
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from llama_models.datatypes import CoreModelId
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@ -7,12 +7,14 @@
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from pathlib import Path
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from llama_models.sku_list import all_registered_models
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from llama_stack.apis.models import ModelInput
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from llama_stack.distribution.datatypes import Provider
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from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
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from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
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from llama_stack.providers.remote.inference.bedrock.bedrock import MODEL_ALIASES
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from llama_stack.apis.models import ModelInput
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from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
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def get_distribution_template() -> DistributionTemplate:
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providers = {
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