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Merge branch 'main' into trace-based-sampling
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eng/pipelines/templates/steps/build-package-artifacts.yml

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@@ -109,7 +109,6 @@ steps:
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condition: and(succeeded(), or(eq(variables['ENABLE_EXTENSION_BUILD'], 'true'), eq('${{ parameters.ArtifactSuffix }}', 'linux')))
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- script: |
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sudo dpkg --configure -a
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sudo apt-get update
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sudo apt-get install -y qemu-user-static binfmt-support
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sudo update-binfmts --enable qemu-aarch64

eng/pipelines/templates/steps/install-portaudio.yml

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steps:
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- script: |
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if [[ "$AGENT_OS" == "Linux" ]]; then
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sudo dpkg --configure -a
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sudo apt-get update
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sudo apt-get install -y portaudio19-dev libasound2-dev
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elif [[ "$AGENT_OS" == "Darwin" ]]; then

sdk/ai/azure-ai-projects/samples/evaluations/agentic_evaluators/sample_tool_success.py renamed to sdk/ai/azure-ai-projects/samples/evaluations/agentic_evaluators/sample_tool_call_success.py

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for Tool Success evaluator using inline dataset content.
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USAGE:
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python sample_tool_success.py
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python sample_tool_call_success.py
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Before running the sample:
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@@ -71,18 +71,18 @@ def main() -> None:
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testing_criteria = [
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{
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"type": "azure_ai_evaluator",
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"name": "tool_success",
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"evaluator_name": "builtin.tool_success",
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"name": "tool_call_success",
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"evaluator_name": "builtin.tool_call_success",
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"initialization_parameters": {"deployment_name": f"{model_deployment_name}"},
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"data_mapping": {"tool_definitions": "{{item.tool_definitions}}", "response": "{{item.response}}"},
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}
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]
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print("Creating Eval Group")
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eval_object = client.evals.create(
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name="Test Tool Success Evaluator with inline data",
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data_source_config=data_source_config, # type: ignore
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testing_criteria=testing_criteria, # type: ignore
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name="Test Tool Call Success Evaluator with inline data",
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data_source_config=data_source_config, # type: ignore
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testing_criteria=testing_criteria, # type: ignore
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)
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print(f"Eval Group created")
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