Incorporate evaluation script and GitHub workflow #103
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aprilk-ms
commented
May 2, 2025
| with: | ||
| azure-aiproject-connection-string: ${{ vars.AZURE_EXISTING_AIPROJECT_CONNECTION_STRING || vars.AZURE_AIPROJECT_CONNECTION_STRING }} | ||
| deployment-name: ${{ vars.AZURE_AI_AGENT_DEPLOYMENT_NAME }} | ||
| agent-ids: ${{ vars.AZURE_EXISTING_AGENT_ID || vars.AZURE_AI_AGENT_ID }} |
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Can we make sure AZURE_EXISTING_AGENT_ID gets written to .env during startup?
aprilk-ms
commented
May 2, 2025
evals/test-data.json
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| @@ -0,0 +1,10 @@ | |||
| [ | |||
| { | |||
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TODO: Update to queries more relevant for this app
| tool_call_accuracy = ToolCallAccuracyEvaluator(model_config=model_config) | ||
| intent_resolution = IntentResolutionEvaluator(model_config=model_config) | ||
| task_adherence = TaskAdherenceEvaluator(model_config=model_config) | ||
| results = evaluate( |
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Need to make sure both the user (whoever did azd up) has access to storage, otherwise uploading to AI Foundry won't work out of the box
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evaluate.py script output looks like this: