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Remove unneeded infra
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docs/safety_evaluation.md

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# Evaluating the RAG answer safety
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# Evaluating RAG answer safety
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When deploying a RAG app to production, you should evaluate the safety of the answers generated by the RAG flow. This is important to ensure that the answers are appropriate and do not contain any harmful or sensitive content. This project includes scripts that use Azure AI services to simulate an adversarial user and evaluate the safety of the answers generated in response to those adversarial queries.
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evals/safety_results.json

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{
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"hate_unfairness": {
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"low_count": 20,
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"score_total": 8,
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"mean_score": 0.4,
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"low_count": 200,
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"score_total": 41,
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"mean_score": 0.205,
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"low_rate": 1.0
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},
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"sexual": {
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"low_count": 20,
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"score_total": 9,
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"mean_score": 0.45,
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"low_count": 200,
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"score_total": 34,
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"mean_score": 0.17,
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"low_rate": 1.0
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},
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"violence": {
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"low_count": 20,
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"score_total": 9,
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"mean_score": 0.45,
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"low_count": 200,
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"score_total": 34,
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"mean_score": 0.17,
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"low_rate": 1.0
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},
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"self_harm": {
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"low_count": 20,
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"score_total": 10,
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"mean_score": 0.5,
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"low_count": 200,
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"score_total": 35,
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"mean_score": 0.175,
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"low_rate": 1.0
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}
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}

infra/core/ai/ai-environment.bicep

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}
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}
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// Outputs
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// Resource Group
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output resourceGroupName string = resourceGroup().name
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// Hub
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output hubName string = hub.outputs.name
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output hubPrincipalId string = hub.outputs.principalId
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// Project
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output projectName string = project.outputs.name
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output projectPrincipalId string = project.outputs.principalId
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//Discoveryurl
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output discoveryUrl string = project.outputs.discoveryUrl

infra/core/ai/cognitiveservices.bicep

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