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Add model diagnostics to non-streaming APIs (#6150)\n\n### Motivation and Context\n\n\nAccording to the\n[ADR](https://github.com/microsoft/semantic-kernel/blob/main/docs/decisions/0044-OTel-semantic-convention.md),\nit's essential that SK provides the best developer experience while\ncomplying with the industry standards for observability in\ngenerative-AI-based applications.\n\n### Description\n\n\nThis PR adds instrumentation to the chat completion and text completion\nendpoints in all AI connectors.\n\nStreaming APIs will be worked on next.\nThe telemetry sample and the documentation will be updated in a separate\nPR.\n\n> Note that this is an ongoing effort, i.e. metrics and more events will\nbe added as the conventions evolve.\n\n### Contribution Checklist\n\n\n\n- [ ] The code builds clean without any errors or warnings\n- [ ] The PR follows the [SK Contribution\nGuidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)\nand the [pre-submission 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My number is: \nResult: true\n```\n\n### Contribution Checklist\n\n\n\n- [x] The code builds clean without any errors or warnings\n- [x] The PR follows the [SK Contribution\nGuidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)\nand the [pre-submission formatting\nscript](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)\nraises no violations\n- [x] All unit tests pass, and I have added new tests where possible\n- [x] I didn't break anyone :smile:","shortMessageHtmlLink":".Net: Example of prompt PII detection logic with Filters and Microsof…"}},{"before":null,"after":"f952e141698a06146a24d9c0ebea937d78761908","ref":"refs/heads/gh-readonly-queue/main/pr-6171-2d38fb939523ed0999728e96dd0897196784935f","pushedAt":"2024-05-10T16:43:49.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"github-merge-queue[bot]","name":null,"path":"/apps/github-merge-queue","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/9919?s=80&v=4"},"commit":{"message":".Net: Example of prompt PII detection logic with Filters and Microsoft Presidio (#6171)\n\n### Motivation and Context\n\n\n\nThis example shows how to implement Personal Identifiable Information\n(PII) detection logic with Filters using Microsoft Presidio service:\nhttps://github.com/microsoft/presidio.\n\nExample contains two filters:\n\nFirst filter is responsible for PII detection in prompt by using\nPresidio Text Analyzer. 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