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Modernize image serving example - #190

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Gia Mondragon (gmndrg) wants to merge 3 commits into
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gmndrg/agentic-retrieval-image-serving
Open

Modernize image serving example#190
Gia Mondragon (gmndrg) wants to merge 3 commits into
mainfrom
gmndrg/agentic-retrieval-image-serving

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@gmndrg

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Summary

  • Update the image-serving notebook to the current preview Azure AI Search SDK.
  • Use Microsoft Foundry endpoints and identity-based authentication.
  • Demonstrate managed ingestion, image-serving statistics, and asset download.
  • Remove internal regression-fixture controls from the public sample.

Validation

  • Notebook JSON is valid.
  • All 10 Python code cells compile.
  • The end-to-end workflow was validated against Azure resources.

haileytap

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@gmndrg

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Addressed the feedback from former inline discussion 3816531732 in 08ee850.

The notebook now states that retrieve reports aggregate image-serving activity without dedicated fields for individual asset-store paths or image bytes. It separately identifies the wildcard index query as the source of selected_image_path, and the download section and variable names now describe an independently selected indexed image asset rather than a retrieve-response reference.

The original inline comment currently returns 404 and no longer has a review-thread object, so it can't be replied to or resolved directly.

@haileytap Hailey Tapia (haileytap) left a comment

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Approved pending some minor suggestions.

@@ -5,30 +5,31 @@
"id": "92ebfca4",
"metadata": {},
"source": [

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Please add (preview) labels to applicable functionality in this notebook.

"metadata": {},
"source": [
"# Example: Image Serving with Azure Blob Knowledge Source\n",
"# Example: Image serving for agentic retrieval using Python\n",

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The C# and Python samples describe the same end-to-end workflow, but their opening content differs in positioning, terminology, prerequisite structure, and setup flow. Could we align the companion samples so that readers receive the same conceptual framing and requirements regardless of language?

In particular:

  • Use parallel introductory wording for the managed-ingestion and indexed-image workflows.

  • Include the same distinction from the classic OcrSkill and normalized_images approach.

  • Use unordered prerequisites in the same order and at the same level of detail. To reduce duplication and maintenance, I recommend replacing both prerequisite lists with: "For required resources and permissions, see Surface document-embedded images in agentic retrieval (preview)." Keep only language-specific requirements in each sample.

  • If desired, keep sequential workflow steps under a separate "Flow" section.

Comment thread image-serving-example/image_serving.ipynb
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2 participants