azure-ai-contentunderstanding-py

Topics in the source

• Azure AI Content Understanding SDK for Python
• Installation
• Environment Variables
• Authentication & Lifecycle
• Core Workflow
• Prebuilt Analyzers
• Analyze Document
• Access Document Content Details

Multimodal AI service that extracts semantic content from documents, video, audio, and image files for RAG and automated workflows. 🔑 Two rules apply to every code sample below: 1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation. - Local dev: DefaultAzureCredential works as-is. - Production: set AZURETOKENCREDENTIALS=prod (or AZURETOKENCREDENTIALS= ) to constrain the credential chain to production-safe credentials. 2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically: - Sync: with (...) as client: - Async: async with (...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio) Snippets may abbreviate this setup, but production code should always follow both rules. Content Understanding operations are asynchronous long-running operations: 1. Begin Analysis — Start the analysis operation with beginanalyze() (returns a poller) 2. Poll for Results — Poll until analysis completes (SDK handles thi

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