Learn about the Python code samples that demonstrate the functionality and workflow of an Azure AI Search solution. These samples use the Azure AI Search client library for the Azure SDK for Python, which you can explore through the following links.
SDK samplesCode samples from the Azure SDK development team demonstrate API usage. You can find these samples in azure-sdk-for-python/tree/main/sdk/search/azure-search-documents/samples on GitHub.
Doc samplesCode samples from the Azure AI Search team demonstrate features and workflows. Many of these samples are referenced in tutorials, quickstarts, and how-to articles. You can find these samples in Azure-Samples/azure-search-python-samples on GitHub.
Demosazure-search-vector-samples on GitHub provides a comprehensive collection of samples for vector search scenarios, organized by scenario or technology.
azure-search-openai-demo is a ChatGPT-like experience over enterprise data with Azure OpenAI Python code showing how to use Azure AI Search with the large language models in Azure OpenAI. For background, see this Tech Community blog post.
aisearch-openai-rag-audio is "voice to RAG". This sample demonstrates a simple architecture for voice-based generative AI applications that enables Azure AI Search RAG on top of the real-time audio API with full-duplex audio streaming from client devices, while securely handling access to both the model and retrieval system. Backend code is written in Python, while frontend code is written in JavaScript. For an introduction, watch this video.
AcceleratorsAn accelerator is an end-to-end solution that includes code and documentation that you can adapt for your own implementation of a specific scenario.
Repository Description RAG Experiment Accelerator Conduct experiments and evaluations using Azure AI Search and the RAG pattern. This accelerator has code for loading multiple data sources, using a variety of models, and creating a variety of search indexes and queries. Other samplesThe following samples are also published by the Azure AI Search team but aren't referenced in documentation. Associated readme files provide usage instructions.
Repository Description index-backup-and-restore.ipynb Uses the azure.search.documents library in the Azure SDK for Python to make a local copy of the retrievable fields of a search index and then push those fields to a new search index. resumable-index-backup-restore This sample accommodates larger indexes exceeding 100,000 documents.Tip
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