Azure Samples
Popular repositories
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azure-search-openai-demo
azure-search-openai-demo PublicA sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
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cognitive-services-speech-sdk
cognitive-services-speech-sdk PublicSample code for the Microsoft Cognitive Services Speech SDK
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active-directory-aspnetcore-webapp-openidconnect-v2
active-directory-aspnetcore-webapp-openidconnect-v2 PublicAn ASP.NET Core Web App which lets sign-in users (including in your org, many orgs, orgs + personal accounts, sovereign clouds) and call Web APIs (including Microsoft Graph)
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Cognitive-Speech-TTS
Cognitive-Speech-TTS PublicMicrosoft Text-to-Speech API sample code in several languages, part of Cognitive Services.
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Repositories
- agent-openai-python-prompty-langchain-pinecone Public
Function calling for vector database lookup based on user question.
- rag-postgres-openai-python Public
A RAG app to ask questions about rows in a database table. Deployable on Azure Container Apps with PostgreSQL Flexible Server.
- contoso-chat-csharp-prompty Public
- azure-search-openai-demo Public
A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
- summarization-openai-python-promptflow Public
This solution converts speech to text and then processes and summarizes the text based on the prompt scenario.
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- chat-with-your-data-solution-accelerator Public
A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.
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- contoso-chat Public
This sample has the full End2End process of creating RAG application with Prompt Flow and AI Studio. It includes GPT 3.5 Turbo LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.