This repository contains demos and templates for building intelligent Apps using OpenAI on Azure.
Regions that this deployment can be executed:
- uksouth
- swedencentral
- canadaeast
- australiaeast
The following scenarios are implemented in this repository:
| Name | Description | Technology |
|---|---|---|
| Prompt Engineering | Basic prompt engineering examples | Azure Prompt Flow |
| Embeddings | Learning about embedding models for text and images | Azure OpenAI, Azure Computer Vision |
| Vector Search | Learning about low level retrieval augmented generation | Azure OpenAI, Azure AI Search |
| Orchestrated Vector Search | Learning about retrieval augmented generation with Orchestration | Azure OpenAI, Azure AI Search, LangChain, Streamlit |
| Persisting Chat Memory | Learning about persisting chat messages | Azure OpenAI, Azure AI Search, LangChain, Azure CosmosDB |
| Tracing Language Models | Learning about tracing language model invocations | Azure OpenAI, LangChain, Azure PromptFlow |
| Tracing Chat application | Learning about tracing a running application | Azure OpenAI, LangChain, Azure PromptFlow, Streamlit, Azure AI Search |
| Function Calling | Learning about using tools from a model | Azure OpenAI, Azure PromptFlow |
| Orchestrating tools | Learning about orchestrating tools from an application | Azure OpenAI, Azure PromptFlow, LangChain |
| Orchestrating multiple tools | Learning about multiple orchestrating tools from an application | Azure OpenAI, Azure PromptFlow, LangChain |
| Agentic RAG | Learning about using agentic retrieval augmented generation | Azure OpenAI, Azure PromptFlow, LangChain, Langgraph |
| Async Agents Tools | Learning about using agentic async tools | Azure OpenAI, Azure PromptFlow, Lama Index |
| Distributed Async Agents Tools | Learning about using agentic tools in a distributed system | Azure OpenAI, Azure PromptFlow, Lama Index, Kafka |
The following lines of code will connect your Codespace az cli and azd cli to the right Azure subscription:
az login
azd auth login
Now deploy the infrastructure components with azure cli
azd up
Get the values for some env variables
azd env get-values | grep AZURE_ENV_NAME
source <(azd env get-values)
Last but not least: deploy a dummy container in Azure Container Apps.
bash ./azd-hooks/deploy.sh 03-rag $AZURE_ENV_NAME
python -m streamlit run app.py --server.port=8000
Run the following script
azd env get-values | grep AZURE_ENV_NAME
source <(azd env get-values | grep AZURE_ENV_NAME)
bash ./azd-hooks/deploy.sh 03-rag $AZURE_ENV_NAME
All the other chapters work the same.