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Deploy to Azure

workshop-azure-openai

This repository is for a workshop using Azure OpenAI Service.

Prerequisites

To run all the projects in this repository, you need the followings.

Here are the preferred tools for development.

Projects

Project Description Image
1_call_azure_openai_chat Call Azure OpenAI Service API from Python No Image
2_streamlit_chat Create an Azure OpenAI Chat app using Streamlit 2_streamlit_chat
3_call_azure_cosmos_db Call Azure Cosmos DB from Python No Image
4_streamlit_chat_history Add feature to store chat history using Azure Cosmos DB 4_streamlit_chat_history
5_streamlit_query_chat_history Search Chat History 5_streamlit_query_chat_history
6_call_azure_ai_search Call Azure AI Search from Python No Image
7_streamlit_chat_rag Add RAG feature to Streamlit chat app 7_streamlit_chat_rag
8_streamlit_azure_openai_batch Call Azure OpenAI Batch API with Streamlit 8_streamlit_azure_openai_batch
9_streamlit_azure_document_intelligence Call Azure AI Document Intelligence API with Streamlit 9_streamlit_azure_document_intelligence
10_streamlit_batch_transcription Call Batch Transcription API with Streamlit 10_streamlit_batch_transcription
11_promptflow Get started with Prompt flow No Image
12_langgraph_agent Create agents with LangGraph No Image
99_streamlit_examples Code samples for Streamlit 99_streamlit_examples

How to run

Referring to the .env.template file, create a .env file in the same directory and set the required credentials.

Local environment

# Create a virtual environment
$ python -m venv .venv

# Activate the virtual environment
$ source .venv/bin/activate

# Install dependencies
$ pip install -r requirements.txt

# Run the script (e.g. run 2_streamlit_chat)
$ python -m streamlit run apps/2_streamlit_chat/main.py

Docker container

# Set Docker image name
## GitHub Container Registry
$ IMAGE=ghcr.io/ks6088ts-labs/workshop-azure-openai:latest
## Docker Hub
$ IMAGE=ks6088ts/workshop-azure-openai:latest

# run 2_streamlit_chat
$ docker run --rm \
    -p 8501:8501 \
    -v ${PWD}/.env:/app/.env \
    ${IMAGE} \
    python -m streamlit run ./apps/2_streamlit_chat/main.py