promptflow-starter-template 0.1.2

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promptflow-starter-template

This project, promptflow-starter-template, uses a modern tech stack to develop applications with Large Language Models (LLMs) and the Promptflow framework. The key technologies are:

• Promptflow: Microsoft Promptflow LLM Framework.
• FastAPI: High-performance API framework.
• Poetry: Dependency management and packaging.
• Docker: Containerization platform.
• Visual Studio Code: Code editor with development container support.
• PyPi: Your promptflow can be packaged and pushed to PyPi or your own Python registry (JFrog Artifactory).

Purpose

The promptflow-starter-template simplifies setting up and managing LLM tools, making integration easier. It packages promptflow with Poetry and runs it with FastAPI in a Docker container.

Usage

To use the promptflow-starter-template, follow these steps:

Prerequisites

• An Azure subscription - Create one for free here.
• An Azure OpenAI Service resource with either gpt-4o or the gpt-4o-mini models deployed. We recommend using standard or global standard model deployment types for initial exploration. For more information about model deployment, see the resource deployment guide.

Steps

1. Setup the .devcontainer/devcontainer.env: Create a .devcontainer/devcontainer.env file with the following content:

   OPENAI_API_KEY=your_openai_api_key
   OPENAI_API_BASE=your_openai_api_base_url
   

   Replace your_openai_api_key with your actual OpenAI API key and your_openai_api_base_url with your Azure OpenAI API base URL.

2. Verify that the connection.yaml matches your deployment: Create a connection.yaml file with the following content:

   $schema: https://azuremlschemas.azureedge.net/promptflow/latest/AzureOpenAIConnection.schema.json
   name: open_ai_connection
   type: azure_open_ai
   module: promptflow.connections
   api_key: "${env.OPENAI_API_KEY}"
   api_base: "<user-input>"
   api_version: "2024-10-01-preview"
   api_type: "azure"
   

   Replace <user-input> with your Azure OpenAI API base URL.

3. Build and run the development container: Open the project in Visual Studio Code and use the Remote - Containers extension to build and run the development container. This will automatically install the dependencies and set up the environment. It will also add the connection automatically.

4. Rename the project directory and update pyproject.toml: Rename the promptflow_starter_template directory to your desired package name. Then, open the pyproject.toml file and update the name, authors, description, version field under [tool.poetry] to match your new package information.

You are now ready to start developing with the promptflow-starter-template.

Run the FastAPI endpoint

To run the FastAPI endpoint, use the following command:

uvicorn promptflow_starter_template.api:app --host 0.0.0.0 --port 5000 --workers 4

Note: Replace promptflow_starter_template with the package name from step 4.

Deployment steps

• Set up PyPi and GitHub Actions: To publish your package to PyPi and automate the process with GitHub Actions, follow these steps: Ensure you add your PyPi token to the GitHub repository secrets as PYPI_API_TOKEN.

You have now set up your project for publishing to PyPi and automated the process with GitHub Actions.

• Build and push Docker images: To build and push Docker images for your project, you can use the following commands:

  There are two Dockerfiles in this project: Dockerfile and Dockerfile.fastapi. The Dockerfile is used for python packagin, while the Dockerfile.fastapi is specifically for the FastAPI production ready application. Thus, only the FastAPI Docker image needs to be pushed to the GitHub Container Registry to use it later.

• Add PYPI_API_TOKEN to .devcontainers/devcontainer.env

• Build the Python package:

  docker build --build-arg PYPI_API_TOKEN=$PYPI_API_TOKEN -t ghcr.io/fabianschurig/promptflow-starter-template/build:latest .
  

• Build the Docker image using the package from previous step:

  docker build -t ghcr.io/fabianschurig/promptflow-starter-template/fastapi:latest -f Dockerfile.fastapi --build-arg PACKAGE_INSTALL_NAME=promptflow-starter-template --build-arg PACKAGE_IMPORT_NAME=promptflow_starter_template .
  

• Run the docker container:

  docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -e OPENAI_API_BASE=$OPENAI_API_BASE -p 5000:5000 ghcr.io/fabianschurig/promptflow-starter-template/fastapi:latest
  

• Push the Docker image to GitHub Container Registry:

  docker push ghcr.io/fabianschurig/promptflow-starter-template/fastapi:latest
  

• Use the Docker compose Set environment variables to .env if they are not set yet in the .devcontainer/devcontainer.env. Those are used when doing docker compose up:

  HOST=0.0.0.0
  PORT=5000
  WORKERS=4
  OPENAI_API_VERSION=2024-10-01-preview
  PACKAGE_INSTALL_NAME=promptflow-starter-template
  PACKAGE_IMPORT_NAME=promptflow_starter_template