Daily Repo Digest QuickStart (Python Copilot SDK on Azure Functions)

A simple AI agent built with the GitHub Copilot SDK, running as an Azure Function. It creates live daily GitHub repository digests for recent pull requests, issues, and workflow failures. The default repository is Azure/azure-functions-host.

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Prerequisites

• Python 3.13+ via uv
• Azure Functions Core Tools
• Azurite for local Azure Functions storage
• Azure Developer CLI (azd) (only needed for deploying Microsoft Foundry resources)
• Access to an AI model via one of:
  • GitHub Copilot subscription - models are available automatically
  • Bring Your Own Key (BYOK) - use an API key from Microsoft Foundry (see BYOK docs)

Quickstart

Want to use your own models? See Deploy Microsoft Foundry Resources below to provision a Microsoft Foundry project instead of using GitHub Copilot models.

1. Clone the repository

2. Install dependencies:

   uv sync

3. Start Azurite in a separate terminal:

   azurite --skipApiVersionCheck --silent --location ./.azurite

4. Run the function locally:

   uv run func start

5. Test the digest agent in another terminal:

   # Interactive chat client
   uv run chat.py
   
   # Or use curl directly
   curl -X POST http://localhost:7071/api/ask \
     -d "Create a concise daily repo digest for Azure/azure-functions-host."

   To chat with a deployed instance, grab the URL and function key from your azd environment:

   export AGENT_URL=$(azd env get-value SERVICE_API_URI)
   export FUNCTION_KEY=$(az functionapp keys list \
     -n $(azd env get-value AZURE_FUNCTION_APP_NAME) \
     -g $(azd env get-value RESOURCE_GROUP) \
     --query "functionKeys.default" -o tsv)
   
   uv run chat.py

Source Code

The agent logic is in function_app.py. It creates a CopilotClient, fetches live public GitHub data through REST APIs, and asks the model to produce a concise daily digest. The sample keeps the Azure Functions hosting model from this repo and exposes:

• An HTTP endpoint at /api/ask for chat or API requests.
• A timer-triggered function named daily_repo_digest that runs the digest at 9 AM Pacific.

chat.py is a lightweight console client that POSTs messages to the function in a loop, giving you an interactive chat experience. It defaults to http://localhost:7071 but can be pointed at a deployed instance via the AGENT_URL environment variable.

Ask for a digest with an optional public repo such as Azure/azure-functions-host. If you omit the repo, the agent uses Azure/azure-functions-host by default. Set GITHUB_REPOSITORY to change the default repository. Set GITHUB_TOKEN only if you want higher public GitHub API rate limits.

Local development uses pyproject.toml with uv sync and uv run. requirements.txt is kept for Azure Functions packaging and should stay aligned with the dependencies in pyproject.toml.

Daily Schedule

The timer trigger uses the Azure Functions NCRONTAB schedule 0 0 16,17 * * *. Azure Functions timer schedules run in UTC for this Linux Functions sample, so the function wakes at both possible 9 AM Pacific UTC offsets and only creates a digest when the current America/Los_Angeles hour is 9. This keeps the sample aligned with Pacific daylight and standard time without adding a separate scheduler service.

Deploy Microsoft Foundry Resources

If you prefer to use your own models via BYOK and don't already have a Microsoft Foundry project with a model deployed:

azd auth login
azd up

This provisions all resources and configures local development automatically.

What Gets Deployed

• Microsoft Foundry project with GPT-5-mini model
• Azure Functions app (Python, Flex Consumption plan)
• Storage, monitoring, and all necessary RBAC role assignments
• Optional: Search for vector store (disabled by default)
• Optional: Cosmos DB for agent thread storage (disabled by default)

Using Microsoft Foundry (BYOK)

By default the agent uses GitHub Copilot's models. To use your own model from Microsoft Foundry instead, set these environment variables:

export AZURE_OPENAI_ENDPOINT="https://<your-ai-services>.openai.azure.com/"
export AZURE_OPENAI_API_KEY="<your-api-key>"
export AZURE_OPENAI_MODEL="gpt-5-mini"  # optional, defaults to gpt-5-mini

Getting these values:

• If you ran azd up, the endpoint is already in your environment. Run azd env get-values | grep AZURE_OPENAI_ENDPOINT
• For the API key, go to Azure Portal, your AI Services resource, Keys and Endpoint, then select the Azure OpenAI tab
• Or find both in the Microsoft Foundry portal under your project settings

See the BYOK docs for details.

Next steps

• Add tools and data sources with Azure Functions custom bindings, Python helpers, or MCP integration: MCP extension notes for this sample, Tutorial: Host an MCP server on Azure Functions, and connect MCP server endpoints to Foundry agents.
• Build durable, long-running Functions workflows: Durable Functions overview and Azure Functions timer triggers.

Learn More

• GitHub Copilot SDK
• Copilot SDK Python docs
• BYOK (Bring Your Own Key)
• Azure Developer CLI