--- title: "GitHub Copilot" description: "import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';" type: skill canonical_url: https://claudary.paisolsolutions.com/skills/github-copilot-integration source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:24:52.153Z license: CC-BY-4.0 attribution: "GitHub Copilot — Claudary (https://claudary.paisolsolutions.com/skills/github-copilot-integration)" --- # GitHub Copilot import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; ## Overview --- sidebar_label: "GitHub Copilot" --- import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # GitHub Copilot This tutorial shows you how to integrate GitHub Copilot with LiteLLM Proxy, allowing you to route requests through LiteLLM's unified interface. :::info This tutorial is based on [Sergio Pino's excellent guide](https://dev.to/spino327/calling-github-copilot-models-from-openhands-using-litellm-proxy-1hl4) for calling GitHub Copilot models through LiteLLM Proxy. This integration allows you to use any LiteLLM supported model through GitHub Copilot's interface. ::: ## Benefits of using GitHub Copilot with LiteLLM When you use GitHub Copilot with LiteLLM you get the following benefits: **Developer Benefits:** - Universal Model Access: Use any LiteLLM supported model (Anthropic, OpenAI, Vertex AI, Bedrock, etc.) through the GitHub Copilot interface. - Higher Rate Limits & Reliability: Load balance across multiple models and providers to avoid hitting individual provider limits, with fallbacks to ensure you get responses even if one provider fails. **Proxy Admin Benefits:** - Centralized Management: Control access to all models through a single LiteLLM proxy instance without giving your developers API Keys to each provider. - Budget Controls: Set spending limits and track costs across all GitHub Copilot usage. ## Prerequisites Before you begin, ensure you have: - GitHub Copilot subscription (Individual, Business, or Enterprise) - A running LiteLLM Proxy instance - A valid LiteLLM Proxy API key - VS Code or compatible IDE with GitHub Copilot extension ## Quick Start Guide ### Step 1: Install LiteLLM Install LiteLLM with proxy support: ```bash uv tool install litellm[proxy] ``` ### Step 2: Configure LiteLLM Proxy Create a `config.yaml` file with your model configurations: ```yaml showLineNumbers title="config.yaml" model_list: - model_name: gpt-4o litellm_params: model: gpt-4o api_key: os.environ/OPENAI_API_KEY - model_name: claude-3-5-sonnet litellm_params: model: anthropic/claude-3-5-sonnet-20241022 api_key: os.environ/ANTHROPIC_API_KEY general_settings: master_key: sk-1234567890 # Change this to a secure key ``` ### Step 3: Start LiteLLM Proxy Start the proxy server: ```bash litellm --config config.yaml --port 4000 ``` ### Step 4: Configure GitHub Copilot Configure GitHub Copilot to use your LiteLLM proxy. Add the following to your VS Code `settings.json`: ```json { "github.copilot.advanced": { "debug.overrideProxyUrl": "http://localhost:4000", "debug.testOverrideProxyUrl": "http://localhost:4000" } } ``` ### Step 5: Test the Integration Restart VS Code and test GitHub Copilot. Your requests will now be routed through LiteLLM Proxy, giving you access to LiteLLM's features like: - Request/response logging - Rate limiting - Cost tracking - Model routing and fallbacks ## Advanced ### Use Anthropic, OpenAI, Bedrock, etc. models with GitHub Copilot You can route GitHub Copilot requests to any provider by configuring different models in your LiteLLM Proxy config: Route requests to Claude Sonnet: ```yaml showLineNumbers title="config.yaml" model_list: - model_name: claude-3-5-sonnet litellm_params: model: anthropic/claude-3-5-sonnet-20241022 api_key: os.environ/ANTHROPIC_API_KEY general_settings: master_key: sk-1234567890 ``` Route requests to GPT-4o: ```yaml showLineNumbers title="config.yaml" model_list: - model_name: gpt-4o litellm_params: model: gpt-4o api_key: os.environ/OPENAI_API_KEY general_settings: master_key: sk-1234567890 ``` Route requests to Claude on Bedrock: ```yaml showLineNumbers title="config.yaml" model_list: - model_name: bedrock-claude litellm_params: model: bedrock/anthropic.claude-haiku-4-5-20251001:0 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: us-east-1 general_settings: master_key: sk-1234567890 ``` All deployments with the same model_name will be load balanced. In this example we load balance between OpenAI and Anthropic: ```yaml showLineNumbers title="config.yaml" model_list: - model_name: gpt-4o litellm_params: model: gpt-4o api_key: os.environ/OPENAI_API_KEY - model_name: gpt-4o # Same model name for load balancing litellm_params: model: anthropic/claude-3-5-sonnet-20241022 api_key: os.environ/ANTHROPIC_API_KEY router_settings: routing_strategy: simple-shuffle general_settings: master_key: sk-1234567890 ``` With this configuration, GitHub Copilot will automatically route requests through LiteLLM to your configured provider(s) with load balancing and fallbacks. ## Troubleshooting If you encounter issues: 1. **GitHub Copilot not using proxy**: Verify the proxy URL is correctly configured in VS Code settings and that LiteLLM proxy is running 2. **Authentication errors**: Ensure your master key is valid and API keys for providers are correctly set 3. **Connection errors**: Check that your LiteLLM Proxy is accessible at `http://localhost:4000` ## Credits This tutorial is based on the work by [Sergio Pino](https://dev.to/spino327) from his original article: [Calling GitHub Copilot models from OpenHands using LiteLLM Proxy](https://dev.to/spino327/calling-github-copilot-models-from-openhands-using-litellm-proxy-1hl4). Thank you for the foundational work! --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/github-copilot-integration) · https://claudary.paisolsolutions.com