GitHub Copilot | liteLLM (original) (raw)

https://docs.github.com/en/copilot

tip

We support GitHub Copilot Chat API with automatic authentication handling

Authentication​

GitHub Copilot uses OAuth device flow for authentication. On first use, you'll be prompted to authenticate via GitHub:

1. LiteLLM will display a device code and verification URL
2. Visit the URL and enter the code to authenticate
3. Your credentials will be stored locally for future use

Usage - LiteLLM Python SDK​

Chat Completion​

GitHub Copilot Chat Completion

from litellm import completion

response = completion(
    model="github_copilot/gpt-4",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant"},
        {"role": "user", "content": "Write a Python function to calculate fibonacci numbers"}
    ]
)
print(response)

GitHub Copilot Chat Completion - Streaming

from litellm import completion

stream = completion(
    model="github_copilot/gpt-4",
    messages=[{"role": "user", "content": "Explain async/await in Python"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")

Responses​

For GPT Codex models, only responses API is supported.

GitHub Copilot Responses

import litellm

response = await litellm.aresponses(
    model="github_copilot/gpt-5.1-codex",
    input="Write a Python hello world",
    max_output_tokens=500
)

print(response)

Embedding​

GitHub Copilot Embedding

import litellm

response = litellm.embedding(
    model="github_copilot/text-embedding-3-small",
    input=["good morning from litellm"]
)
print(response)

Usage - LiteLLM Proxy​

Add the following to your LiteLLM Proxy configuration file:

config.yaml

model_list:
  - model_name: github_copilot/gpt-4
    litellm_params:
      model: github_copilot/gpt-4
  - model_name: github_copilot/gpt-5.1-codex
    model_info:
      mode: responses
    litellm_params:
      model: github_copilot/gpt-5.1-codex
  - model_name: github_copilot/text-embedding-ada-002
    model_info:
      mode: embedding
    litellm_params:
      model: github_copilot/text-embedding-ada-002

Start your LiteLLM Proxy server:

Start LiteLLM Proxy

litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000

• OpenAI SDK
• LiteLLM SDK
• cURL

GitHub Copilot via Proxy - Non-streaming

from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="your-proxy-api-key"       # Your proxy API key
)

# Non-streaming response
response = client.chat.completions.create(
    model="github_copilot/gpt-4",
    messages=[{"role": "user", "content": "How do I optimize this SQL query?"}]
)

print(response.choices[0].message.content)

Getting Started​

1. Ensure you have GitHub Copilot access (paid GitHub subscription required)
2. Run your first LiteLLM request - you'll be prompted to authenticate
3. Follow the device flow authentication process
4. Start making requests to GitHub Copilot through LiteLLM

Configuration​

Environment Variables​

You can customize token storage locations:

Environment Variables

# Optional: Custom token directory
export GITHUB_COPILOT_TOKEN_DIR="~/.config/litellm/github_copilot"

# Optional: Custom access token file name
export GITHUB_COPILOT_ACCESS_TOKEN_FILE="access-token"

# Optional: Custom API key file name
export GITHUB_COPILOT_API_KEY_FILE="api-key.json"

# Optional: Custom Copilot endpoints for authentication and usage
# (needed when using GitHub Enterprise subscriptions with custom endpoints or self-hosted GitHub servers
export GITHUB_COPILOT_API_BASE="https://copilot-api.my-company.ghe.com"
export GITHUB_COPILOT_DEVICE_CODE_URL="https://my-company.ghe.com/login/device/code"
export GITHUB_COPILOT_ACCESS_TOKEN_URL="https://my-company.ghe.com/login/oauth/access_token"
export GITHUB_COPILOT_API_KEY_URL="https://my-company.ghe.com/api/v3/copilot_internal/v2/token"

LiteLLM automatically injects the required GitHub Copilot headers (simulating VSCode). You don't need to specify them manually.

If you want to override the defaults (e.g., to simulate a different editor), you can use extra_headers:

Custom Headers (Optional)

extra_headers = {
    "editor-version": "vscode/1.85.1",           # Editor version
    "editor-plugin-version": "copilot/1.155.0",  # Plugin version
    "Copilot-Integration-Id": "vscode-chat",     # Integration ID
    "user-agent": "GithubCopilot/1.155.0"        # User agent
}