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GitHub Copilot CLI Quickstart

This example shows how to use the GitHub Copilot CLI as the LLM backend for OpenEvolve. No API keys are needed — authentication uses your GitHub Copilot subscription.

Prerequisites

  1. Install GitHub Copilot CLI:

    npm install -g @github/copilot

  2. Authenticate:

    copilot login

    For headless runs you can instead export a fine-grained personal access token with the "Copilot Requests" permission as COPILOT_GITHUB_TOKEN.

  3. Install OpenEvolve:

    pip install openevolve

Run

python openevolve-run.py \
  examples/copilot_cli_quickstart/initial_program.py \
  examples/copilot_cli_quickstart/evaluator.py \
  --config examples/copilot_cli_quickstart/config.yaml \
  --iterations 50

How It Works

The config.yaml sets provider: "copilot_cli" which routes all LLM calls through the copilot -p subprocess instead of the OpenAI-compatible API. The CLI handles authentication, model selection, and billing.

Because the CLI has no --system-prompt flag, the system message is prepended to the prompt. Each call runs with --silent --no-color --no-ask-user --no-custom-instructions --disable-builtin-mcps so that only the model response reaches stdout and prompts stay reproducible across machines.

Key Config Options

Field Description Default
provider Set to "copilot_cli" to use the CLI backend "openai"
name Model passed to --model; use "auto" to let Copilot choose "auto"
reasoning_effort One of none, minimal, low, medium, high, xhigh, max unset
max_ai_credits Per-call AI credit budget unset
allow_all_tools Pre-approve the agent's tools false
timeout CLI timeout in seconds 300
retries Number of retry attempts on failure 3
retry_delay Seconds between retries 5

temperature, top_p and max_tokens have no equivalent CLI flag and are ignored by this backend.

Evolution only needs text generation, so tools are left unapproved by default. Set allow_all_tools: true only if you want the agent to read and write files while generating.

Ensemble Example

A single provider covers every model your subscription exposes, so an ensemble can mix vendors:

llm:
  provider: "copilot_cli"
  models:
    - name: "claude-sonnet-4.6"
      weight: 0.5
    - name: "gpt-5.4"
      weight: 0.3
    - name: "gemini-3.1-pro-preview"
      weight: 0.2

Programmatic Usage

You can also inject the Copilot CLI backend at runtime without modifying config files:

from openevolve.llm.copilot_cli import init_copilot_cli_client

for model_cfg in config.llm.models:
    model_cfg.init_client = init_copilot_cli_client