.env.example

# ==============================================================================
# CI-Copilot Environment Configuration
# ==============================================================================
# Copy this file to .env and fill in your values:
#   cp .env.example .env

# ------------------------------------------------------------------------------
# API Keys (Required)
# ------------------------------------------------------------------------------

# Your OpenAI API key. Required if using OpenAI as the LLM provider (default).
# If using a different provider, set the corresponding key instead:
#   Anthropic  → ANTHROPIC_API_KEY
#   Google     → GOOGLE_API_KEY
#   AWS        → AWS credentials (via env or ~/.aws/credentials)
#   Azure      → AZURE_OPENAI_API_KEY + AZURE_OPENAI_ENDPOINT
OPENAI_API_KEY="your_openai_api_key_here"

# GitHub Personal Access Token with `repo` scope.
# Used by the GitHub MCP server to read repositories and create PRs.
GITHUB_PERSONAL_ACCESS_TOKEN="github_personal_access_token_with_repo_scope"

# ------------------------------------------------------------------------------
# LLM Configuration
# ------------------------------------------------------------------------------
# CI-Copilot uses three LLM tiers for different tasks. You can mix providers.
#
# Supported providers: openai, anthropic, google_genai, bedrock, azure_openai
#
# If you're using OpenAI for everything, leave LLM_PROVIDER as "openai".
# If you want to use a different provider (e.g. Anthropic), change LLM_PROVIDER
# to "anthropic" and set LLM_MODEL to a valid Anthropic model name.
# You can also mix — e.g. use OpenAI for standard tasks and Anthropic for higher.

# Standard LLM — used for routing, tool calls, and general agent tasks
LLM_PROVIDER=openai
LLM_MODEL=gpt-4o-mini

# Higher-tier LLM — used for complex reasoning (dependency extraction, CI inference)
# Set to a more capable model if budget allows
LLM_HIGHER_PROVIDER=openai
LLM_HIGHER_MODEL=gpt-5-mini

# Deep Agent LLM — used for workflow rendering and refinement (needs strong code generation)
LLM_DEEPAGENT_PROVIDER=openai
LLM_DEEPAGENT_MODEL=o4-mini

# ------------------------------------------------------------------------------
# A2A Server
# ------------------------------------------------------------------------------

# Port the CI-Copilot A2A server listens on
A2A_SERVER_PORT=10102

# ------------------------------------------------------------------------------
# LangSmith (Optional — for tracing and debugging agent runs)
# ------------------------------------------------------------------------------
# Set LANGCHAIN_TRACING_V2=true to enable LangSmith tracing.
# You'll need a LangSmith API key from https://smith.langchain.com

LANGCHAIN_TRACING_V2=false
LANGCHAIN_API_KEY="your_langsmith_api_key_here"
LANGSMITH_PROJECT="ci-copilot"