.env.example

# FrontierSWE-OpenEnv — Environment Variables
#
# Copy to .env and fill in:
#
#   cp .env.example .env
#
# Pass to Docker:
#   docker run --env-file .env -p 8000:8000 frontier-swe-pg:latest
#
# All variables are prefixed FSWE_ (Frontier SWE).


# Agent LLM (the model being trained / evaluated)
# This is the model that pi uses to write code inside the env.

# Model name (e.g. qwen-3.5-27b, gpt-4o, claude-sonnet-4-20250514)
FSWE_AGENT_MODEL=qwen-3.5-27b

# Pi provider name — must match a key in models.json
# The entrypoint generates models.json with this provider key
FSWE_AGENT_PROVIDER=openai-compat

# OpenAI-compatible base URL for the agent model
FSWE_AGENT_API_URL=https://api.openai.com/llm/v1

# API key for the agent endpoint
FSWE_AGENT_API_KEY=your-agent-api-key-here


# Grader LLM (L2 code-review + L3 plan-review rubrics)
# A separate (typically stronger) model that scores the agent's
# code diffs and plans. Required for non-zero L2/L3 scores.

# Model name for the grader (e.g. gpt-4o, gemini-2.0-flash)
FSWE_GRADER_MODEL=qwen-3.5-27b

# OpenAI-compatible base URL for the grader
FSWE_GRADER_API_URL=https://api.openai.com/llm/v1

# API key for the grader endpoint
FSWE_GRADER_API_KEY=your-grader-api-key-here


# Fallback (optional)
# If FSWE_AGENT_API_KEY or FSWE_GRADER_API_KEY is not set, the
# standard OPENAI_API_KEY is used as a last resort. Useful when
# agent and grader share the same API.
# OPENAI_API_KEY=sk-...


# Inference smoke driver (inference.py)
# Only FSWE_SPACE_URL is required. Pi inside the Space already has the
# FSWE_AGENT_* / FSWE_GRADER_* keys, so inference.py does not need them.

FSWE_SPACE_URL=https://your-space-host.hf.space

# Optional knobs (defaults shown):
# MAX_STEPS=4
# TASK_COUNT=1
# MESSAGE_TIMEOUT=900