docs/ROLES.md

ROLES.md — Team Roles & Responsibilities

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Role Definitions

Environment Engineer

Owns: server/environment.py, models.py, data pipeline

• Implements reset(), step(), state following OpenEnv ABC
• Defines typed Action, Observation, State dataclasses
• Writes ground-truth data loader and reward computation logic
• Ensures step() is stateless-safe for concurrent sessions
• Writes unit tests for environment logic

API / Infra Engineer

Owns: server/app.py, server/Dockerfile, openenv.yaml, pyproject.toml

• Wires create_fastapi_app(env) correctly
• Configures Dockerfile for uvicorn with WORKERS, PORT env vars
• Manages HF Spaces deployment (openenv push)
• Validates /health, /reset, /step, /state endpoints
• Configures scaling (workers, MAX_CONCURRENT_ENVS)

Client Engineer

Owns: client.py

• Implements HTTPEnvClient subclass
• Implements _step_payload(), _parse_result(), _parse_state()
• Writes async and sync usage examples
• Ensures client works against both local Docker and HF Spaces URL

Training Engineer

Owns: train.py / Colab notebook, GRPOConfig, rollout function

• Writes rollout_func that calls env.reset() + env.step() in loop
• Defines GRPOConfig (learning rate, batch size, vLLM settings)
• Registers all reward functions with GRPOTrainer
• Monitors training via trackio
• Pushes fine-tuned model to HF Hub

Reward Designer

Owns: REWARD_DESIGN.md, reward function implementations

• Designs decomposed, float-returning reward functions
• Works with Environment Engineer to embed reward signals in step()
• Validates reward signal is non-sparse and well-shaped
• Documents reward composition and rationale

QA / Evaluation Engineer

Owns: evaluation scripts, metrics

• Validates environment correctness (does step() behave deterministically?)
• Runs baseline policies to sanity-check reward range
• Evaluates fine-tuned model on held-out evaluation set
• Produces final metrics for hackathon submission

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Collaboration Rules

• All code must follow OpenEnv 5-step pattern (see ARCHITECTURE.md)
• No deviation from step() / reset() / state interface
• All reward functions must return List[float] for GRPOTrainer compatibility
• Docker image must pass curl /health before any deployment PR is merged
• HF Space URL must be live before training begins