# ── GraphStrike — OpenEnv Environment Server ─────────────────────────────────

# This Dockerfile runs the environment server (FastAPI + Gradio UI + episodes).

# No training loop, no AWS credentials required.

#

# Used by: openenv push / HuggingFace Spaces deployment

# Port: 7860 (HF Spaces default — configurable via PORT env var)

#

# For local training (Qwen3 + Reflexion + Hybrid Policy), use server/Dockerfile.

# ─────────────────────────────────────────────────────────────────────────────

FROM python:3.12-slim

WORKDIR /app

# ── Install Python dependencies (network available on HF build workers) ───────

COPY requirements.txt .

RUN pip install --no-cache-dir \

fastapi \

"uvicorn[standard]" \

"pydantic>=2.6.0" \

requests \

"openenv-core>=0.2.0" \

"gradio>=4.0.0" \

"openai>=1.0.0"

# ── Copy source code ──────────────────────────────────────────────────────────

COPY . .

# ── Pre-generate all 150 episodes at build time (~1 second, deterministic) ───

# This bakes the episodes into the image so the server starts instantly.

RUN python server/generator.py

# ── Dirs for optional persistent data (mounted as volumes on local Docker) ───

RUN mkdir -p /app/memory /app/runs

# ── Runtime config ────────────────────────────────────────────────────────────

ENV PORT=7860

ENV AWS_DEFAULT_REGION=us-east-1

# HF Spaces expects the app on port 7860 (override via PORT env var)

EXPOSE 7860

# Server only — the training loop is NOT started here.

# Judges evaluate the environment via the API endpoints:

# GET /health → liveness check

# GET /tasks → available tasks + action schema

# POST /reset → start an episode

# POST /step → take an action

# GET /grader → get normalised score after SUBMIT

# POST /baseline → run the rule-based agent on all 3 tasks

CMD ["python", "-m", "uvicorn", "server.app:app", \

"--host", "0.0.0.0", \

"--port", "7860", \

"--workers", "1", \

"--log-level", "info"]