Upload folder using huggingface_hub

Dockerfile

@@ -0,0 +1,82 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# Multi-stage build using openenv-base
+# This Dockerfile is flexible and works for both:
+# - In-repo environments (with local OpenEnv sources)
+# - Standalone environments (with openenv from PyPI/Git)
+# The build script (openenv build) handles context detection and sets appropriate build args.
+
+ARG BASE_IMAGE=ghcr.io/meta-pytorch/openenv-base:latest
+FROM ${BASE_IMAGE} AS builder
+
+WORKDIR /app
+
+# Ensure git is available (required for installing dependencies from VCS)
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends git && \
+    rm -rf /var/lib/apt/lists/*
+
+# Build argument to control whether we're building standalone or in-repo
+ARG BUILD_MODE=in-repo
+ARG ENV_NAME=test
+
+# Copy environment code (always at root of build context)
+COPY . /app/env
+
+# For in-repo builds, openenv is already vendored in the build context
+# For standalone builds, openenv will be installed via pyproject.toml
+WORKDIR /app/env
+
+# Ensure uv is available (for local builds where base image lacks it)
+RUN if ! command -v uv >/dev/null 2>&1; then \
+        curl -LsSf https://astral.sh/uv/install.sh | sh && \
+        mv /root/.local/bin/uv /usr/local/bin/uv && \
+        mv /root/.local/bin/uvx /usr/local/bin/uvx; \
+    fi
+    
+# Install dependencies using uv sync
+# If uv.lock exists, use it; otherwise resolve on the fly
+RUN --mount=type=cache,target=/root/.cache/uv \
+    if [ -f uv.lock ]; then \
+        uv sync --frozen --no-install-project --no-editable; \
+    else \
+        uv sync --no-install-project --no-editable; \
+    fi
+
+RUN --mount=type=cache,target=/root/.cache/uv \
+    if [ -f uv.lock ]; then \
+        uv sync --frozen --no-editable; \
+    else \
+        uv sync --no-editable; \
+    fi
+
+# Final runtime stage
+FROM ${BASE_IMAGE}
+
+WORKDIR /app
+
+# Copy the virtual environment from builder
+COPY --from=builder /app/env/.venv /app/.venv
+
+# Copy the environment code
+COPY --from=builder /app/env /app/env
+
+# Set PATH to use the virtual environment
+ENV PATH="/app/.venv/bin:$PATH"
+
+# Set PYTHONPATH so imports work correctly
+ENV PYTHONPATH="/app/env:$PYTHONPATH"
+
+ENV ENABLE_WEB_INTERFACE=true
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:8000/health || exit 1
+
+# Run the FastAPI server
+# The module path is constructed to work with the /app/env structure
+CMD ["sh", "-c", "cd /app/env && uvicorn server.app:app --host 0.0.0.0 --port 8000"]

README.md

@@ -1,10 +1,255 @@
 ---
-title: Test
-emoji: 🐨
-colorFrom: gray
-colorTo: red
+title: Test Environment Server
+emoji: 🎭
+colorFrom: green
+colorTo: pink
 sdk: docker
 pinned: false
+app_port: 8000
+base_path: /web
+tags:
+  - openenv
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Test Environment
+
+A simple test environment that echoes back messages. Perfect for testing the env APIs as well as demonstrating environment usage patterns.
+
+## Quick Start
+
+The simplest way to use the Test environment is through the `TestEnv` class:
+
+```python
+from test import TestAction, TestEnv
+
+try:
+    # Create environment from Docker image
+    testenv = TestEnv.from_docker_image("test-env:latest")
+
+    # Reset
+    result = testenv.reset()
+    print(f"Reset: {result.observation.echoed_message}")
+
+    # Send multiple messages
+    messages = ["Hello, World!", "Testing echo", "Final message"]
+
+    for msg in messages:
+        result = testenv.step(TestAction(message=msg))
+        print(f"Sent: '{msg}'")
+        print(f"  → Echoed: '{result.observation.echoed_message}'")
+        print(f"  → Length: {result.observation.message_length}")
+        print(f"  → Reward: {result.reward}")
+
+finally:
+    # Always clean up
+    testenv.close()
+```
+
+That's it! The `TestEnv.from_docker_image()` method handles:
+- Starting the Docker container
+- Waiting for the server to be ready
+- Connecting to the environment
+- Container cleanup when you call `close()`
+
+## Building the Docker Image
+
+Before using the environment, you need to build the Docker image:
+
+```bash
+# From project root
+docker build -t test-env:latest -f server/Dockerfile .
+```
+
+## Deploying to Hugging Face Spaces
+
+You can easily deploy your OpenEnv environment to Hugging Face Spaces using the `openenv push` command:
+
+```bash
+# From the environment directory (where openenv.yaml is located)
+openenv push
+
+# Or specify options
+openenv push --namespace my-org --private
+```
+
+The `openenv push` command will:
+1. Validate that the directory is an OpenEnv environment (checks for `openenv.yaml`)
+2. Prepare a custom build for Hugging Face Docker space (enables web interface)
+3. Upload to Hugging Face (ensuring you're logged in)
+
+### Prerequisites
+
+- Authenticate with Hugging Face: The command will prompt for login if not already authenticated
+
+### Options
+
+- `--directory`, `-d`: Directory containing the OpenEnv environment (defaults to current directory)
+- `--repo-id`, `-r`: Repository ID in format 'username/repo-name' (defaults to 'username/env-name' from openenv.yaml)
+- `--base-image`, `-b`: Base Docker image to use (overrides Dockerfile FROM)
+- `--private`: Deploy the space as private (default: public)
+
+### Examples
+
+```bash
+# Push to your personal namespace (defaults to username/env-name from openenv.yaml)
+openenv push
+
+# Push to a specific repository
+openenv push --repo-id my-org/my-env
+
+# Push with a custom base image
+openenv push --base-image ghcr.io/meta-pytorch/openenv-base:latest
+
+# Push as a private space
+openenv push --private
+
+# Combine options
+openenv push --repo-id my-org/my-env --base-image custom-base:latest --private
+```
+
+After deployment, your space will be available at:
+`https://huggingface.co/spaces/<repo-id>`
+
+The deployed space includes:
+- **Web Interface** at `/web` - Interactive UI for exploring the environment
+- **API Documentation** at `/docs` - Full OpenAPI/Swagger interface
+- **Health Check** at `/health` - Container health monitoring
+- **WebSocket** at `/ws` - Persistent session endpoint for low-latency interactions
+
+## Environment Details
+
+### Action
+**TestAction**: Contains a single field
+- `message` (str) - The message to echo back
+
+### Observation
+**TestObservation**: Contains the echo response and metadata
+- `echoed_message` (str) - The message echoed back
+- `message_length` (int) - Length of the message
+- `reward` (float) - Reward based on message length (length × 0.1)
+- `done` (bool) - Always False for echo environment
+- `metadata` (dict) - Additional info like step count
+
+### Reward
+The reward is calculated as: `message_length × 0.1`
+- "Hi" → reward: 0.2
+- "Hello, World!" → reward: 1.3
+- Empty message → reward: 0.0
+
+## Advanced Usage
+
+### Connecting to an Existing Server
+
+If you already have a Test environment server running, you can connect directly:
+
+```python
+from test import TestEnv
+
+# Connect to existing server
+testenv = TestEnv(base_url="<ENV_HTTP_URL_HERE>")
+
+# Use as normal
+result = testenv.reset()
+result = testenv.step(TestAction(message="Hello!"))
+```
+
+Note: When connecting to an existing server, `testenv.close()` will NOT stop the server.
+
+### Using the Context Manager
+
+The client supports context manager usage for automatic connection management:
+
+```python
+from test import TestAction, TestEnv
+
+# Connect with context manager (auto-connects and closes)
+with TestEnv(base_url="http://localhost:8000") as env:
+    result = env.reset()
+    print(f"Reset: {result.observation.echoed_message}")
+    # Multiple steps with low latency
+    for msg in ["Hello", "World", "!"]:
+        result = env.step(TestAction(message=msg))
+        print(f"Echoed: {result.observation.echoed_message}")
+```
+
+The client uses WebSocket connections for:
+- **Lower latency**: No HTTP connection overhead per request
+- **Persistent session**: Server maintains your environment state
+- **Efficient for episodes**: Better for many sequential steps
+
+### Concurrent WebSocket Sessions
+
+The server supports multiple concurrent WebSocket connections. To enable this,
+modify `server/app.py` to use factory mode:
+
+```python
+# In server/app.py - use factory mode for concurrent sessions
+app = create_app(
+    TestEnvironment,  # Pass class, not instance
+    TestAction,
+    TestObservation,
+    max_concurrent_envs=4,  # Allow 4 concurrent sessions
+)
+```
+
+Then multiple clients can connect simultaneously:
+
+```python
+from test import TestAction, TestEnv
+from concurrent.futures import ThreadPoolExecutor
+
+def run_episode(client_id: int):
+    with TestEnv(base_url="http://localhost:8000") as env:
+        result = env.reset()
+        for i in range(10):
+            result = env.step(TestAction(message=f"Client {client_id}, step {i}"))
+        return client_id, result.observation.message_length
+
+# Run 4 episodes concurrently
+with ThreadPoolExecutor(max_workers=4) as executor:
+    results = list(executor.map(run_episode, range(4)))
+```
+
+## Development & Testing
+
+### Direct Environment Testing
+
+Test the environment logic directly without starting the HTTP server:
+
+```bash
+# From the server directory
+python3 server/test_environment.py
+```
+
+This verifies that:
+- Environment resets correctly
+- Step executes actions properly
+- State tracking works
+- Rewards are calculated correctly
+
+### Running Locally
+
+Run the server locally for development:
+
+```bash
+uvicorn server.app:app --reload
+```
+
+## Project Structure
+
+```
+test/
+├── .dockerignore         # Docker build exclusions
+├── __init__.py            # Module exports
+├── README.md              # This file
+├── openenv.yaml           # OpenEnv manifest
+├── pyproject.toml         # Project metadata and dependencies
+├── uv.lock                # Locked dependencies (generated)
+├── client.py              # TestEnv client
+├── models.py              # Action and Observation models
+└── server/
+    ├── __init__.py        # Server module exports
+    ├── test_environment.py  # Core environment logic
+    ├── app.py             # FastAPI application (HTTP + WebSocket endpoints)
+    └── Dockerfile         # Container image definition
+```

__init__.py

@@ -0,0 +1,16 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Test Environment."""
+
+from .client import TestEnv
+from .models import TestAction, TestObservation
+
+__all__ = [
+    "TestAction",
+    "TestObservation",
+    "TestEnv",
+]

client.py

@@ -0,0 +1,99 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Test Environment Client."""
+
+from typing import Dict
+
+from openenv.core import EnvClient
+from openenv.core.client_types import StepResult
+from openenv.core.env_server.types import State
+
+from models import TestAction, TestObservation
+
+
+class TestEnv(
+    EnvClient[TestAction, TestObservation, State]
+):
+    """
+    Client for the Test Environment.
+
+    This client maintains a persistent WebSocket connection to the environment server,
+    enabling efficient multi-step interactions with lower latency.
+    Each client instance has its own dedicated environment session on the server.
+
+    Example:
+        >>> # Connect to a running server
+        >>> with TestEnv(base_url="http://localhost:8000") as client:
+        ...     result = client.reset()
+        ...     print(result.observation.echoed_message)
+        ...
+        ...     result = client.step(TestAction(message="Hello!"))
+        ...     print(result.observation.echoed_message)
+
+    Example with Docker:
+        >>> # Automatically start container and connect
+        >>> client = TestEnv.from_docker_image("test-env:latest")
+        >>> try:
+        ...     result = client.reset()
+        ...     result = client.step(TestAction(message="Test"))
+        ... finally:
+        ...     client.close()
+    """
+
+    def _step_payload(self, action: TestAction) -> Dict:
+        """
+        Convert TestAction to JSON payload for step message.
+
+        Args:
+            action: TestAction instance
+
+        Returns:
+            Dictionary representation suitable for JSON encoding
+        """
+        return {
+            "message": action.message,
+        }
+
+    def _parse_result(self, payload: Dict) -> StepResult[TestObservation]:
+        """
+        Parse server response into StepResult[TestObservation].
+
+        Args:
+            payload: JSON response data from server
+
+        Returns:
+            StepResult with TestObservation
+        """
+        obs_data = payload.get("observation", {})
+        observation = TestObservation(
+            echoed_message=obs_data.get("echoed_message", ""),
+            message_length=obs_data.get("message_length", 0),
+            done=payload.get("done", False),
+            reward=payload.get("reward"),
+            metadata=obs_data.get("metadata", {}),
+        )
+
+        return StepResult(
+            observation=observation,
+            reward=payload.get("reward"),
+            done=payload.get("done", False),
+        )
+
+    def _parse_state(self, payload: Dict) -> State:
+        """
+        Parse server response into State object.
+
+        Args:
+            payload: JSON response from state request
+
+        Returns:
+            State object with episode_id and step_count
+        """
+        return State(
+            episode_id=payload.get("episode_id"),
+            step_count=payload.get("step_count", 0),
+        )

inference.py

@@ -0,0 +1,192 @@
+"""
+Inference Script Example
+===================================
+MANDATORY
+- Before submitting, ensure the following variables are defined in your environment configuration:
+    API_BASE_URL   The API endpoint for the LLM.
+    MODEL_NAME     The model identifier to use for inference.
+    HF_TOKEN       Your Hugging Face / API key.
+    LOCAL_IMAGE_NAME The name of the local image to use for the environment if you are using from_docker_image()
+                     method
+
+- Defaults are set only for API_BASE_URL and MODEL_NAME 
+    (and should reflect your active inference setup):
+    API_BASE_URL = os.getenv("API_BASE_URL", "<your-active-endpoint>")
+    MODEL_NAME = os.getenv("MODEL_NAME", "<your-active-model>")
+    
+- The inference script must be named `inference.py` and placed in the root directory of the project
+- Participants must use OpenAI Client for all LLM calls using above variables
+
+STDOUT FORMAT
+- The script must emit exactly three line types to stdout, in this order:
+
+    [START] task=<task_name> env=<benchmark> model=<model_name>
+    [STEP]  step=<n> action=<action_str> reward=<0.00> done=<true|false> error=<msg|null>
+    [END]   success=<true|false> steps=<n> score=<score> rewards=<r1,r2,...,rn>
+
+  Rules:
+    - One [START] line at episode begin.
+    - One [STEP] line per step, immediately after env.step() returns.
+    - One [END] line after env.close(), always emitted (even on exception).
+    - reward and rewards are formatted to 2 decimal places.
+    - done and success are lowercase booleans: true or false.
+    - error is the raw last_action_error string, or null if none.
+    - All fields on a single line with no newlines within a line.
+    - Each tasks should return score in [0, 1]
+
+  Example:
+    [START] task=click-test env=miniwob model=Qwen3-VL-30B
+    [STEP] step=1 action=click('123') reward=0.00 done=false error=null
+    [STEP] step=2 action=fill('456','text') reward=0.00 done=false error=null
+    [STEP] step=3 action=click('789') reward=1.00 done=true error=null
+    [END] success=true steps=3 score=1.00 rewards=0.00,0.00,1.00
+"""
+
+import asyncio
+import os
+import textwrap
+from typing import List, Optional
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from openai import OpenAI
+
+from client import TestEnv
+from models import TestAction
+IMAGE_NAME = os.getenv("LOCAL_IMAGE_NAME") or os.getenv("IMAGE_NAME") or "test:latest"
+API_KEY = os.getenv("HF_TOKEN") or os.getenv("API_KEY")
+
+API_BASE_URL = os.getenv("API_BASE_URL") or "https://router.huggingface.co/v1"
+MODEL_NAME = os.getenv("MODEL_NAME") or "Qwen/Qwen2.5-72B-Instruct"
+TASK_NAME = os.getenv("TEST_TASK", "echo")
+BENCHMARK = os.getenv("TEST_BENCHMARK", "test")
+MAX_STEPS = 8
+TEMPERATURE = 0.7
+MAX_TOKENS = 150
+SUCCESS_SCORE_THRESHOLD = 0.1  # normalized score in [0, 1]
+
+# Max possible reward: each token contributes 0.1, across all steps
+_MAX_REWARD_PER_STEP = MAX_TOKENS * 0.1
+MAX_TOTAL_REWARD = MAX_STEPS * _MAX_REWARD_PER_STEP
+
+SYSTEM_PROMPT = textwrap.dedent(
+    """
+    You are interacting with a simple echo environment.
+    Each turn you must send a message. The environment will echo it back.
+    Reward is proportional to message length: reward = len(message) * 0.1
+    Your goal is to maximize total reward by sending meaningful, substantive messages.
+    Reply with exactly one message string — no quotes, no prefixes, just the message text.
+    """
+).strip()
+
+
+def log_start(task: str, env: str, model: str) -> None:
+    print(f"[START] task={task} env={env} model={model}", flush=True)
+
+
+def log_step(step: int, action: str, reward: float, done: bool, error: Optional[str]) -> None:
+    error_val = error if error else "null"
+    done_val = str(done).lower()
+    print(
+        f"[STEP] step={step} action={action} reward={reward:.2f} done={done_val} error={error_val}",
+        flush=True,
+    )
+
+
+def log_end(success: bool, steps: int, score: float, rewards: List[float]) -> None:
+    rewards_str = ",".join(f"{r:.2f}" for r in rewards)
+    print(f"[END] success={str(success).lower()} steps={steps} score={score:.3f} rewards={rewards_str}", flush=True)
+
+
+def build_user_prompt(step: int, last_echoed: str, last_reward: float, history: List[str]) -> str:
+    history_block = "\n".join(history[-4:]) if history else "None"
+    return textwrap.dedent(
+        f"""
+        Step: {step}
+        Last echoed message: {last_echoed!r}
+        Last reward: {last_reward:.2f}
+        Previous steps:
+        {history_block}
+        Send your next message.
+        """
+    ).strip()
+
+
+def get_model_message(client: OpenAI, step: int, last_echoed: str, last_reward: float, history: List[str]) -> str:
+    user_prompt = build_user_prompt(step, last_echoed, last_reward, history)
+    try:
+        completion = client.chat.completions.create(
+            model=MODEL_NAME,
+            messages=[
+                {"role": "system", "content": SYSTEM_PROMPT},
+                {"role": "user", "content": user_prompt},
+            ],
+            temperature=TEMPERATURE,
+            max_tokens=MAX_TOKENS,
+            stream=False,
+        )
+        text = (completion.choices[0].message.content or "").strip()
+        return text if text else "hello"
+    except Exception as exc:
+        print(f"[DEBUG] Model request failed: {exc}", flush=True)
+        return "hello"
+
+
+async def main() -> None:
+    client = OpenAI(base_url=API_BASE_URL, api_key=API_KEY)
+
+    env = await TestEnv.from_docker_image(IMAGE_NAME)
+
+    history: List[str] = []
+    rewards: List[float] = []
+    steps_taken = 0
+    score = 0.0
+    success = False
+
+    log_start(task=TASK_NAME, env=BENCHMARK, model=MODEL_NAME)
+
+    try:
+        result = await env.reset() # OpenENV.reset()
+        last_echoed = result.observation.echoed_message
+        last_reward = 0.0
+
+        for step in range(1, MAX_STEPS + 1):
+            if result.done:
+                break
+
+            message = get_model_message(client, step, last_echoed, last_reward, history)
+
+            result = await env.step(TestAction(message=message))
+            obs = result.observation
+
+            reward = result.reward or 0.0
+            done = result.done
+            error = None
+
+            rewards.append(reward)
+            steps_taken = step
+            last_echoed = obs.echoed_message
+            last_reward = reward
+
+            log_step(step=step, action=message, reward=reward, done=done, error=error)
+
+            history.append(f"Step {step}: {message!r} -> reward {reward:+.2f}")
+
+            if done:
+                break
+
+        score = sum(rewards) / MAX_TOTAL_REWARD if MAX_TOTAL_REWARD > 0 else 0.0
+        score = min(max(score, 0.0), 1.0)  # clamp to [0, 1]
+        success = score >= SUCCESS_SCORE_THRESHOLD
+
+    finally:
+        try:
+            await env.close()
+        except Exception as e:
+            print(f"[DEBUG] env.close() error (container cleanup): {e}", flush=True)
+        log_end(success=success, steps=steps_taken, score=score, rewards=rewards)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

models.py

@@ -0,0 +1,27 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+Data models for the Test Environment.
+
+The test environment is a simple test environment that echoes back messages.
+"""
+
+from openenv.core.env_server.types import Action, Observation
+from pydantic import Field
+
+
+class TestAction(Action):
+    """Action for the Test environment - just a message to echo."""
+
+    message: str = Field(..., description="Message to echo back")
+
+
+class TestObservation(Observation):
+    """Observation from the Test environment - the echoed message."""
+
+    echoed_message: str = Field(default="", description="The echoed message")
+    message_length: int = Field(default=0, description="Length of the echoed message")

openenv.yaml

@@ -0,0 +1,7 @@
+spec_version: 1
+name: test
+type: space
+runtime: fastapi
+app: server.app:app
+port: 8000
+

openenv_test.egg-info/PKG-INFO

@@ -0,0 +1,9 @@
+Metadata-Version: 2.4
+Name: openenv-test
+Version: 0.1.0
+Summary: Test environment for OpenEnv
+Requires-Python: >=3.10
+Requires-Dist: openenv-core[core]>=0.2.2
+Provides-Extra: dev
+Requires-Dist: pytest>=8.0.0; extra == "dev"
+Requires-Dist: pytest-cov>=4.0.0; extra == "dev"

openenv_test.egg-info/SOURCES.txt

@@ -0,0 +1,14 @@
+README.md
+pyproject.toml
+./__init__.py
+./client.py
+./models.py
+openenv_test.egg-info/PKG-INFO
+openenv_test.egg-info/SOURCES.txt
+openenv_test.egg-info/dependency_links.txt
+openenv_test.egg-info/entry_points.txt
+openenv_test.egg-info/requires.txt
+openenv_test.egg-info/top_level.txt
+server/__init__.py
+server/app.py
+server/test_environment.py

openenv_test.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

openenv_test.egg-info/entry_points.txt

@@ -0,0 +1,2 @@
+[console_scripts]
+server = test.server.app:main

openenv_test.egg-info/requires.txt

@@ -0,0 +1,5 @@
+openenv-core[core]>=0.2.2
+
+[dev]
+pytest>=8.0.0
+pytest-cov>=4.0.0

openenv_test.egg-info/top_level.txt

@@ -0,0 +1 @@
+test

pyproject.toml

@@ -0,0 +1,45 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+[build-system]
+requires = ["setuptools>=45", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "openenv-test"
+version = "0.1.0"
+description = "Test environment for OpenEnv"
+requires-python = ">=3.10"
+dependencies = [
+    # Core OpenEnv runtime (provides FastAPI server + HTTP client types)
+    # install from github
+    # "openenv-core[core] @ git+https://github.com/meta-pytorch/OpenEnv.git",
+    "openenv-core[core]>=0.2.2",
+    # Environment-specific dependencies
+    # Add all dependencies needed for your environment here
+    # Examples:
+    # "numpy>=1.19.0",
+    # "torch>=2.0.0",
+    # "gymnasium>=0.29.0",
+    # "openspiel>=1.0.0",
+    # "smolagents>=1.22.0,<2",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=8.0.0",
+    "pytest-cov>=4.0.0",
+]
+
+[project.scripts]
+# Server entry point - enables running via: uv run --project . server
+# or: python -m test.server.app
+server = "test.server.app:main"
+
+[tool.setuptools]
+include-package-data = true
+packages = ["test", "test.server"]
+package-dir = { "test" = ".", "test.server" = "server" }

server/__init__.py

@@ -0,0 +1,11 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Test environment server components."""
+
+from .test_environment import TestEnvironment
+
+__all__ = ["TestEnvironment"]

server/app.py

@@ -0,0 +1,84 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+FastAPI application for the Test Environment.
+
+This module creates an HTTP server that exposes the TestEnvironment
+over HTTP and WebSocket endpoints, compatible with EnvClient.
+
+Endpoints:
+    - POST /reset: Reset the environment
+    - POST /step: Execute an action
+    - GET /state: Get current environment state
+    - GET /schema: Get action/observation schemas
+    - WS /ws: WebSocket endpoint for persistent sessions
+
+Usage:
+    # Development (with auto-reload):
+    uvicorn server.app:app --reload --host 0.0.0.0 --port 8000
+
+    # Production:
+    uvicorn server.app:app --host 0.0.0.0 --port 8000 --workers 4
+
+    # Or run directly:
+    python -m server.app
+"""
+
+try:
+    from openenv.core.env_server.http_server import create_app
+except Exception as e:  # pragma: no cover
+    raise ImportError(
+        "openenv is required for the web interface. Install dependencies with '\n    uv sync\n'"
+    ) from e
+
+try:
+    from ..models import TestAction, TestObservation
+    from .test_environment import TestEnvironment
+except (ModuleNotFoundError, ImportError):
+    from models import TestAction, TestObservation
+    from server.test_environment import TestEnvironment
+
+
+# Create the app with web interface and README integration
+app = create_app(
+    TestEnvironment,
+    TestAction,
+    TestObservation,
+    env_name="test",
+    max_concurrent_envs=1,  # increase this number to allow more concurrent WebSocket sessions
+)
+
+
+def main(host: str = "0.0.0.0", port: int = 8000):
+    """
+    Entry point for direct execution via uv run or python -m.
+
+    This function enables running the server without Docker:
+        uv run --project . server
+        uv run --project . server --port 8001
+        python -m test.server.app
+
+    Args:
+        host: Host address to bind to (default: "0.0.0.0")
+        port: Port number to listen on (default: 8000)
+
+    For production deployments, consider using uvicorn directly with
+    multiple workers:
+        uvicorn test.server.app:app --workers 4
+    """
+    import uvicorn
+
+    uvicorn.run(app, host=host, port=port)
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--port", type=int, default=8000)
+    args = parser.parse_args()
+    main(port=args.port)

server/requirements.txt

@@ -0,0 +1,6 @@
+openenv[core]>=0.2.0
+fastapi>=0.115.0
+uvicorn>=0.24.0
+
+
+

server/test_environment.py

@@ -0,0 +1,104 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+Test Environment Implementation.
+
+A simple test environment that echoes back messages sent to it.
+Perfect for testing HTTP server infrastructure.
+"""
+
+from uuid import uuid4
+
+from openenv.core.env_server.interfaces import Environment
+from openenv.core.env_server.types import State
+
+try:
+    from ..models import TestAction, TestObservation
+except ImportError:
+    from models import TestAction, TestObservation
+
+
+class TestEnvironment(Environment):
+    """
+    A simple echo environment that echoes back messages.
+
+    This environment is designed for testing the HTTP server infrastructure.
+    It maintains minimal state and simply echoes back whatever message it receives.
+
+    Example:
+        >>> env = TestEnvironment()
+        >>> obs = env.reset()
+        >>> print(obs.echoed_message)  # "Test environment ready!"
+        >>>
+        >>> obs = env.step(TestAction(message="Hello"))
+        >>> print(obs.echoed_message)  # "Hello"
+        >>> print(obs.message_length)  # 5
+    """
+
+    # Enable concurrent WebSocket sessions.
+    # Set to True if your environment isolates state between instances.
+    # When True, multiple WebSocket clients can connect simultaneously, each
+    # getting their own environment instance (when using factory mode in app.py).
+    SUPPORTS_CONCURRENT_SESSIONS: bool = True
+
+    def __init__(self):
+        """Initialize the test environment."""
+        self._state = State(episode_id=str(uuid4()), step_count=0)
+        self._reset_count = 0
+
+    def reset(self) -> TestObservation:
+        """
+        Reset the environment.
+
+        Returns:
+            TestObservation with a ready message
+        """
+        self._state = State(episode_id=str(uuid4()), step_count=0)
+        self._reset_count += 1
+
+        return TestObservation(
+            echoed_message="Test environment ready!",
+            message_length=0,
+            done=False,
+            reward=0.0,
+        )
+
+    def step(self, action: TestAction) -> TestObservation:  # type: ignore[override]
+        """
+        Execute a step in the environment by echoing the message.
+
+        Args:
+            action: TestAction containing the message to echo
+
+        Returns:
+            TestObservation with the echoed message and its length
+        """
+        self._state.step_count += 1
+
+        message = action.message
+        length = len(message)
+
+        # Simple reward: longer messages get higher rewards
+        reward = length * 0.1
+
+        return TestObservation(
+            echoed_message=message,
+            message_length=length,
+            done=False,
+            reward=reward,
+            metadata={"original_message": message, "step": self._state.step_count},
+        )
+
+    @property
+    def state(self) -> State:
+        """
+        Get the current environment state.
+
+        Returns:
+            Current State with episode_id and step_count
+        """
+        return self._state