Upload folder using huggingface_hub

Dockerfile

@@ -0,0 +1,20 @@
+# 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.
+
+# Use the specified openenv-base image
+FROM ghcr.io/meta-pytorch/openenv-base:latest
+
+# Copy only what's needed for this environment
+COPY src/core/ /app/src/core/
+COPY src/envs/nle_env/ /app/src/envs/nle_env/
+
+# 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
+CMD ["uvicorn", "envs.nle_env.server.app:app", "--host", "0.0.0.0", "--port", "8000"]
+ENV ENABLE_WEB_INTERFACE=true

README.md

@@ -1,10 +1,39 @@
 ---
-title: Nle Env-pr-161
-emoji: 🚀
-colorFrom: yellow
-colorTo: gray
+title: Nle_env Environment Server
+emoji: 🐳
+colorFrom: blue
+colorTo: green
 sdk: docker
 pinned: false
+app_port: 8000
+base_path: /web
+tags:
+  - openenv-pr
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Nle_env Environment Server
+
+FastAPI server for nle_env environment powered by Meta's OpenEnv.
+
+## About
+
+This Space provides a containerized environment for nle_env interactions.
+Built with FastAPI and OpenEnv framework.
+
+## Web Interface
+
+This deployment includes an interactive web interface for exploring the environment:
+- **HumanAgent Interface**: Interact with the environment using a web form
+- **State Observer**: Real-time view of environment state and action history
+- **Live Updates**: WebSocket-based real-time updates
+
+Access the web interface at: `/web`
+
+
+## API Documentation
+
+Visit `/docs` for interactive API documentation.
+
+## Health Check
+
+The environment provides a health check endpoint at `/health`.

src/core/README.md

@@ -0,0 +1,180 @@
+# <img width="35" height="35" alt="image" src="https://github.com/user-attachments/assets/2700a971-e5d6-4036-b03f-2f89c9791609" /> OpenEnv: Agentic Execution Environments
+
+An e2e framework for creating, deploying and using isolated execution environments for agentic RL training, built using Gymnasium style simple APIs. OpenEnv provides a standard for interacting with agentic execution environments via simple Gymnasium style APIs - step(), reset(), state(). Users of agentic execution environments can interact with the environment during RL training loops using these simple APIs.
+
+In addition to making it easier for researchers and RL framework writers, we also provide tools for environment creators making it easier for them to create richer environments and make them available over familiar protocols like HTTP and packaged using canonical technologies like docker. Environment creators can use the OpenEnv framework to create environments that are isolated, secure, and easy to deploy and use.
+
+
+## Overview
+`openenv-core` provides the foundational building blocks for creating and interacting with containerized environments over HTTP. It enables you to build agent environments that can be deployed as Docker containers and accessed via a simple HTTP API.
+
+> ⚠️ **Early Development Warning** OpenEnv is currently in an experimental
+> stage. You should expect bugs, incomplete features, and APIs that may change
+> in future versions. The project welcomes bugfixes, but to make sure things are
+> well coordinated you should discuss any significant change before starting the
+> work. It's recommended that you signal your intention to contribute in the
+> issue tracker, either by filing a new issue or by claiming an existing one.
+
+
+# OpenEnv Core
+
+Core components for OpenEnv - a framework for building HTTP-based agentic environments.
+
+## Features
+
+- **HTTPEnvClient**: Generic HTTP client for interacting with remote environments
+- **HTTPEnvServer**: FastAPI-based server wrapper for exposing environments over HTTP
+- **Container Providers**: Pluggable architecture for running containers (Docker, Kubernetes, etc.)
+- **Type System**: Strongly-typed Action/Observation/State interfaces
+- **Web Interface**: Optional web UI for interacting with environments
+
+## Installation
+
+```bash
+pip install openenv-core
+```
+
+For development:
+```bash
+pip install openenv-core[dev]
+```
+
+## Quick Start
+
+### Creating an Environment Client
+
+```python
+from openenv_core import HTTPEnvClient, StepResult
+from dataclasses import dataclass
+
+@dataclass
+class MyAction:
+    text: str
+
+@dataclass
+class MyObservation:
+    response: str
+
+class MyEnvClient(HTTPEnvClient[MyAction, MyObservation]):
+    def _step_payload(self, action: MyAction) -> dict:
+        return {"text": action.text}
+
+    def _parse_result(self, payload: dict) -> StepResult[MyObservation]:
+        obs_data = payload["observation"]
+        return StepResult(
+            observation=MyObservation(**obs_data),
+            reward=payload.get("reward"),
+            done=payload.get("done", False)
+        )
+
+    def _parse_state(self, payload: dict) -> Any:
+        return payload
+
+# Use with Docker
+env = MyEnvClient.from_docker_image("my-env:latest")
+result = env.reset()
+step_result = env.step(MyAction(text="hello"))
+env.close()
+```
+
+### Creating an Environment Server
+
+```python
+from openenv_core.env_server import Environment, HTTPEnvServer, create_app
+from dataclasses import dataclass
+
+@dataclass
+class MyAction:
+    text: str
+
+@dataclass
+class MyObservation:
+    response: str
+    reward: float = 0.0
+    done: bool = False
+
+class MyEnvironment(Environment):
+    def reset(self) -> MyObservation:
+        return MyObservation(response="Ready")
+
+    def step(self, action: MyAction) -> MyObservation:
+        return MyObservation(
+            response=f"Echo: {action.text}",
+            reward=1.0,
+            done=False
+        )
+
+# Create FastAPI app
+env = MyEnvironment()
+app = create_app(env, MyAction, MyObservation)
+
+# Run with: uvicorn module:app --host 0.0.0.0 --port 8000
+```
+
+## Container Providers
+
+OpenEnv Core supports multiple container providers:
+
+### Local Docker Provider
+
+```python
+from openenv_core.containers.runtime import LocalDockerProvider
+
+provider = LocalDockerProvider()
+base_url = provider.start_container("my-env:latest")
+provider.wait_for_ready(base_url)
+# Use environment...
+provider.stop_container()
+```
+
+### Kubernetes Provider (Coming Soon)
+
+```python
+from openenv_core.containers.runtime import KubernetesProvider
+
+provider = KubernetesProvider(namespace="envs")
+base_url = provider.start_container("my-env:latest")
+# Use environment...
+provider.stop_container()
+```
+
+
+## API Reference
+
+### HTTPEnvClient
+
+Base class for environment clients with these abstract methods:
+
+- `_step_payload(action)`: Convert action to JSON
+- `_parse_result(payload)`: Parse response to StepResult
+- `_parse_state(payload)`: Parse state response
+
+### HTTPEnvServer
+
+Server wrapper with these methods:
+
+- `register_routes(app)`: Register endpoints on FastAPI app
+- `_deserialize_action(data)`: Convert JSON to Action
+- `_serialize_observation(obs)`: Convert Observation to JSON
+
+### Environment Interface
+
+Base interface for environment implementations:
+
+- `reset()`: Reset environment and return initial observation
+- `step(action)`: Execute action and return observation
+- `state`: Property returning current environment state
+
+## License
+
+This project is licensed under the BSD-3-Clause License - see the LICENSE file for details.
+
+## Contributing
+
+Contributions are welcome! Please see the main OpenEnv repository for contribution guidelines.
+
+## Links
+
+- **Homepage**: https://github.com/facebookresearch/OpenEnv
+- **Documentation**: https://github.com/facebookresearch/OpenEnv/blob/main/README.md
+- **Bug Tracker**: https://github.com/facebookresearch/OpenEnv/issues

src/core/__init__.py

@@ -0,0 +1,19 @@
+# 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.
+
+"""Core components for agentic environments."""
+
+# Re-export main components from submodules for convenience
+from .env_server import *
+from .client_types import StepResult
+from .http_env_client import HTTPEnvClient
+
+# Note: MCP module doesn't export anything yet
+
+__all__ = [
+    "HTTPEnvClient",
+    "StepResult",
+]

src/core/client_types.py

@@ -0,0 +1,22 @@
+# Type definitions for EnvTorch
+from dataclasses import dataclass
+from typing import Any, Generic, Optional, TypeVar
+
+# Generic type for observations
+ObsT = TypeVar("ObsT")  # TypeVar for typehinting in IDEs
+
+
+@dataclass
+class StepResult(Generic[ObsT]):
+    """
+    Represents the result of one environment step.
+
+    Attributes:
+        observation: The environment's observation after the action.
+        reward: Scalar reward for this step (optional).
+        done: Whether the episode is finished.
+    """
+
+    observation: ObsT
+    reward: Optional[float] = None
+    done: bool = False

src/core/containers/__init__.py

@@ -0,0 +1,7 @@
+# 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.
+
+"""Container management for environment servers."""

src/core/containers/images/Dockerfile

@@ -0,0 +1,47 @@
+# 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.
+
+#
+# OpenEnv Base Image
+#
+# This is the standard base image for all OpenEnv environment servers.
+# It includes the minimal dependencies needed to run HTTP environment servers.
+#
+# Build: docker build -t openenv-base:latest -f src/core/containers/images/Dockerfile .
+# Tag:   docker tag openenv-base:latest openenv-base:0.1.0
+#
+
+FROM python:3.11-slim
+
+# Set metadata
+LABEL maintainer="OpenEnv Team"
+LABEL description="Base image for OpenEnv based environment servers"
+LABEL version="0.1.0"
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python dependencies that all environments need
+RUN pip install --no-cache-dir \
+    "fastapi>=0.104.0" \
+    "uvicorn[standard]>=0.24.0" \
+    "requests>=2.25.0" \
+    "wsproto>=1.0.0" \
+    smolagents
+
+# Set working directory
+WORKDIR /app
+
+# Default environment variables
+ENV PYTHONPATH=/app/src
+ENV PYTHONUNBUFFERED=1
+
+# Default expose port (can be overridden)
+EXPOSE 8000
+
+# Note: CMD should be specified in child Dockerfiles

src/core/containers/images/README.md

@@ -0,0 +1,92 @@
+# OpenEnv Base Image
+
+Standard base image for all OpenEnv environment servers.
+
+## What's Included
+
+| Layer | Size | Contents |
+|-------|------|----------|
+| python:3.11-slim | 200 MB  | Base Python runtime |
+| + Dependencies   | 100 MB  | FastAPI, uvicorn, requests |
+| **Total**        | **~300 MB** | Ready for environment servers |
+
+## Image Sizes
+
+```
+openenv-base:latest   300 MB  (python + fastapi + uvicorn)
+```
+echo-env:latest        500 MB  (python + fastapi + uvicorn + app)
+coding-env:latest      520 MB  (python + fastapi + uvicorn + app + tools)
+another-env:latest     510 MB  (python + fastapi + uvicorn + app)
+---
+Total: 1.5 GB (with lots of duplication)
+```
+
+### With Base Images (✅ Solution)
+```
+openenv-base:latest    300 MB  (python + fastapi + uvicorn)
+echo-env:latest         50 MB  (app only, uses base)
+coding-env:latest       70 MB  (app + tools, uses base)
+another-env:latest      45 MB  (app only, uses base)
+---
+Total: 465 MB (base shared, minimal duplication)
+```
+
+## Building the Base Image
+
+```bash
+# From project root
+docker build -t openenv-base:latest -f src/core/containers/images/Dockerfile .
+```
+
+## Usage in Environment Dockerfiles
+
+Each environment Dockerfile should start with:
+
+```dockerfile
+FROM openenv-base:latest
+
+# Copy only environment-specific files
+COPY src/core/ /app/src/core/
+COPY src/envs/my_env/ /app/src/envs/my_env/
+
+# Run the server
+CMD ["uvicorn", "envs.my_env.server.app:app", "--host", "0.0.0.0", "--port", "8000"]
+```
+
+## Base Image Contents
+
+- Python 3.11-slim
+- FastAPI >= 0.104.0
+- Uvicorn >= 0.24.0
+- Requests >= 2.25.0
+- curl (for health checks)
+
+## Example: Building Echo Environment
+
+```bash
+# Step 1: Build base image (do this once)
+docker build -t openenv-base:latest -f src/core/containers/images/Dockerfile .
+
+# Step 2: Build echo environment (uses base)
+docker build -t echo-env:latest -f src/envs/echo_env/server/Dockerfile .
+
+# Step 3: Run echo environment
+docker run -p 8000:8000 echo-env:latest
+```
+
+## Updating the Base
+
+When dependencies need updating:
+
+1. Update `src/core/containers/images/Dockerfile`
+2. Rebuild base image
+3. Rebuild all environment images (they'll use new base)
+
+```bash
+# Update base
+docker build -t openenv-base:latest -f src/core/containers/images/Dockerfile .
+
+# Rebuild environments (they automatically use new base)
+docker build -t echo-env:latest -f src/envs/echo_env/server/Dockerfile .
+```

src/core/containers/runtime/__init__.py

@@ -0,0 +1,15 @@
+# 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.
+
+"""Container runtime providers."""
+
+from .providers import ContainerProvider, KubernetesProvider, LocalDockerProvider
+
+__all__ = [
+    "ContainerProvider",
+    "LocalDockerProvider",
+    "KubernetesProvider",
+]

src/core/containers/runtime/providers.py

@@ -0,0 +1,293 @@
+# 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.
+
+"""
+Container provider abstractions for running environment servers.
+
+This module provides a pluggable architecture for different container providers
+(local Docker, Kubernetes, cloud providers, etc.) to be used with HTTPEnvClient.
+"""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Optional
+
+
+class ContainerProvider(ABC):
+    """
+    Abstract base class for container providers.
+
+    Providers implement this interface to support different container platforms:
+    - LocalDockerProvider: Runs containers on local Docker daemon
+    - KubernetesProvider: Runs containers in Kubernetes cluster
+    - FargateProvider: Runs containers on AWS Fargate
+    - CloudRunProvider: Runs containers on Google Cloud Run
+
+    The provider manages a single container lifecycle and provides the base URL
+    for connecting to it.
+
+    Example:
+        >>> provider = LocalDockerProvider()
+        >>> base_url = provider.start_container("echo-env:latest")
+        >>> print(base_url)  # http://localhost:8000
+        >>> # Use the environment via base_url
+        >>> provider.stop_container()
+    """
+
+    @abstractmethod
+    def start_container(
+        self,
+        image: str,
+        port: Optional[int] = None,
+        env_vars: Optional[Dict[str, str]] = None,
+        **kwargs: Any,
+    ) -> str:
+        """
+        Start a container from the specified image.
+
+        Args:
+            image: Container image name (e.g., "echo-env:latest")
+            port: Port to expose (if None, provider chooses)
+            env_vars: Environment variables to pass to container
+            **kwargs: Provider-specific options
+
+        Returns:
+            Base URL to connect to the container (e.g., "http://localhost:8000")
+
+        Raises:
+            RuntimeError: If container fails to start
+        """
+        pass
+
+    @abstractmethod
+    def stop_container(self) -> None:
+        """
+        Stop and remove the running container.
+
+        This cleans up the container that was started by start_container().
+        """
+        pass
+
+    @abstractmethod
+    def wait_for_ready(self, base_url: str, timeout_s: float = 30.0) -> None:
+        """
+        Wait for the container to be ready to accept requests.
+
+        This typically polls the /health endpoint until it returns 200.
+
+        Args:
+            base_url: Base URL of the container
+            timeout_s: Maximum time to wait
+
+        Raises:
+            TimeoutError: If container doesn't become ready in time
+        """
+        pass
+
+
+class LocalDockerProvider(ContainerProvider):
+    """
+    Container provider for local Docker daemon.
+
+    This provider runs containers on the local machine using Docker.
+    Useful for development and testing.
+
+    Example:
+        >>> provider = LocalDockerProvider()
+        >>> base_url = provider.start_container("echo-env:latest")
+        >>> # Container running on http://localhost:<random-port>
+        >>> provider.stop_container()
+    """
+
+    def __init__(self):
+        """Initialize the local Docker provider."""
+        self._container_id: Optional[str] = None
+        self._container_name: Optional[str] = None
+
+        # Check if Docker is available
+        import subprocess
+
+        try:
+            subprocess.run(
+                ["docker", "version"],
+                check=True,
+                capture_output=True,
+                timeout=5,
+            )
+        except (subprocess.CalledProcessError, FileNotFoundError, subprocess.TimeoutExpired):
+            raise RuntimeError(
+                "Docker is not available. Please install Docker Desktop or Docker Engine."
+            )
+
+    def start_container(
+        self,
+        image: str,
+        port: Optional[int] = None,
+        env_vars: Optional[Dict[str, str]] = None,
+        **kwargs: Any,
+    ) -> str:
+        """
+        Start a Docker container locally.
+
+        Args:
+            image: Docker image name
+            port: Port to expose (if None, finds available port)
+            env_vars: Environment variables for the container
+            **kwargs: Additional Docker run options
+
+        Returns:
+            Base URL to connect to the container
+        """
+        import subprocess
+        import time
+
+        # Find available port if not specified
+        if port is None:
+            port = self._find_available_port()
+
+        # Generate container name
+        self._container_name = self._generate_container_name(image)
+
+        # Build docker run command
+        cmd = [
+            "docker", "run",
+            "-d",  # Detached
+            "--name", self._container_name,
+            "-p", f"{port}:8000",  # Map port
+        ]
+
+        # Add environment variables
+        if env_vars:
+            for key, value in env_vars.items():
+                cmd.extend(["-e", f"{key}={value}"])
+
+        # Add image
+        cmd.append(image)
+
+        # Run container
+        try:
+            result = subprocess.run(cmd, capture_output=True, text=True, check=True)
+            self._container_id = result.stdout.strip()
+        except subprocess.CalledProcessError as e:
+            error_msg = f"Failed to start Docker container.\nCommand: {' '.join(cmd)}\nExit code: {e.returncode}\nStderr: {e.stderr}\nStdout: {e.stdout}"
+            raise RuntimeError(error_msg) from e
+
+        # Wait a moment for container to start
+        time.sleep(1)
+
+        base_url = f"http://localhost:{port}"
+        return base_url
+
+    def stop_container(self) -> None:
+        """
+        Stop and remove the Docker container.
+        """
+        if self._container_id is None:
+            return
+
+        import subprocess
+
+        try:
+            # Stop container
+            subprocess.run(
+                ["docker", "stop", self._container_id],
+                capture_output=True,
+                check=True,
+                timeout=10,
+            )
+
+            # Remove container
+            subprocess.run(
+                ["docker", "rm", self._container_id],
+                capture_output=True,
+                check=True,
+                timeout=10,
+            )
+        except subprocess.CalledProcessError:
+            # Container might already be stopped/removed
+            pass
+        finally:
+            self._container_id = None
+            self._container_name = None
+
+    def wait_for_ready(self, base_url: str, timeout_s: float = 30.0) -> None:
+        """
+        Wait for container to be ready by polling /health endpoint.
+
+        Args:
+            base_url: Base URL of the container
+            timeout_s: Maximum time to wait
+
+        Raises:
+            TimeoutError: If container doesn't become ready
+        """
+        import time
+        import requests
+
+        start_time = time.time()
+        health_url = f"{base_url}/health"
+
+        while time.time() - start_time < timeout_s:
+            try:
+                response = requests.get(health_url, timeout=2.0)
+                if response.status_code == 200:
+                    return
+            except requests.RequestException:
+                pass
+
+            time.sleep(0.5)
+
+        raise TimeoutError(
+            f"Container at {base_url} did not become ready within {timeout_s}s"
+        )
+
+    def _find_available_port(self) -> int:
+        """
+        Find an available port on localhost.
+
+        Returns:
+            An available port number
+        """
+        import socket
+
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+            s.bind(("", 0))
+            s.listen(1)
+            port = s.getsockname()[1]
+        return port
+
+    def _generate_container_name(self, image: str) -> str:
+        """
+        Generate a unique container name based on image name and timestamp.
+
+        Args:
+            image: Docker image name
+
+        Returns:
+            A unique container name
+        """
+        import time
+
+        clean_image = image.split("/")[-1].split(":")[0]
+        timestamp = int(time.time() * 1000)
+        return f"{clean_image}-{timestamp}"
+
+
+class KubernetesProvider(ContainerProvider):
+    """
+    Container provider for Kubernetes clusters.
+
+    This provider creates pods in a Kubernetes cluster and exposes them
+    via services or port-forwarding.
+
+    Example:
+        >>> provider = KubernetesProvider(namespace="envtorch-dev")
+        >>> base_url = provider.start_container("echo-env:latest")
+        >>> # Pod running in k8s, accessible via service or port-forward
+        >>> provider.stop_container()
+    """
+    pass

src/core/containers/test_local_docker_provider.py

@@ -0,0 +1,258 @@
+#!/usr/bin/env python3
+"""
+End-to-end test for LocalDockerProvider.
+
+This script tests the complete flow:
+1. Start a container using LocalDockerProvider
+2. Wait for it to be ready
+3. Make HTTP requests to test the environment
+4. Clean up the container
+"""
+
+import sys
+from pathlib import Path
+
+# Add src to path
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+import requests
+
+from core.containers.runtime import LocalDockerProvider
+
+# TODO: Remove this test or make it a functional test sicne this will be tested in e2e test for echo env
+def test_local_docker_provider():
+    """Test LocalDockerProvider end-to-end."""
+    print("=" * 60)
+    print("LocalDockerProvider End-to-End Test")
+    print("=" * 60)
+    print()
+
+    provider = None
+
+    try:
+        # Step 1: Create provider
+        print("Step 1: Creating LocalDockerProvider...")
+        provider = LocalDockerProvider()
+        print("✓ Provider created\n")
+
+        # Step 2: Start container
+        print("Step 2: Starting echo-env container...")
+        base_url = provider.start_container("echo-env:latest")
+        print(f"✓ Container started at: {base_url}")
+        if provider._container_id:
+            print(f"  Container ID: {provider._container_id[:12]}...")
+        if provider._container_name:
+            print(f"  Container name: {provider._container_name}\n")
+
+        # Step 3: Wait for ready
+        print("Step 3: Waiting for container to be ready...")
+        provider.wait_for_ready(base_url, timeout_s=30.0)
+        print("✓ Container is ready!\n")
+
+        # Step 4: Test health endpoint
+        print("Step 4: Testing /health endpoint...")
+        response = requests.get(f"{base_url}/health")
+        print(f"  Status: {response.status_code}")
+        print(f"  Response: {response.json()}")
+        assert response.status_code == 200
+        assert response.json()["status"] == "healthy"
+        print("✓ Health check passed\n")
+
+        # Step 5: Test reset endpoint
+        print("Step 5: Testing /reset endpoint...")
+        response = requests.post(
+            f"{base_url}/reset",
+            json={},
+            headers={"Content-Type": "application/json"},
+        )
+        print(f"  Status: {response.status_code}")
+        data = response.json()
+        print(f"  Message: {data['observation']['echoed_message']}")
+        print(f"  Reward: {data['reward']}")
+        print(f"  Done: {data['done']}")
+        assert response.status_code == 200
+        assert data["observation"]["echoed_message"] == "Echo environment ready!"
+        print("✓ Reset test passed\n")
+
+        # Step 6: Test step endpoint
+        print("Step 6: Testing /step endpoint...")
+        response = requests.post(
+            f"{base_url}/step",
+            json={"action": {"message": "Hello from LocalDockerProvider!"}},
+            headers={"Content-Type": "application/json"},
+        )
+        print(f"  Status: {response.status_code}")
+        data = response.json()
+        print(f"  Echoed: {data['observation']['echoed_message']}")
+        print(f"  Length: {data['observation']['message_length']}")
+        print(f"  Reward: {data['reward']}")
+        assert response.status_code == 200
+        assert data["observation"]["echoed_message"] == "Hello from LocalDockerProvider!"
+        assert data["observation"]["message_length"] == 31
+        print("✓ Step test passed\n")
+
+        # Step 7: Test state endpoint
+        print("Step 7: Testing /state endpoint...")
+        response = requests.get(f"{base_url}/state")
+        print(f"  Status: {response.status_code}")
+        data = response.json()
+        print(f"  Episode ID: {data['episode_id']}")
+        print(f"  Step count: {data['step_count']}")
+        assert response.status_code == 200
+        assert data["step_count"] == 1  # One step from above
+        print("✓ State test passed\n")
+
+        # Step 8: Multiple steps
+        print("Step 8: Testing multiple steps...")
+        for i in range(3):
+            response = requests.post(
+                f"{base_url}/step",
+                json={"action": {"message": f"Message {i+1}"}},
+                headers={"Content-Type": "application/json"},
+            )
+            assert response.status_code == 200
+            print(f"  Step {i+1}: ✓")
+
+        # Check state updated
+        response = requests.get(f"{base_url}/state")
+        data = response.json()
+        assert data["step_count"] == 4  # 1 + 3 more steps
+        print(f"  Final step count: {data['step_count']}")
+        print("✓ Multiple steps test passed\n")
+
+        print("=" * 60)
+        print("✓ All tests passed!")
+        print("=" * 60)
+        print()
+
+        return True
+
+    except Exception as e:
+        print(f"\n❌ Test failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+    finally:
+        # Step 9: Cleanup
+        if provider is not None:
+            print("\nStep 9: Cleaning up container...")
+            try:
+                provider.stop_container()
+                print("✓ Container stopped and removed\n")
+            except Exception as e:
+                print(f"⚠️  Cleanup warning: {e}\n")
+
+
+def test_provider_with_custom_port():
+    """Test provider with custom port."""
+    print("=" * 60)
+    print("LocalDockerProvider with Custom Port Test")
+    print("=" * 60)
+    print()
+
+    provider = None
+
+    try:
+        provider = LocalDockerProvider()
+
+        print("Starting container on custom port 8123...")
+        base_url = provider.start_container("echo-env:latest", port=8123)
+        print(f"✓ Started at: {base_url}")
+        assert ":8123" in base_url
+
+        print("Waiting for ready...")
+        provider.wait_for_ready(base_url)
+        print("✓ Ready!")
+
+        print("Testing health...")
+        response = requests.get(f"{base_url}/health")
+        assert response.status_code == 200
+        print("✓ Health check passed")
+
+        print("\n✓ Custom port test passed!\n")
+        return True
+
+    except Exception as e:
+        print(f"\n❌ Test failed: {e}")
+        return False
+
+    finally:
+        if provider is not None:
+            provider.stop_container()
+            print("✓ Cleaned up\n")
+
+
+def test_provider_with_env_vars():
+    """Test provider with environment variables."""
+    print("=" * 60)
+    print("LocalDockerProvider with Environment Variables Test")
+    print("=" * 60)
+    print()
+
+    provider = None
+
+    try:
+        provider = LocalDockerProvider()
+
+        print("Starting container with environment variables...")
+        base_url = provider.start_container(
+            "echo-env:latest",
+            env_vars={"DEBUG": "true", "LOG_LEVEL": "info"}
+        )
+        print(f"✓ Started at: {base_url}")
+
+        print("Waiting for ready...")
+        provider.wait_for_ready(base_url)
+        print("✓ Ready!")
+
+        print("Testing health...")
+        response = requests.get(f"{base_url}/health")
+        assert response.status_code == 200
+        print("✓ Health check passed")
+
+        print("\n✓ Environment variables test passed!\n")
+        return True
+
+    except Exception as e:
+        print(f"\n❌ Test failed: {e}")
+        return False
+
+    finally:
+        if provider is not None:
+            provider.stop_container()
+            print("✓ Cleaned up\n")
+
+
+if __name__ == "__main__":
+    print()
+    print("🐳 LocalDockerProvider Test Suite")
+    print()
+
+    results = []
+
+    # Run basic test
+    results.append(("Basic End-to-End", test_local_docker_provider()))
+
+    # Run custom port test
+    results.append(("Custom Port", test_provider_with_custom_port()))
+
+    # Run environment variables test
+    results.append(("Environment Variables", test_provider_with_env_vars()))
+
+    # Summary
+    print("=" * 60)
+    print("Test Summary")
+    print("=" * 60)
+    for name, passed in results:
+        status = "✓ PASSED" if passed else "✗ FAILED"
+        print(f"{name:25} {status}")
+    print("=" * 60)
+
+    all_passed = all(result for _, result in results)
+    if all_passed:
+        print("\n🎉 All tests passed!")
+        exit(0)
+    else:
+        print("\n❌ Some tests failed")
+        exit(1)

src/core/env_server/__init__.py

@@ -0,0 +1,35 @@
+# 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.
+
+"""Core environment interfaces and types."""
+
+from .base_transforms import CompositeTransform, NullTransform
+from .http_server import HTTPEnvServer, create_app, create_fastapi_app
+from .interfaces import Environment, Message, ModelTokenizer, Transform
+from .types import Action, Observation, State
+from .web_interface import create_web_interface_app, WebInterfaceManager
+
+__all__ = [
+    # Core interfaces
+    "Environment",
+    "Transform",
+    "Message",
+    "ModelTokenizer",
+    # Types
+    "Action",
+    "Observation",
+    "State",
+    # Base transforms
+    "CompositeTransform",
+    "NullTransform",
+    # HTTP Server
+    "HTTPEnvServer",
+    "create_app",
+    "create_fastapi_app",
+    # Web Interface
+    "create_web_interface_app",
+    "WebInterfaceManager",
+]

src/core/env_server/base_transforms.py

@@ -0,0 +1,29 @@
+# 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.
+
+"""Base transform implementations for composing environment-specific transforms."""
+
+from .interfaces import Transform
+from .types import Observation
+
+
+class CompositeTransform(Transform):
+    """Combines multiple transforms into a single transform."""
+
+    def __init__(self, transforms: list[Transform]):
+        self.transforms = transforms
+
+    def __call__(self, observation: Observation) -> Observation:
+        for transform in self.transforms:
+            observation = transform(observation)
+        return observation
+
+
+class NullTransform(Transform):
+    """Default transform that passes through unchanged."""
+
+    def __call__(self, observation: Observation) -> Observation:
+        return observation

src/core/env_server/http_server.py

@@ -0,0 +1,233 @@
+# 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.
+
+"""
+HTTP server wrapper for Environment instances.
+
+This module provides utilities to wrap any Environment subclass and expose it
+over HTTP endpoints that HTTPEnvClient can consume.
+"""
+
+from __future__ import annotations
+
+import os
+from dataclasses import asdict
+from typing import Any, Dict, Type
+
+from .interfaces import Environment
+from .types import Action, Observation
+from fastapi import Body, FastAPI
+
+class HTTPEnvServer:
+    """
+    HTTP server wrapper for Environment instances.
+
+    This class wraps an Environment and exposes its reset(), step(), and state
+    methods as HTTP endpoints compatible with HTTPEnvClient.
+
+    The server expects:
+    - Action deserialization: Converts JSON dict to Action subclass
+    - Observation serialization: Converts Observation subclass to JSON dict
+
+    Example:
+        >>> from core.env_server import HTTPEnvServer
+        >>> from envs.coding_env.server import CodeExecutionEnvironment
+        >>>
+        >>> env = CodeExecutionEnvironment()
+        >>> server = HTTPEnvServer(env)
+        >>>
+        >>> # Register routes with FastAPI
+        >>> from fastapi import FastAPI
+        >>> app = FastAPI()
+        >>> server.register_routes(app)
+    """
+
+    def __init__(
+        self,
+        env: Environment,
+        action_cls: Type[Action],
+        observation_cls: Type[Observation],
+    ):
+        """
+        Initialize HTTP server wrapper.
+
+        Args:
+            env: The Environment instance to wrap
+            action_cls: The Action subclass this environment expects
+            observation_cls: The Observation subclass this environment returns
+        """
+        self.env = env
+        self.action_cls = action_cls
+        self.observation_cls = observation_cls
+
+    def register_routes(self, app: Any) -> None:
+        """
+        Register HTTP routes on a FastAPI application.
+
+        Args:
+            app: FastAPI application instance
+        """
+
+        if not isinstance(app, FastAPI):
+            raise TypeError("app must be a FastAPI instance")
+
+        @app.post("/reset")
+        async def reset(request: Dict[str, Any] = Body(default={})) -> Dict[str, Any]:
+            """Reset endpoint - returns initial observation."""
+            # TODO: Handle seed, episode_id from request if provided
+            observation = self.env.reset()
+            return self._serialize_observation(observation)
+
+        @app.post("/step")
+        async def step(request: Dict[str, Any]) -> Dict[str, Any]:
+            """Step endpoint - executes action and returns observation."""
+            action_data = request.get("action", {})
+            # TODO: Handle timeout_s, request_id, episode_id from request if provided
+
+            # Deserialize action
+            action = self._deserialize_action(action_data)
+
+            # Execute step
+            observation = self.env.step(action)
+
+            # Return serialized observation
+            return self._serialize_observation(observation)
+
+        @app.get("/state")
+        async def get_state() -> Dict[str, Any]:
+            """State endpoint - returns current environment state."""
+            state = self.env.state
+            return asdict(state)
+
+        @app.get("/health")
+        async def health() -> Dict[str, str]:
+            """Health check endpoint."""
+            return {"status": "healthy"}
+
+
+    def _deserialize_action(self, action_data: Dict[str, Any]) -> Action:
+        """
+        Convert JSON dict to Action instance.
+
+        Args:
+            action_data: Dictionary containing action data
+
+        Returns:
+            Action instance
+
+        Note:
+            This is a simple implementation. Subclasses may need to override
+            for more complex deserialization logic.
+        """
+        # Remove metadata if present (it will be set via kw_only field)
+        metadata = action_data.pop("metadata", {})
+        action = self.action_cls(**action_data)
+        action.metadata = metadata
+        return action
+
+    def _serialize_observation(self, observation: Observation) -> Dict[str, Any]:
+        """
+        Convert Observation instance to JSON-compatible dict.
+
+        Args:
+            observation: Observation instance
+
+        Returns:
+            Dictionary compatible with HTTPEnvClient._parse_result()
+
+        The format matches what HTTPEnvClient expects:
+        {
+            "observation": {...},  # Observation fields
+            "reward": float | None,
+            "done": bool,
+        }
+        """
+        obs_dict = asdict(observation)
+
+        # Extract reward and done (these are part of StepResult on client side)
+        reward = obs_dict.pop("reward", None)
+        done = obs_dict.pop("done", False)
+        obs_dict.pop("metadata", None)  # Remove metadata from observation
+
+        # Return in HTTPEnvClient expected format
+        return {
+            "observation": obs_dict,
+            "reward": reward,
+            "done": done,
+        }
+
+def create_app(
+    env: Environment,
+    action_cls: Type[Action],
+    observation_cls: Type[Observation],
+    env_name: Optional[str] = None,
+) -> Any:
+    """
+    Create a FastAPI application with or without web interface.
+    
+    This function creates a FastAPI app with the web interface enabled by default,
+    including README integration for better user experience.
+    
+    Args:
+        env: The Environment instance to serve
+        action_cls: The Action subclass this environment expects
+        observation_cls: The Observation subclass this environment returns
+        env_name: Optional environment name for README loading
+        
+    Returns:
+        FastAPI application instance with or without web interface and README integration
+    """
+    # Check if web interface should be enabled
+    # This can be controlled via environment variable or build argument
+    enable_web = (
+        os.getenv("ENABLE_WEB_INTERFACE", "false").lower() in ("true", "1", "yes")
+    )
+
+    if enable_web:
+        # Import web interface only when needed
+        from .web_interface import create_web_interface_app
+        return create_web_interface_app(env, action_cls, observation_cls, env_name)
+    else:
+        # Use standard FastAPI app without web interface
+        return create_fastapi_app(env, action_cls, observation_cls)
+    
+
+def create_fastapi_app(
+    env: Environment,
+    action_cls: Type[Action],
+    observation_cls: Type[Observation],
+) -> Any:
+    """
+    Create a FastAPI application with routes for the given environment.
+
+    Args:
+        env: The Environment instance to serve
+        action_cls: The Action subclass this environment expects
+        observation_cls: The Observation subclass this environment returns
+
+    Returns:
+        FastAPI application instance with routes registered
+
+    Example:
+        >>> from envs.coding_env.server import CodeExecutionEnvironment
+        >>> from envs.coding_env.models import CodeAction, CodeObservation
+        >>>
+        >>> env = CodeExecutionEnvironment()
+        >>> app = create_fastapi_app(env, CodeAction, CodeObservation)
+        >>>
+        >>> # Run with: uvicorn module:app --host 0.0.0.0 --port 8000
+    """
+    try:
+        from fastapi import FastAPI
+    except ImportError:
+        raise ImportError(
+            "FastAPI is required. Install with: pip install fastapi uvicorn"
+        )
+
+    app = FastAPI(title="Environment HTTP Server")
+    server = HTTPEnvServer(env, action_cls, observation_cls)
+    server.register_routes(app)
+    return app

src/core/env_server/interfaces.py

@@ -0,0 +1,118 @@
+# 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.
+
+from abc import ABC, abstractmethod
+from typing import Any, Protocol, TypedDict
+
+from .types import Action, Observation, State
+
+
+class Message(TypedDict):
+    """A message in a conversation.
+
+    Compatible with Huggingface chat template format.
+    """
+
+    role: str
+    content: str
+
+
+class ModelTokenizer(Protocol):
+    """Protocol for tokenizers that support chat templates.
+
+    This protocol defines the interface that tokenizers must implement
+    to work with chat-based environments. It's compatible with
+    Huggingface transformers tokenizers.
+    """
+
+    def apply_chat_template(
+        self,
+        conversation: list[Message],
+        tokenize: bool = True,
+        return_tensors: str | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        """Apply a chat template to format and optionally tokenize a conversation.
+
+        Args:
+            conversation: List of message dictionaries with 'role' and 'content'
+            tokenize: Whether to tokenize the output
+            return_tensors: Format for returned tensors ('pt' for PyTorch)
+            **kwargs: Additional arguments
+
+        Returns:
+            Formatted and optionally tokenized conversation
+        """
+        ...
+
+    def decode(
+        self, token_ids: Any, skip_special_tokens: bool = False, **kwargs: Any
+    ) -> str:
+        """Decode token IDs back to text.
+
+        Args:
+            token_ids: Token IDs to decode
+            skip_special_tokens: Whether to skip special tokens in output
+            **kwargs: Additional arguments
+
+        Returns:
+            Decoded text string
+        """
+        ...
+
+
+class Transform(ABC):
+    """Transform observations to add rewards, metrics, or other modifications.
+
+    Transforms follow the TorchRL pattern where they take an observation
+    and return a (potentially modified) observation. This allows for
+    flexible reward computation and observation augmentation.
+    """
+
+    @abstractmethod
+    def __call__(self, observation: Observation) -> Observation:
+        """Transform an observation.
+
+        Args:
+            observation: The input observation
+
+        Returns:
+            The transformed observation
+        """
+        pass
+
+
+class Environment(ABC):
+    """Base class for all environment servers following Gym/Gymnasium API.
+
+    Args:
+        transform: Optional transform to apply to observations
+    """
+
+    def __init__(self, transform: Transform | None = None):
+        self.transform = transform
+
+    @abstractmethod
+    def reset(self) -> Observation:
+        """Reset the environment and return initial observation."""
+        pass
+
+    @abstractmethod
+    def step(self, action: Action) -> Observation:
+        """Take a step in the environment."""
+        pass
+
+    @property
+    @abstractmethod
+    def state(self) -> State:
+        """Get the current environment state."""
+        pass
+
+    def _apply_transform(self, observation: Observation) -> Observation:
+        """Apply transform if one is provided."""
+        if self.transform is not None:
+            return self.transform(observation)
+        return observation

src/core/env_server/types.py

@@ -0,0 +1,57 @@
+# 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.
+
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional, Union
+
+
+# Type aliases
+Scalar = Union[int, float, bool]
+
+
+@dataclass(kw_only=True)
+class Action:
+    """Base class for all environment actions."""
+
+    metadata: Dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass(kw_only=True)
+class Observation:
+    """Base class for all environment observations."""
+
+    done: bool = False
+    reward: Union[bool, int, float, None] = None
+    metadata: Dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class State:
+    """Base class for environment state."""
+
+    episode_id: Optional[str] = None
+    step_count: int = 0
+
+
+@dataclass
+class CodeExecResult:
+    """Result of code execution containing stdout, stderr, and exit code."""
+
+    stdout: str
+    stderr: str
+    exit_code: int
+
+
+@dataclass
+class EnvironmentMetadata:
+    """Metadata about an environment for documentation and UI purposes."""
+    
+    name: str
+    description: str
+    readme_content: Optional[str] = None
+    version: Optional[str] = None
+    author: Optional[str] = None
+    documentation_url: Optional[str] = None

src/core/env_server/web_interface.py

@@ -0,0 +1,1613 @@
+# 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.
+
+"""
+Web interface for OpenEnv environments.
+
+This module provides a web-based interface for interacting with OpenEnv environments,
+including a two-pane layout for HumanAgent interaction and state observation.
+"""
+
+from __future__ import annotations
+
+import json
+import time
+from dataclasses import asdict, dataclass
+from typing import Any, Dict, List, Optional, Type
+from datetime import datetime
+
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect, Request
+from fastapi.responses import HTMLResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel
+
+from .interfaces import Environment
+from .types import Action, Observation, State, EnvironmentMetadata
+
+
+def load_environment_metadata(env: Environment, env_name: Optional[str] = None) -> EnvironmentMetadata:
+    """
+    Load environment metadata including README content.
+    
+    Args:
+        env: The environment instance
+        env_name: Optional environment name for README file lookup
+        
+    Returns:
+        EnvironmentMetadata with loaded information
+    """
+    # Try to get metadata from environment if it has a method for it
+    if hasattr(env, 'get_metadata'):
+        return env.get_metadata()
+    
+    # Default metadata
+    metadata = EnvironmentMetadata(
+        name=env_name or env.__class__.__name__,
+        description=f"{env.__class__.__name__} environment",
+        version="1.0.0"
+    )
+    
+    # Try to load README from file system
+    readme_content = _load_readme_from_filesystem(env_name)
+    if readme_content:
+        metadata.readme_content = readme_content
+    
+    return metadata
+
+
+def _load_readme_from_filesystem(env_name: Optional[str]) -> Optional[str]:
+    """
+    Load README content from the filesystem.
+    
+    Tries multiple locations:
+    1. Container filesystem: /app/README.md
+    2. Local development: src/envs/{env_name}/README.md
+    3. Environment variable: ENV_README_PATH
+    """
+    import os
+    from pathlib import Path
+    
+    # Try container filesystem first
+    container_readme = Path("/app/README.md")
+    if container_readme.exists():
+        try:
+            return container_readme.read_text(encoding='utf-8')
+        except Exception:
+            pass
+    
+    # Try environment variable path
+    custom_path = os.environ.get("ENV_README_PATH")
+    if custom_path and Path(custom_path).exists():
+        try:
+            return Path(custom_path).read_text(encoding='utf-8')
+        except Exception:
+            pass
+    
+    # Try local development path
+    if env_name:
+        local_readme = Path(f"src/envs/{env_name}/README.md")
+        if local_readme.exists():
+            try:
+                return local_readme.read_text(encoding='utf-8')
+            except Exception:
+                pass
+    
+    return None
+
+
+@dataclass
+class ActionLog:
+    """Log entry for an action taken."""
+    timestamp: str
+    action: Dict[str, Any]
+    observation: Dict[str, Any]
+    reward: Optional[float]
+    done: bool
+    step_count: int
+
+
+@dataclass
+class EpisodeState:
+    """Current episode state for the web interface."""
+    episode_id: Optional[str]
+    step_count: int
+    current_observation: Optional[Dict[str, Any]]
+    action_logs: List[ActionLog]
+    is_reset: bool = True
+
+
+class WebInterfaceManager:
+    """Manages the web interface for an environment."""
+    
+    def __init__(
+        self,
+        env: Environment,
+        action_cls: Type[Action],
+        observation_cls: Type[Observation],
+        metadata: Optional[EnvironmentMetadata] = None,
+    ):
+        self.env = env
+        self.action_cls = action_cls
+        self.observation_cls = observation_cls
+        self.metadata = metadata or EnvironmentMetadata(
+            name=env.__class__.__name__,
+            description=f"{env.__class__.__name__} environment"
+        )
+        self.episode_state = EpisodeState(
+            episode_id=None,
+            step_count=0,
+            current_observation=None,
+            action_logs=[]
+        )
+        self.connected_clients: List[WebSocket] = []
+    
+    async def connect_websocket(self, websocket: WebSocket):
+        """Connect a new WebSocket client."""
+        await websocket.accept()
+        self.connected_clients.append(websocket)
+        
+        # Send current state to the new client
+        await self._send_state_update()
+    
+    async def disconnect_websocket(self, websocket: WebSocket):
+        """Disconnect a WebSocket client."""
+        if websocket in self.connected_clients:
+            self.connected_clients.remove(websocket)
+    
+    async def _send_state_update(self):
+        """Send current state to all connected clients."""
+        if not self.connected_clients:
+            return
+            
+        state_data = {
+            "type": "state_update",
+            "episode_state": asdict(self.episode_state)
+        }
+        
+        # Send to all connected clients
+        disconnected_clients = []
+        for client in self.connected_clients:
+            try:
+                await client.send_text(json.dumps(state_data))
+            except:
+                disconnected_clients.append(client)
+        
+        # Remove disconnected clients
+        for client in disconnected_clients:
+            self.connected_clients.remove(client)
+    
+    async def reset_environment(self) -> Dict[str, Any]:
+        """Reset the environment and update state."""
+        observation = self.env.reset()
+        state = self.env.state
+        
+        # Update episode state
+        self.episode_state.episode_id = state.episode_id
+        self.episode_state.step_count = 0
+        self.episode_state.current_observation = asdict(observation)
+        self.episode_state.action_logs = []
+        self.episode_state.is_reset = True
+        
+        # Send state update
+        await self._send_state_update()
+        
+        return {
+            "observation": asdict(observation),
+            "reward": observation.reward,
+            "done": observation.done,
+        }
+    
+    async def step_environment(self, action_data: Dict[str, Any]) -> Dict[str, Any]:
+        """Execute a step in the environment and update state."""
+        # Deserialize action
+        action = self._deserialize_action(action_data)
+        
+        # Execute step
+        observation = self.env.step(action)
+        state = self.env.state
+        
+        # Create action log
+        action_log = ActionLog(
+            timestamp=datetime.now().isoformat(),
+            action=asdict(action),
+            observation=asdict(observation),
+            reward=observation.reward,
+            done=observation.done,
+            step_count=state.step_count
+        )
+        
+        # Update episode state
+        self.episode_state.episode_id = state.episode_id
+        self.episode_state.step_count = state.step_count
+        self.episode_state.current_observation = asdict(observation)
+        self.episode_state.action_logs.append(action_log)
+        self.episode_state.is_reset = False
+        
+        # Send state update
+        await self._send_state_update()
+        
+        return {
+            "observation": asdict(observation),
+            "reward": observation.reward,
+            "done": observation.done,
+        }
+    
+    def get_state(self) -> Dict[str, Any]:
+        """Get current environment state."""
+        state = self.env.state
+        return asdict(state)
+    
+    def _deserialize_action(self, action_data: Dict[str, Any]) -> Action:
+        """Convert JSON dict to Action instance."""
+        metadata = action_data.pop("metadata", {})
+        
+        # Handle tensor fields that come from JSON as lists
+        processed_data = {}
+        for key, value in action_data.items():
+            if key == "tokens" and isinstance(value, (list, str)):
+                # Convert list or string to tensor
+                if isinstance(value, str):
+                    # If it's a string, try to parse it as a list of numbers
+                    try:
+                        import json
+                        value = json.loads(value)
+                    except:
+                        # If parsing fails, treat as empty list
+                        value = []
+                if isinstance(value, list):
+                    import torch
+                    processed_data[key] = torch.tensor(value, dtype=torch.long)
+                else:
+                    processed_data[key] = value
+            elif key == "action_id" and isinstance(value, str):
+                # Convert action_id from string to int
+                try:
+                    processed_data[key] = int(value)
+                except ValueError:
+                    # If conversion fails, keep original value
+                    processed_data[key] = value
+            else:
+                processed_data[key] = value
+        
+        action = self.action_cls(**processed_data)
+        action.metadata = metadata
+        return action
+
+
+def create_web_interface_app(
+    env: Environment,
+    action_cls: Type[Action],
+    observation_cls: Type[Observation],
+    env_name: Optional[str] = None,
+) -> FastAPI:
+    """
+    Create a FastAPI application with web interface for the given environment.
+    
+    Args:
+        env: The Environment instance to serve
+        action_cls: The Action subclass this environment expects
+        observation_cls: The Observation subclass this environment returns
+        env_name: Optional environment name for README loading
+        
+    Returns:
+        FastAPI application instance with web interface
+    """
+    from .http_server import create_fastapi_app
+    
+    # Create the base environment app
+    app = create_fastapi_app(env, action_cls, observation_cls)
+    
+    # Load environment metadata
+    metadata = load_environment_metadata(env, env_name)
+    
+    # Create web interface manager
+    web_manager = WebInterfaceManager(env, action_cls, observation_cls, metadata)
+    
+    # Add web interface routes
+    @app.get("/web", response_class=HTMLResponse)
+    async def web_interface():
+        """Serve the web interface."""
+        return get_web_interface_html(action_cls, web_manager.metadata)
+    
+    @app.get("/web/metadata")
+    async def web_metadata():
+        """Get environment metadata."""
+        return asdict(web_manager.metadata)
+    
+    @app.websocket("/ws")
+    async def websocket_endpoint(websocket: WebSocket):
+        """WebSocket endpoint for real-time updates."""
+        await web_manager.connect_websocket(websocket)
+        try:
+            while True:
+                # Keep connection alive
+                await websocket.receive_text()
+        except WebSocketDisconnect:
+            await web_manager.disconnect_websocket(websocket)
+    
+    @app.post("/web/reset")
+    async def web_reset():
+        """Reset endpoint for web interface."""
+        return await web_manager.reset_environment()
+    
+    @app.post("/web/step")
+    async def web_step(request: Dict[str, Any]):
+        """Step endpoint for web interface."""
+        # Check if this is a message-based request (chat environment)
+        if "message" in request:
+            message = request["message"]
+            # Convert message to action using the environment's message_to_action method
+            action = web_manager.env.message_to_action(message)
+            action_data = {"tokens": action.tokens.tolist()}
+        else:
+            action_data = request.get("action", {})
+        
+        return await web_manager.step_environment(action_data)
+    
+    @app.get("/web/state")
+    async def web_state():
+        """State endpoint for web interface."""
+        return web_manager.get_state()
+    
+    return app
+
+
+def get_web_interface_html(action_cls: Type[Action], metadata: Optional[EnvironmentMetadata] = None) -> str:
+    """Generate the HTML for the web interface."""
+    
+    # Check if this is a chat environment by looking for tokens field
+    is_chat_env = False
+    if hasattr(action_cls, '__dataclass_fields__'):
+        for field_name, field_info in action_cls.__dataclass_fields__.items():
+            if field_name == 'tokens' and hasattr(field_info.type, '__name__') and 'Tensor' in field_info.type.__name__:
+                is_chat_env = True
+                break
+    
+    # Get action fields for dynamic form generation with enhanced metadata
+    action_fields = _extract_action_fields(action_cls)
+    
+    return f"""
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>OpenEnv Web Interface</title>
+    <style>
+        * {{
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+        }}
+        
+        body {{
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            background-color: #f5f5f5;
+            height: 100vh;
+            overflow: hidden;
+        }}
+        
+        .container {{
+            display: flex;
+            height: 100vh;
+        }}
+        
+        .left-pane {{
+            width: 50%;
+            background: white;
+            border-right: 1px solid #e0e0e0;
+            display: flex;
+            flex-direction: column;
+        }}
+        
+        .right-pane {{
+            width: 50%;
+            background: #fafafa;
+            display: flex;
+            flex-direction: column;
+        }}
+        
+        .pane-header {{
+            padding: 20px;
+            border-bottom: 1px solid #e0e0e0;
+            background: #f8f9fa;
+            font-weight: 600;
+            font-size: 16px;
+        }}
+        
+        .pane-content {{
+            flex: 1;
+            padding: 20px;
+            overflow-y: auto;
+        }}
+        
+        .action-form {{
+            background: white;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 20px;
+            margin-bottom: 20px;
+        }}
+        
+        .form-group {{
+            margin-bottom: 15px;
+        }}
+        
+        .form-group label {{
+            display: block;
+            margin-bottom: 5px;
+            font-weight: 500;
+            color: #333;
+        }}
+        
+        .form-group input, .form-group textarea {{
+            width: 100%;
+            padding: 8px 12px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+        }}
+        
+        .form-group input:focus, .form-group textarea:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        .btn {{
+            background: #007bff;
+            color: white;
+            border: none;
+            padding: 10px 20px;
+            border-radius: 4px;
+            cursor: pointer;
+            font-size: 14px;
+            margin-right: 10px;
+            margin-bottom: 10px;
+        }}
+        
+        .btn:hover {{
+            background: #0056b3;
+        }}
+        
+        .btn:disabled {{
+            background: #6c757d;
+            cursor: not-allowed;
+        }}
+        
+        .btn-secondary {{
+            background: #6c757d;
+        }}
+        
+        .btn-secondary:hover {{
+            background: #545b62;
+        }}
+        
+        .state-display {{
+            background: white;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 15px;
+            margin-bottom: 20px;
+        }}
+        
+        .state-item {{
+            margin-bottom: 8px;
+        }}
+        
+        .state-label {{
+            font-weight: 500;
+            color: #666;
+        }}
+        
+        .state-value {{
+            color: #333;
+            font-family: monospace;
+        }}
+        
+        .logs-container {{
+            background: white;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 15px;
+            max-height: 400px;
+            overflow-y: auto;
+        }}
+        
+        .log-entry {{
+            border-bottom: 1px solid #f0f0f0;
+            padding: 10px 0;
+        }}
+        
+        .log-entry:last-child {{
+            border-bottom: none;
+        }}
+        
+        .log-timestamp {{
+            font-size: 12px;
+            color: #666;
+            margin-bottom: 5px;
+        }}
+        
+        .log-action {{
+            background: #e3f2fd;
+            padding: 8px;
+            border-radius: 4px;
+            margin-bottom: 5px;
+            font-family: monospace;
+            font-size: 12px;
+        }}
+        
+        .log-observation {{
+            background: #f3e5f5;
+            padding: 8px;
+            border-radius: 4px;
+            font-family: monospace;
+            font-size: 12px;
+        }}
+        
+        .log-reward {{
+            font-weight: 600;
+            color: #28a745;
+        }}
+        
+        .log-done {{
+            font-weight: 600;
+            color: #dc3545;
+        }}
+        
+        .status-indicator {{
+            display: inline-block;
+            width: 8px;
+            height: 8px;
+            border-radius: 50%;
+            margin-right: 8px;
+        }}
+        
+        .status-connected {{
+            background: #28a745;
+        }}
+        
+        .status-disconnected {{
+            background: #dc3545;
+        }}
+        
+        .json-display {{
+            background: #f8f9fa;
+            border: 1px solid #e9ecef;
+            border-radius: 4px;
+            padding: 10px;
+            font-family: monospace;
+            font-size: 12px;
+            white-space: pre-wrap;
+            max-height: 200px;
+            overflow-y: auto;
+        }}
+        
+        /* Chat Interface Styles */
+        .chat-interface {{
+            background: white;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 20px;
+            margin-bottom: 20px;
+        }}
+        
+        .chat-messages {{
+            background: #f8f9fa;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 15px;
+            margin-bottom: 15px;
+            max-height: 400px;
+            overflow-y: auto;
+        }}
+        
+        .chat-message {{
+            margin-bottom: 15px;
+            padding: 10px;
+            border-radius: 8px;
+        }}
+        
+        .chat-message:last-child {{
+            margin-bottom: 0;
+        }}
+        
+        .chat-message.user {{
+            background: #e3f2fd;
+            margin-left: 20px;
+        }}
+        
+        .chat-message.assistant {{
+            background: #f3e5f5;
+            margin-right: 20px;
+        }}
+        
+        .chat-message.system {{
+            background: #e8f5e8;
+            font-style: italic;
+        }}
+        
+        .message-role {{
+            font-weight: 600;
+            font-size: 12px;
+            color: #666;
+            margin-bottom: 5px;
+        }}
+        
+        .message-content {{
+            font-size: 14px;
+            line-height: 1.4;
+        }}
+        
+        .chat-input-container {{
+            border-top: 1px solid #e0e0e0;
+            padding-top: 15px;
+        }}
+        
+        .role-selector {{
+            margin-bottom: 10px;
+        }}
+        
+        .role-selector label {{
+            font-weight: 500;
+            margin-right: 10px;
+        }}
+        
+        .role-selector select {{
+            padding: 5px 10px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+        }}
+        
+        .message-input {{
+            display: flex;
+            gap: 10px;
+            align-items: flex-end;
+        }}
+        
+        .message-input textarea {{
+            flex: 1;
+            padding: 10px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            resize: vertical;
+            font-family: inherit;
+        }}
+        
+        .message-input textarea:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        /* Instructions Section Styles */
+        .instructions-section {{
+            background: white;
+            border: 1px solid #e0e0e0;
+            border-radius: 8px;
+            padding: 20px;
+            margin-bottom: 20px;
+        }}
+        
+        .instructions-header {{
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+            margin-bottom: 15px;
+        }}
+        
+        .instructions-title {{
+            font-size: 18px;
+            font-weight: 600;
+            color: #333;
+            margin: 0;
+        }}
+        
+        .instructions-toggle {{
+            background: #f8f9fa;
+            border: 1px solid #dee2e6;
+            border-radius: 4px;
+            padding: 5px 10px;
+            cursor: pointer;
+            font-size: 12px;
+            color: #6c757d;
+        }}
+        
+        .instructions-toggle:hover {{
+            background: #e9ecef;
+        }}
+        
+        .instructions-content {{
+            display: none;
+            max-height: 400px;
+            overflow-y: auto;
+            border-top: 1px solid #e0e0e0;
+            padding-top: 15px;
+        }}
+        
+        .instructions-content.expanded {{
+            display: block;
+        }}
+        
+        .instructions-content h1,
+        .instructions-content h2,
+        .instructions-content h3 {{
+            color: #333;
+            margin-top: 20px;
+            margin-bottom: 10px;
+        }}
+        
+        .instructions-content h1 {{
+            font-size: 24px;
+            border-bottom: 2px solid #007bff;
+            padding-bottom: 10px;
+        }}
+        
+        .instructions-content h2 {{
+            font-size: 20px;
+        }}
+        
+        .instructions-content h3 {{
+            font-size: 16px;
+        }}
+        
+        .instructions-content p {{
+            margin-bottom: 10px;
+            line-height: 1.6;
+        }}
+        
+        .instructions-content code {{
+            background: #f8f9fa;
+            padding: 2px 4px;
+            border-radius: 3px;
+            font-family: monospace;
+            font-size: 14px;
+        }}
+        
+        .instructions-content pre {{
+            background: #f8f9fa;
+            border: 1px solid #e9ecef;
+            border-radius: 4px;
+            padding: 15px;
+            overflow-x: auto;
+            margin: 10px 0;
+        }}
+        
+        .instructions-content pre code {{
+            background: none;
+            padding: 0;
+        }}
+        
+        .instructions-content ul,
+        .instructions-content ol {{
+            margin: 10px 0;
+            padding-left: 20px;
+        }}
+        
+        .instructions-content li {{
+            margin-bottom: 5px;
+        }}
+        
+        .instructions-content table {{
+            border-collapse: collapse;
+            width: 100%;
+            margin: 15px 0;
+        }}
+        
+        .instructions-content th,
+        .instructions-content td {{
+            border: 1px solid #dee2e6;
+            padding: 8px 12px;
+            text-align: left;
+        }}
+        
+        .instructions-content th {{
+            background: #f8f9fa;
+            font-weight: 600;
+        }}
+        
+        /* Enhanced Form Styles */
+        .help-text {{
+            display: block;
+            margin-top: 5px;
+            font-size: 12px;
+            color: #6c757d;
+            font-style: italic;
+        }}
+        
+        .form-group label {{
+            font-weight: 500;
+            color: #333;
+            margin-bottom: 5px;
+        }}
+        
+        .form-group select {{
+            width: 100%;
+            padding: 8px 12px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+            background-color: white;
+        }}
+        
+        .form-group select:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        .form-group textarea {{
+            width: 100%;
+            padding: 8px 12px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+            font-family: inherit;
+            resize: vertical;
+        }}
+        
+        .form-group textarea:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        .form-group input[type="number"] {{
+            width: 100%;
+            padding: 8px 12px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+        }}
+        
+        .form-group input[type="number"]:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        .form-group input[type="text"]:focus {{
+            outline: none;
+            border-color: #007bff;
+            box-shadow: 0 0 0 2px rgba(0, 123, 255, 0.25);
+        }}
+        
+        .required-indicator {{
+            color: #dc3545;
+            font-weight: bold;
+        }}
+        
+        .form-group .field-description {{
+            font-size: 11px;
+            color: #666;
+            margin-top: 2px;
+            font-style: italic;
+        }}
+    </style>
+</head>
+<body>
+    <div class="container">
+        <!-- Left Pane: HumanAgent Interface -->
+        <div class="left-pane">
+            <div class="pane-header">
+                <span class="status-indicator status-disconnected" id="connection-status"></span>
+                HumanAgent Interface
+            </div>
+            <div class="pane-content">
+                <!-- Instructions Section -->
+                {_generate_instructions_section(metadata)}
+                
+                <!-- Action Form or Chat Interface -->
+                {_generate_action_interface(action_fields, is_chat_env)}
+                
+                <!-- Control Buttons -->
+                <div style="margin-bottom: 20px;">
+                    <button class="btn btn-secondary" id="reset-btn">Reset Environment</button>
+                    <button class="btn btn-secondary" id="state-btn">Get State</button>
+                </div>
+                
+                <!-- Current State Display -->
+                <div class="state-display">
+                    <h3>Current State</h3>
+                    <div id="current-state">
+                        <div class="state-item">
+                            <span class="state-label">Status:</span>
+                            <span class="state-value" id="env-status">Not initialized</span>
+                        </div>
+                        <div class="state-item">
+                            <span class="state-label">Episode ID:</span>
+                            <span class="state-value" id="episode-id">-</span>
+                        </div>
+                        <div class="state-item">
+                            <span class="state-label">Step Count:</span>
+                            <span class="state-value" id="step-count">0</span>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+        
+        <!-- Right Pane: State Observer -->
+        <div class="right-pane">
+            <div class="pane-header">
+                State Observer
+            </div>
+            <div class="pane-content">
+                <!-- Current Observation -->
+                <div class="state-display">
+                    <h3>Current Observation</h3>
+                    <div id="current-observation" class="json-display">
+                        No observation yet
+                    </div>
+                </div>
+                
+                <!-- Action Logs -->
+                <div class="logs-container">
+                    <h3>Action History</h3>
+                    <div id="action-logs">
+                        No actions taken yet
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <script>
+        class OpenEnvWebInterface {{
+            constructor() {{
+                this.ws = null;
+                this.isConnected = false;
+                this.init();
+            }}
+            
+            init() {{
+                this.connectWebSocket();
+                this.setupEventListeners();
+            }}
+            
+            connectWebSocket() {{
+                const protocol = window.location.protocol === 'https:' ? 'wss:' : 'ws:';
+                const wsUrl = `${{protocol}}//${{window.location.host}}/ws`;
+                
+                this.ws = new WebSocket(wsUrl);
+                
+                this.ws.onopen = () => {{
+                    this.isConnected = true;
+                    this.updateConnectionStatus(true);
+                    console.log('WebSocket connected');
+                }};
+                
+                this.ws.onmessage = (event) => {{
+                    const data = JSON.parse(event.data);
+                    if (data.type === 'state_update') {{
+                        this.updateUI(data.episode_state);
+                    }}
+                }};
+                
+                this.ws.onclose = () => {{
+                    this.isConnected = false;
+                    this.updateConnectionStatus(false);
+                    console.log('WebSocket disconnected');
+                    // Attempt to reconnect after 3 seconds
+                    setTimeout(() => this.connectWebSocket(), 3000);
+                }};
+                
+                this.ws.onerror = (error) => {{
+                    console.error('WebSocket error:', error);
+                }};
+            }}
+            
+            setupEventListeners() {{
+                // Instructions toggle
+                const instructionsToggle = document.getElementById('instructions-toggle');
+                const instructionsContent = document.getElementById('instructions-content');
+                if (instructionsToggle && instructionsContent) {{
+                    instructionsToggle.addEventListener('click', () => {{
+                        instructionsContent.classList.toggle('expanded');
+                        instructionsToggle.textContent = instructionsContent.classList.contains('expanded') 
+                            ? 'Hide Instructions' : 'Show Instructions';
+                    }});
+                }}
+                
+                // Check if this is a chat environment
+                const isChatEnv = document.getElementById('chat-messages') !== null;
+                
+                if (isChatEnv) {{
+                    // Chat environment event listeners
+                    document.getElementById('send-message-btn').addEventListener('click', () => {{
+                        this.sendMessage();
+                    }});
+                    
+                    // Send message on Enter (but allow Shift+Enter for new lines)
+                    document.getElementById('message-input').addEventListener('keydown', (e) => {{
+                        if (e.key === 'Enter' && !e.shiftKey) {{
+                            e.preventDefault();
+                            this.sendMessage();
+                        }}
+                    }});
+                }} else {{
+                    // Traditional action form submission
+                    const actionForm = document.getElementById('action-form');
+                    if (actionForm) {{
+                        actionForm.addEventListener('submit', (e) => {{
+                            e.preventDefault();
+                            this.submitAction();
+                        }});
+                    }}
+                }}
+                
+                // Reset button
+                document.getElementById('reset-btn').addEventListener('click', () => {{
+                    this.resetEnvironment();
+                }});
+                
+                // State button
+                document.getElementById('state-btn').addEventListener('click', () => {{
+                    this.getState();
+                }});
+            }}
+            
+            async sendMessage() {{
+                const messageInput = document.getElementById('message-input');
+                const roleSelect = document.getElementById('message-role');
+                const message = messageInput.value.trim();
+                const role = roleSelect.value;
+                
+                if (!message) {{
+                    return;
+                }}
+                
+                // Add message to chat display immediately
+                this.addMessageToChat(role, message);
+                
+                // Clear input
+                messageInput.value = '';
+                
+                try {{
+                    // Send message to server to convert to action and step
+                    const response = await fetch('/web/step', {{
+                        method: 'POST',
+                        headers: {{ 'Content-Type': 'application/json' }},
+                        body: JSON.stringify({{ 
+                            message: {{
+                                role: role,
+                                content: message
+                            }}
+                        }})
+                    }});
+                    
+                    if (!response.ok) {{
+                        throw new Error(`HTTP error! status: ${{response.status}}`);
+                    }}
+                    
+                    const result = await response.json();
+                    console.log('Message sent:', result);
+                }} catch (error) {{
+                    console.error('Error sending message:', error);
+                    alert('Error sending message: ' + error.message);
+                }}
+            }}
+            
+            addMessageToChat(role, content) {{
+                const chatMessages = document.getElementById('chat-messages');
+                const messageDiv = document.createElement('div');
+                messageDiv.className = `chat-message ${{role}}`;
+                
+                messageDiv.innerHTML = `
+                    <div class="message-role">${{role.charAt(0).toUpperCase() + role.slice(1)}}</div>
+                    <div class="message-content">${{content}}</div>
+                `;
+                
+                chatMessages.appendChild(messageDiv);
+                chatMessages.scrollTop = chatMessages.scrollHeight;
+            }}
+            
+            async submitAction() {{
+                const formData = new FormData(document.getElementById('action-form'));
+                const action = {{}};
+                
+                // Collect form data
+                for (const [key, value] of formData.entries()) {{
+                    if (value !== '') {{
+                        // Handle tensor fields (tokens) - convert comma-separated string to array
+                        if (key === 'tokens') {{
+                            try {{
+                                action[key] = value.split(',').map(x => parseInt(x.trim())).filter(x => !isNaN(x));
+                            }} catch (e) {{
+                                console.error('Error parsing tokens:', e);
+                                action[key] = [];
+                            }}
+                        }} else {{
+                            action[key] = value;
+                        }}
+                    }}
+                }}
+                
+                try {{
+                    const response = await fetch('/web/step', {{
+                        method: 'POST',
+                        headers: {{ 'Content-Type': 'application/json' }},
+                        body: JSON.stringify({{ action }})
+                    }});
+                    
+                    if (!response.ok) {{
+                        throw new Error(`HTTP error! status: ${{response.status}}`);
+                    }}
+                    
+                    const result = await response.json();
+                    console.log('Step result:', result);
+                }} catch (error) {{
+                    console.error('Error submitting action:', error);
+                    alert('Error submitting action: ' + error.message);
+                }}
+            }}
+            
+            async resetEnvironment() {{
+                try {{
+                    const response = await fetch('/web/reset', {{
+                        method: 'POST',
+                        headers: {{ 'Content-Type': 'application/json' }}
+                    }});
+                    
+                    if (!response.ok) {{
+                        throw new Error(`HTTP error! status: ${{response.status}}`);
+                    }}
+                    
+                    const result = await response.json();
+                    console.log('Reset result:', result);
+                }} catch (error) {{
+                    console.error('Error resetting environment:', error);
+                    alert('Error resetting environment: ' + error.message);
+                }}
+            }}
+            
+            async getState() {{
+                try {{
+                    const response = await fetch('/web/state');
+                    const state = await response.json();
+                    console.log('Current state:', state);
+                    alert('Current state: ' + JSON.stringify(state, null, 2));
+                }} catch (error) {{
+                    console.error('Error getting state:', error);
+                    alert('Error getting state: ' + error.message);
+                }}
+            }}
+            
+            updateConnectionStatus(connected) {{
+                const indicator = document.getElementById('connection-status');
+                if (connected) {{
+                    indicator.className = 'status-indicator status-connected';
+                }} else {{
+                    indicator.className = 'status-indicator status-disconnected';
+                }}
+            }}
+            
+            updateUI(episodeState) {{
+                // Check if this is a chat environment
+                const isChatEnv = document.getElementById('chat-messages') !== null;
+                
+                // Update current state
+                document.getElementById('env-status').textContent = 
+                    episodeState.is_reset ? 'Reset' : 'Running';
+                document.getElementById('episode-id').textContent = 
+                    episodeState.episode_id || '-';
+                document.getElementById('step-count').textContent = 
+                    episodeState.step_count.toString();
+                
+                if (isChatEnv) {{
+                    // Update chat interface
+                    this.updateChatInterface(episodeState);
+                }} else {{
+                    // Update traditional observation display
+                    const observationDiv = document.getElementById('current-observation');
+                    if (episodeState.current_observation) {{
+                        observationDiv.textContent = JSON.stringify(
+                            episodeState.current_observation, null, 2
+                        );
+                    }} else {{
+                        observationDiv.textContent = 'No observation yet';
+                    }}
+                }}
+                
+                // Update action logs
+                const logsDiv = document.getElementById('action-logs');
+                if (episodeState.action_logs.length === 0) {{
+                    logsDiv.innerHTML = 'No actions taken yet';
+                }} else {{
+                    logsDiv.innerHTML = episodeState.action_logs.map(log => `
+                        <div class="log-entry">
+                            <div class="log-timestamp">${{log.timestamp}} (Step ${{log.step_count}})</div>
+                            <div class="log-action">Action: ${{JSON.stringify(log.action, null, 2)}}</div>
+                            <div class="log-observation">Observation: ${{JSON.stringify(log.observation, null, 2)}}</div>
+                            <div>
+                                <span class="log-reward">Reward: ${{log.reward !== null ? log.reward : 'None'}}</span>
+                                ${{log.done ? '<span class="log-done">DONE</span>' : ''}}
+                            </div>
+                        </div>
+                    `).join('');
+                }}
+            }}
+            
+            updateChatInterface(episodeState) {{
+                const chatMessages = document.getElementById('chat-messages');
+                if (!chatMessages) return;
+                
+                // Clear existing messages (except system message)
+                const systemMessage = chatMessages.querySelector('.chat-message.system');
+                chatMessages.innerHTML = '';
+                if (systemMessage) {{
+                    chatMessages.appendChild(systemMessage);
+                }}
+                
+                // Add messages from current observation
+                if (episodeState.current_observation && episodeState.current_observation.messages) {{
+                    episodeState.current_observation.messages.forEach(msg => {{
+                        this.addMessageToChat(msg.role, msg.content);
+                    }});
+                }}
+            }}
+        }}
+        
+        // Initialize the web interface when the page loads
+        document.addEventListener('DOMContentLoaded', () => {{
+            new OpenEnvWebInterface();
+        }});
+    </script>
+</body>
+</html>
+    """.replace('{_generate_action_form_fields(action_fields)}', _generate_action_form_fields(action_fields))
+
+
+def _generate_instructions_section(metadata: Optional[EnvironmentMetadata]) -> str:
+    """Generate the instructions section with environment documentation."""
+    if not metadata or not metadata.readme_content:
+        return ''
+    
+    # Convert markdown to HTML (basic conversion)
+    import re
+    html_content = _markdown_to_html(metadata.readme_content)
+    
+    return f'''
+                <!-- Instructions Section -->
+                <div class="instructions-section">
+                    <div class="instructions-header">
+                        <h3 class="instructions-title">{metadata.name}</h3>
+                        <button class="instructions-toggle" id="instructions-toggle">Show Instructions</button>
+                    </div>
+                    <div class="instructions-content" id="instructions-content">
+                        <div class="instructions-readme">
+                            {html_content}
+                        </div>
+                    </div>
+                </div>
+    '''
+
+
+def _extract_action_fields(action_cls: Type[Action]) -> List[Dict[str, Any]]:
+    """Extract enhanced field metadata from Action class for form generation."""
+    import typing
+    from typing import get_origin, get_args
+    
+    action_fields = []
+    if not hasattr(action_cls, '__dataclass_fields__'):
+        return action_fields
+    
+    for field_name, field_info in action_cls.__dataclass_fields__.items():
+        if field_name == 'metadata':
+            continue
+            
+        field_type = field_info.type
+        field_metadata = _extract_field_metadata(field_name, field_info)
+        
+        # Determine input type based on field type
+        input_type = _determine_input_type(field_type)
+        
+        # Check if field is required
+        is_required = field_info.default is field_info.default_factory
+        
+        action_fields.append({
+            'name': field_name,
+            'type': input_type,
+            'required': is_required,
+            'description': field_metadata.get('description', ''),
+            'default_value': field_metadata.get('default_value'),
+            'choices': field_metadata.get('choices', []),
+            'min_value': field_metadata.get('min_value'),
+            'max_value': field_metadata.get('max_value'),
+            'placeholder': field_metadata.get('placeholder', ''),
+            'help_text': field_metadata.get('help_text', ''),
+        })
+    
+    return action_fields
+
+
+def _extract_field_metadata(field_name: str, field_info) -> Dict[str, Any]:
+    """Extract metadata from dataclass field including docstring and type hints."""
+    import typing
+    from typing import get_origin, get_args, Literal, Union, Optional
+    
+    metadata = {}
+    
+    # Extract description from field docstring or annotation
+    if hasattr(field_info, 'metadata') and field_info.metadata:
+        # Check for custom metadata
+        for meta in field_info.metadata:
+            if isinstance(meta, dict):
+                metadata.update(meta)
+    
+    # Extract type information
+    field_type = field_info.type
+    origin = get_origin(field_type)
+    
+    # Handle Literal types for dropdown choices
+    if origin is Literal:
+        args = get_args(field_type)
+        metadata['choices'] = list(args)
+    
+    # Handle Optional types
+    if origin is Union:
+        args = get_args(field_type)
+        if len(args) == 2 and type(None) in args:
+            # This is Optional[SomeType]
+            non_none_type = args[0] if args[1] is type(None) else args[1]
+            metadata['optional'] = True
+            # Recursively check the non-None type for choices
+            if get_origin(non_none_type) is Literal:
+                metadata['choices'] = list(get_args(non_none_type))
+        else:
+            # Regular Union type
+            metadata['choices'] = [str(arg) for arg in args if arg is not type(None)]
+    
+    # Handle numeric constraints
+    if field_type in (int, float):
+        # Check for common constraint patterns in field name
+        if 'count' in field_name.lower() or 'num' in field_name.lower():
+            metadata['min_value'] = 0
+        if 'id' in field_name.lower():
+            metadata['min_value'] = 0
+    
+    # Generate placeholder text
+    if 'message' in field_name.lower():
+        metadata['placeholder'] = f'Enter {field_name.replace("_", " ")}...'
+    elif 'code' in field_name.lower():
+        metadata['placeholder'] = 'Enter Python code here...'
+    elif 'tokens' in field_name.lower():
+        metadata['placeholder'] = 'Enter comma-separated token IDs (e.g., 1,2,3,4,5)'
+    else:
+        metadata['placeholder'] = f'Enter {field_name.replace("_", " ")}...'
+    
+    # Generate help text based on field name and type
+    if 'action_id' in field_name.lower():
+        metadata['help_text'] = 'The action ID to execute in the environment'
+    elif 'game_name' in field_name.lower():
+        metadata['help_text'] = 'Name of the game or environment'
+    elif 'tokens' in field_name.lower():
+        metadata['help_text'] = 'Token IDs as a comma-separated list of integers'
+    elif 'code' in field_name.lower():
+        metadata['help_text'] = 'Python code to execute in the environment'
+    elif 'message' in field_name.lower():
+        metadata['help_text'] = 'Text message to send'
+    
+    return metadata
+
+
+def _determine_input_type(field_type) -> str:
+    """Determine the appropriate HTML input type for a field type."""
+    import typing
+    from typing import get_origin, get_args, Literal, Union
+    
+    # Handle direct types
+    if field_type == str:
+        return "text"
+    elif field_type == int:
+        return "number"
+    elif field_type == float:
+        return "number"
+    elif field_type == bool:
+        return "checkbox"
+    
+    # Handle complex types
+    origin = get_origin(field_type)
+    
+    if origin is Literal:
+        return "select"
+    elif origin is Union:
+        args = get_args(field_type)
+        if len(args) == 2 and type(None) in args:
+            # Optional type - use the non-None type
+            non_none_type = args[0] if args[1] is type(None) else args[1]
+            return _determine_input_type(non_none_type)
+        elif all(isinstance(arg, str) for arg in args if arg is not type(None)):
+            return "select"
+        else:
+            return "text"
+    elif hasattr(field_type, '__name__') and 'Tensor' in field_type.__name__:
+        return "tensor"
+    else:
+        return "text"
+
+
+def _markdown_to_html(markdown: str) -> str:
+    """Convert basic markdown to HTML for README display."""
+    import html
+    import re
+    
+    # Escape HTML first
+    html_content = html.escape(markdown)
+    
+    # Convert headers
+    html_content = re.sub(r'^# (.*?)$', r'<h1>\1</h1>', html_content, flags=re.MULTILINE)
+    html_content = re.sub(r'^## (.*?)$', r'<h2>\1</h2>', html_content, flags=re.MULTILINE)
+    html_content = re.sub(r'^### (.*?)$', r'<h3>\1</h3>', html_content, flags=re.MULTILINE)
+    
+    # Convert code blocks
+    html_content = re.sub(r'```(.*?)\n(.*?)\n```', r'<pre><code>\2</code></pre>', html_content, flags=re.DOTALL)
+    html_content = re.sub(r'`([^`]+)`', r'<code>\1</code>', html_content)
+    
+    # Convert bold and italic
+    html_content = re.sub(r'\*\*(.*?)\*\*', r'<strong>\1</strong>', html_content)
+    html_content = re.sub(r'\*(.*?)\*', r'<em>\1</em>', html_content)
+    
+    # Convert lists
+    html_content = re.sub(r'^- (.*?)$', r'<li>\1</li>', html_content, flags=re.MULTILINE)
+    html_content = re.sub(r'(<li>.*</li>)', r'<ul>\1</ul>', html_content, flags=re.DOTALL)
+    
+    # Convert line breaks
+    html_content = html_content.replace('\n', '<br>')
+    
+    return html_content
+
+
+def _generate_action_interface(action_fields: List[Dict[str, Any]], is_chat_env: bool) -> str:
+    """Generate either a chat interface or action form based on environment type."""
+    if is_chat_env:
+        return _generate_chat_interface()
+    else:
+        return _generate_action_form(action_fields)
+
+def _generate_chat_interface() -> str:
+    """Generate a chat-style interface for chat environments."""
+    return '''
+                <!-- Chat Interface -->
+                <div class="chat-interface">
+                    <h3>Chat Interface</h3>
+                    <div class="chat-messages" id="chat-messages">
+                        <div class="chat-message system">
+                            <div class="message-role">System</div>
+                            <div class="message-content">Chat environment ready. Send a message to start the conversation.</div>
+                        </div>
+                    </div>
+                    <div class="chat-input-container">
+                        <div class="role-selector">
+                            <label for="message-role">Role:</label>
+                            <select id="message-role">
+                                <option value="user">User</option>
+                                <option value="assistant">Assistant</option>
+                            </select>
+                        </div>
+                        <div class="message-input">
+                            <textarea id="message-input" placeholder="Type your message here..." rows="3"></textarea>
+                            <button class="btn" id="send-message-btn">Send Message</button>
+                        </div>
+                    </div>
+                </div>
+    '''
+
+def _generate_action_form(action_fields: List[Dict[str, Any]]) -> str:
+    """Generate a traditional action form for non-chat environments."""
+    return f'''
+                <!-- Action Form -->
+                <div class="action-form">
+                    <h3>Take Action</h3>
+                    <form id="action-form">
+                        {_generate_action_form_fields(action_fields)}
+                        <button type="submit" class="btn" id="step-btn">Step</button>
+                    </form>
+                </div>
+    '''
+
+def _generate_action_form_fields(action_fields: List[Dict[str, Any]]) -> str:
+    """Generate HTML form fields for action input with enhanced metadata."""
+    if not action_fields:
+        return '<p>No action fields available</p>'
+    
+    fields_html = []
+    for field in action_fields:
+        field_html = _generate_single_field(field)
+        fields_html.append(field_html)
+    
+    return '\n'.join(fields_html)
+
+
+def _generate_single_field(field: Dict[str, Any]) -> str:
+    """Generate HTML for a single form field with enhanced metadata."""
+    field_name = field['name']
+    field_type = field['type']
+    required = field['required']
+    placeholder = field.get('placeholder', '')
+    help_text = field.get('help_text', '')
+    choices = field.get('choices', [])
+    min_value = field.get('min_value')
+    max_value = field.get('max_value')
+    default_value = field.get('default_value')
+    
+    # Build label with required indicator
+    label_text = field_name.replace('_', ' ').title()
+    if required:
+        label_text += ' <span style="color: red;">*</span>'
+    
+    # Build input attributes
+    input_attrs = []
+    if required:
+        input_attrs.append('required')
+    if placeholder:
+        input_attrs.append(f'placeholder="{placeholder}"')
+    if min_value is not None:
+        input_attrs.append(f'min="{min_value}"')
+    if max_value is not None:
+        input_attrs.append(f'max="{max_value}"')
+    if default_value is not None:
+        input_attrs.append(f'value="{default_value}"')
+    
+    attrs_str = ' '.join(input_attrs)
+    
+    if field_type == 'checkbox':
+        return f'''
+            <div class="form-group">
+                <label>
+                    <input type="checkbox" name="{field_name}" value="true" {attrs_str}>
+                    {label_text}
+                </label>
+                {f'<small class="help-text">{help_text}</small>' if help_text else ''}
+            </div>
+        '''
+    
+    elif field_type == 'select':
+        options_html = []
+        if not required:
+            options_html.append(f'<option value="">-- Select {label_text} --</option>')
+        
+        for choice in choices:
+            selected = 'selected' if str(choice) == str(default_value) else ''
+            options_html.append(f'<option value="{choice}" {selected}>{choice}</option>')
+        
+        return f'''
+            <div class="form-group">
+                <label for="{field_name}">{label_text}:</label>
+                <select name="{field_name}" id="{field_name}" {attrs_str}>
+                    {''.join(options_html)}
+                </select>
+                {f'<small class="help-text">{help_text}</small>' if help_text else ''}
+            </div>
+        '''
+    
+    elif field_type == 'tensor':
+        return f'''
+            <div class="form-group">
+                <label for="{field_name}">{label_text} (comma-separated integers):</label>
+                <input type="text" name="{field_name}" id="{field_name}" {attrs_str}>
+                <small class="help-text">{help_text or 'Enter token IDs as comma-separated integers (e.g., 1,2,3,4,5)'}</small>
+            </div>
+        '''
+    
+    elif field_type == 'text' and ('message' in field_name.lower() or 'code' in field_name.lower()):
+        return f'''
+            <div class="form-group">
+                <label for="{field_name}">{label_text}:</label>
+                <textarea name="{field_name}" id="{field_name}" rows="3" {attrs_str}></textarea>
+                {f'<small class="help-text">{help_text}</small>' if help_text else ''}
+            </div>
+        '''
+    
+    else:
+        return f'''
+            <div class="form-group">
+                <label for="{field_name}">{label_text}:</label>
+                <input type="{field_type}" name="{field_name}" id="{field_name}" {attrs_str}>
+                {f'<small class="help-text">{help_text}</small>' if help_text else ''}
+            </div>
+        '''

src/core/http_env_client.py

@@ -0,0 +1,203 @@
+"""
+core/runner_env.py
+Minimal HTTP-based environment client.
+- Talks to a single env worker exposing: POST /reset, POST /step
+
+Future hooks (commented below) for:
+- episode_id, seed on reset
+- request_id on step
+- custom headers (auth/trace)
+"""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Generic, Optional, Type, TYPE_CHECKING, TypeVar
+
+import requests
+
+from .client_types import StepResult
+from .containers.runtime import LocalDockerProvider
+
+if TYPE_CHECKING:
+    from .containers.runtime import ContainerProvider
+
+ActT = TypeVar("ActT")
+ObsT = TypeVar("ObsT")
+EnvClientT = TypeVar("EnvClientT", bound="HTTPEnvClient")
+
+
+class HTTPEnvClient(ABC, Generic[ActT, ObsT]):
+    def __init__(
+        self,
+        base_url: str,
+        request_timeout_s: float = 15.0,
+        default_headers: Optional[Dict[str, str]] = None,
+        provider: Optional["ContainerProvider"] = None,
+    ):
+        self._base = base_url.rstrip("/")
+        self._timeout = float(request_timeout_s)
+        self._http = requests.Session()
+        self._headers = default_headers or {}
+        self._provider = provider
+
+    @classmethod
+    def from_docker_image(
+        cls: Type[EnvClientT],
+        image: str,
+        provider: Optional["ContainerProvider"] = None,
+        **kwargs: Any,
+    ) -> EnvClientT:
+        """
+        Create an environment client by spinning up a Docker container locally.
+
+        This is a development utility that:
+        1. Starts a Docker container from the specified image
+        2. Waits for the server to be ready
+        3. Creates and returns a client instance connected to the container
+
+        Note: The container lifecycle management is left to the user or higher-level
+        orchestration. The container will keep running until manually stopped.
+
+        Args:
+            image: Docker image name to run (e.g., "echo-env:latest")
+            provider: Container provider to use (defaults to LocalDockerProvider)
+            **kwargs: Additional arguments to pass to provider.start_container()
+                     (e.g., env_vars, port)
+
+        Returns:
+            An instance of the client class connected to the running container
+
+        Example:
+            >>> from envs.coding_env.client import CodingEnv
+            >>> from envs.coding_env.models import CodeAction
+            >>>
+            >>> # Create environment from image
+            >>> env = CodingEnv.from_docker_image("coding-env:latest")
+            >>>
+            >>> # Create environment with custom env vars
+            >>> env = CodingEnv.from_docker_image(
+            ...     "coding-env:latest",
+            ...     env_vars={"MY_VAR": "value"}
+            ... )
+            >>>
+            >>> # Use the environment
+            >>> result = env.reset()
+            >>> print(result.observation)
+            >>>
+            >>> step_result = env.step(CodeAction(code="print('hello')"))
+            >>> print(step_result.observation.stdout)
+            >>>
+            >>> # Cleanup (optional)
+            >>> env.close()
+        """
+
+        # Use default provider if none provided
+        if provider is None:
+            provider = LocalDockerProvider()
+
+        # 1. Start container with optional kwargs (e.g., env_vars, port)
+        base_url = provider.start_container(image, **kwargs)
+
+        # 2. Wait for server to be ready
+        provider.wait_for_ready(base_url)
+
+        # 3. Create and return client instance with provider reference
+        return cls(base_url=base_url, provider=provider)
+
+    @classmethod
+    def from_hub(cls: Type[EnvClientT], repo_id: str, provider: Optional["ContainerProvider"] = None, **kwargs: Any) -> EnvClientT:
+        """
+        Create an environment client by pulling from a Hugging Face model hub.
+        """
+        
+        if provider is None:
+            provider = LocalDockerProvider()
+        
+        if "tag" in kwargs:
+            tag = kwargs["tag"]
+        else:
+            tag = "latest"
+        
+        base_url = f"registry.hf.space/{repo_id.replace('/', '-')}:{tag}"
+        
+        return cls.from_docker_image(image=base_url, provider=provider)
+
+    @abstractmethod
+    def _step_payload(self, action: ActT) -> dict:
+        """Convert an Action object to the JSON body expected by the env server."""
+        raise NotImplementedError
+
+    @abstractmethod
+    def _parse_result(self, payload: dict) -> StepResult[ObsT]:
+        """Convert a JSON response from the env server to StepResult[ObsT]."""
+        raise NotImplementedError
+
+    @abstractmethod
+    def _parse_state(self, payload: dict) -> Any:
+        """Convert a JSON response from the state endpoint to a State object."""
+        raise NotImplementedError
+
+    # ---------- Environment Server Interface Methods ----------
+    def reset(self) -> StepResult[ObsT]:
+        body: Dict[str, Any] = {}
+        # TODO: later:
+        # body["seed"] = seed
+        # body["episode_id"] = episode_id
+        r = self._http.post(
+            f"{self._base}/reset",
+            json=body,
+            headers=self._headers,
+            timeout=self._timeout,
+        )
+        r.raise_for_status()
+        return self._parse_result(r.json())
+
+    def step(self, action: ActT) -> StepResult[ObsT]:
+        body: Dict[str, Any] = {
+            "action": self._step_payload(action),
+            "timeout_s": int(self._timeout),
+        }
+        # TODO: later:
+        # body["request_id"] = str(uuid.uuid4())
+        # body["episode_id"] = current_episode_id
+        r = self._http.post(
+            f"{self._base}/step",
+            json=body,
+            headers=self._headers,
+            timeout=self._timeout,
+        )
+        r.raise_for_status()
+        return self._parse_result(r.json())
+
+    def state(self) -> Any:
+        """
+        Get the current environment state from the server.
+
+        Returns:
+            State object with environment state information (e.g., episode_id, step_count)
+
+        Example:
+            >>> client = EchoEnv.from_docker_image("echo-env:latest")
+            >>> result = client.reset()
+            >>> state = client.state()
+            >>> print(state.episode_id)
+            >>> print(state.step_count)
+        """
+        r = self._http.get(
+            f"{self._base}/state",
+            headers=self._headers,
+            timeout=self._timeout,
+        )
+        r.raise_for_status()
+        return self._parse_state(r.json())
+
+    def close(self) -> None:
+        """
+        Close the environment and clean up resources.
+
+        If this client was created via from_docker_image(), this will stop
+        and remove the associated container.
+        """
+        if self._provider is not None:
+            self._provider.stop_container()

src/core/pyproject.toml

@@ -0,0 +1,46 @@
+[build-system]
+requires = ["setuptools>=45", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "openenv-core"
+version = "0.1.0"
+description = "Core components for OpenEnv - HTTP-based agentic environments"
+readme = "README.md"
+requires-python = ">=3.8"
+license = {text = "BSD-3-Clause"}
+authors = [
+    {name = "Meta Platforms, Inc.", email = "opensource@meta.com"}
+]
+keywords = ["environment", "agent", "http", "docker", "fastapi"]
+
+dependencies = [
+    "requests>=2.25.0",
+    "fastapi>=0.104.0",
+    "uvicorn>=0.24.0",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=7.0.0",
+    "black>=23.0.0",
+    "ruff>=0.1.0",
+    "mypy>=1.0.0",
+]
+
+[project.urls]
+Homepage = "https://github.com/facebookresearch/OpenEnv"
+Repository = "https://github.com/facebookresearch/OpenEnv"
+Documentation = "https://github.com/facebookresearch/OpenEnv/blob/main/README.md"
+"Bug Tracker" = "https://github.com/facebookresearch/OpenEnv/issues"
+
+[tool.setuptools]
+py-modules = ["openenv_core.__init__", "openenv_core.http_env_client", "openenv_core.client_types"]
+packages = [
+    "openenv_core",
+    "openenv_core.containers",
+    "openenv_core.containers.runtime",
+    "openenv_core.env_server",
+    "openenv_core.tools"
+]
+package-dir = {"openenv_core" = "."}

src/core/tools/__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.
+
+"""Core tools for code execution and other utilities."""
+
+from .git_server_client import GitServerClient, RepoInfo
+from .local_python_executor import PyExecutor
+
+__all__ = [
+    "PyExecutor",
+    "GitServerClient",
+    "RepoInfo",
+]

src/core/tools/git_server_client.py

@@ -0,0 +1,362 @@
+#!/usr/bin/env python3
+"""
+Git Server Client for connecting to external Gitea instance.
+
+This module provides a lightweight client for interacting with a shared
+Gitea service, optimized for task-based isolation where multiple environment
+instances share the same Gitea server but have isolated workspaces.
+"""
+
+import json
+import os
+import shutil
+import subprocess
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from urllib.parse import urlparse
+
+
+@dataclass
+class RepoInfo:
+    """Information about a repository."""
+
+    name: str
+    url: str
+    commit: str
+    clone_url: str
+
+
+class GitServerClient:
+    """
+    Client for connecting to an external Gitea server.
+
+    This client is optimized for task-based isolation where:
+    - Multiple tasks share the same Gitea instance
+    - Each task has its own isolated workspace
+    - Fast reset() via git operations (no server restart)
+    - Repos are pre-migrated to Gitea once
+
+    Args:
+        gitea_url: URL of the Gitea server (e.g., "http://gitea:3000")
+        username: Gitea username for authentication
+        password: Gitea password for authentication
+        workspace_dir: Local workspace directory for cloning repos
+
+    Example:
+        >>> # Connect to shared Gitea (credentials from environment)
+        >>> import os
+        >>> client = GitServerClient(
+        ...     gitea_url=os.getenv("GITEA_URL"),
+        ...     username=os.getenv("GITEA_USERNAME"),
+        ...     password=os.getenv("GITEA_PASSWORD")
+        ... )
+        >>> client.wait_for_ready()
+        >>> # Clone repo to workspace
+        >>> path = client.clone_to_workspace("my-repo", commit="abc123")
+        >>> # Fast reset to base state
+        >>> client.reset_workspace("my-repo", commit="abc123")
+    """
+
+    def __init__(
+        self,
+        gitea_url: str,
+        username: str,
+        password: str,
+        workspace_dir: str = "/workspace",
+    ):
+        """Initialize Git Server Client."""
+        self.gitea_url = gitea_url.rstrip("/")
+        self.username = username
+        self.password = password
+        self.workspace_dir = Path(workspace_dir)
+        self.is_ready = False
+
+        # Parse Gitea URL
+        parsed = urlparse(self.gitea_url)
+        self.domain = parsed.hostname or "localhost"
+        self.port = parsed.port or 3000
+
+        # Ensure workspace exists
+        os.makedirs(self.workspace_dir, exist_ok=True)
+
+        # Configure git credentials
+        self._configure_git()
+
+    def _configure_git(self):
+        """Configure git credentials for automatic authentication."""
+        home_dir = Path.home()
+
+        # Git config
+        git_config = f"""[user]
+    name = {self.username}
+    email = {self.username}@local.env
+[init]
+    defaultBranch = main
+[credential]
+    helper = store
+"""
+        gitconfig_path = home_dir / ".gitconfig"
+        gitconfig_path.write_text(git_config)
+
+        # Git credentials
+        git_credentials = f"http://{self.username}:{self.password}@{self.domain}:{self.port}\n"
+        gitcreds_path = home_dir / ".git-credentials"
+        gitcreds_path.write_text(git_credentials)
+        gitcreds_path.chmod(0o600)
+
+    def wait_for_ready(self, timeout: int = 30) -> bool:
+        """
+        Wait for Gitea server to be ready.
+
+        Args:
+            timeout: Maximum seconds to wait
+
+        Returns:
+            True if server is ready, False otherwise
+        """
+        start_time = time.time()
+        while time.time() - start_time < timeout:
+            try:
+                result = subprocess.run(
+                    ["curl", "-sf", f"{self.gitea_url}/"],
+                    capture_output=True,
+                    timeout=5,
+                )
+                if result.returncode == 0:
+                    self.is_ready = True
+                    return True
+            except subprocess.TimeoutExpired:
+                pass
+            except Exception:
+                pass
+
+            time.sleep(1)
+
+        return False
+
+    def list_repositories(self) -> list[dict[str, str]]:
+        """
+        List all repositories in Gitea.
+
+        Returns:
+            List of repository information dictionaries
+        """
+        if not self.is_ready:
+            raise RuntimeError("Gitea server is not ready")
+
+        result = subprocess.run(
+            [
+                "curl",
+                "-s",
+                f"{self.gitea_url}/api/v1/user/repos",
+                "-u",
+                f"{self.username}:{self.password}",
+            ],
+            capture_output=True,
+            text=True,
+        )
+
+        if result.returncode != 0:
+            return []
+
+        try:
+            repos = json.loads(result.stdout)
+            return [
+                {
+                    "name": repo["name"],
+                    "full_name": repo["full_name"],
+                    "clone_url": repo["clone_url"],
+                    "description": repo.get("description", ""),
+                }
+                for repo in repos
+            ]
+        except (json.JSONDecodeError, KeyError):
+            return []
+
+    def clone_to_workspace(
+        self, repo_name: str, target_dir: str | None = None, commit: str = "main"
+    ) -> str:
+        """
+        Clone a repository to the workspace at a specific commit.
+
+        This creates a fresh clone optimized for task isolation.
+
+        Args:
+            repo_name: Name of repository to clone
+            target_dir: Target directory name (defaults to repo_name)
+            commit: Commit hash or branch to check out
+
+        Returns:
+            Path to cloned repository
+
+        Raises:
+            RuntimeError: If clone fails
+        """
+        if not self.is_ready:
+            raise RuntimeError("Gitea server is not ready")
+
+        target_dir = target_dir or repo_name
+        target_path = self.workspace_dir / target_dir
+
+        # Remove existing directory if present
+        if target_path.exists():
+            shutil.rmtree(target_path)
+
+        clone_url = f"{self.gitea_url}/{self.username}/{repo_name}.git"
+
+        # Clone repository
+        result = subprocess.run(
+            ["git", "clone", clone_url, str(target_path)],
+            capture_output=True,
+            text=True,
+        )
+
+        if result.returncode != 0:
+            raise RuntimeError(f"Clone failed: {result.stderr}")
+
+        # Checkout specific commit
+        if commit != "main":
+            result = subprocess.run(
+                ["git", "checkout", commit],
+                cwd=str(target_path),
+                capture_output=True,
+                text=True,
+            )
+
+            if result.returncode != 0:
+                raise RuntimeError(f"Checkout failed: {result.stderr}")
+
+        return str(target_path)
+
+    def reset_workspace(self, repo_name: str, commit: str = "main") -> bool:
+        """
+        Fast reset of workspace to base state (optimized for task resets).
+
+        This is much faster than re-cloning. It:
+        1. Checks out the target commit
+        2. Resets to that commit (hard)
+        3. Cleans untracked files
+
+        Args:
+            repo_name: Name of repository (directory in workspace)
+            commit: Commit hash or branch to reset to
+
+        Returns:
+            True if reset successful
+
+        Raises:
+            RuntimeError: If reset fails
+        """
+        repo_path = self.workspace_dir / repo_name
+
+        if not repo_path.exists():
+            raise RuntimeError(f"Repository not found in workspace: {repo_name}")
+
+        # Fetch latest (in case commit is new)
+        subprocess.run(
+            ["git", "fetch", "--all"],
+            cwd=str(repo_path),
+            capture_output=True,
+        )
+
+        # Checkout and hard reset to commit
+        result = subprocess.run(
+            ["git", "checkout", commit],
+            cwd=str(repo_path),
+            capture_output=True,
+            text=True,
+        )
+
+        if result.returncode != 0:
+            raise RuntimeError(f"Checkout failed: {result.stderr}")
+
+        result = subprocess.run(
+            ["git", "reset", "--hard", f"origin/{commit}" if commit != "main" else commit],
+            cwd=str(repo_path),
+            capture_output=True,
+            text=True,
+        )
+
+        if result.returncode != 0:
+            # Try without origin/ prefix
+            result = subprocess.run(
+                ["git", "reset", "--hard", commit],
+                cwd=str(repo_path),
+                capture_output=True,
+                text=True,
+            )
+            if result.returncode != 0:
+                raise RuntimeError(f"Reset failed: {result.stderr}")
+
+        # Clean untracked files and directories
+        subprocess.run(
+            ["git", "clean", "-fdx"],
+            cwd=str(repo_path),
+            capture_output=True,
+        )
+
+        return True
+
+    def execute_git_command(
+        self, command: str, working_dir: str = ""
+    ) -> tuple[int, str, str]:
+        """
+        Execute a git command in the workspace.
+
+        Args:
+            command: Git command to execute (without 'git' prefix)
+            working_dir: Working directory relative to workspace
+
+        Returns:
+            Tuple of (exit_code, stdout, stderr)
+        """
+        work_path = (
+            self.workspace_dir / working_dir if working_dir else self.workspace_dir
+        )
+
+        if not work_path.exists():
+            return (1, "", f"Working directory does not exist: {work_path}")
+
+        # Split command safely
+        cmd_parts = ["git"] + command.split()
+
+        result = subprocess.run(
+            cmd_parts,
+            cwd=str(work_path),
+            capture_output=True,
+            text=True,
+        )
+
+        return (result.returncode, result.stdout, result.stderr)
+
+    def get_current_commit(self, repo_name: str) -> str:
+        """
+        Get current commit hash of a workspace repository.
+
+        Args:
+            repo_name: Name of repository in workspace
+
+        Returns:
+            Commit hash
+        """
+        repo_path = self.workspace_dir / repo_name
+
+        if not repo_path.exists():
+            raise RuntimeError(f"Repository not found: {repo_name}")
+
+        result = subprocess.run(
+            ["git", "rev-parse", "HEAD"],
+            cwd=str(repo_path),
+            capture_output=True,
+            text=True,
+        )
+
+        if result.returncode != 0:
+            raise RuntimeError(f"Failed to get commit: {result.stderr}")
+
+        return result.stdout.strip()
+
+    def workspace_exists(self, repo_name: str) -> bool:
+        """Check if a repository exists in workspace."""
+        return (self.workspace_dir / repo_name).exists()

src/core/tools/local_python_executor.py

@@ -0,0 +1,105 @@
+# 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.
+
+"""
+Local Python Executor.
+
+This module provides functionality for executing Python code locally by wrapping
+the smolagents LocalPythonExecutor.
+"""
+
+from smolagents import LocalPythonExecutor
+
+from core.env_server.types import CodeExecResult
+
+
+class PyExecutor:
+    """
+    Wrapper around smolagents LocalPythonExecutor for executing Python code.
+
+    This class provides a simple interface to execute Python code in a subprocess
+    and capture the results including stdout, stderr, and exit code.
+
+    Args:
+        additional_imports: List of additional module imports to authorize.
+                          For example: ["numpy", "pandas", "matplotlib"]
+                          These will be added to the base authorized imports.
+
+    Example:
+        >>> # Basic usage with default imports
+        >>> executor = PyExecutor()
+        >>> result = executor.run("print('Hello, World!')")
+        >>> print(result.stdout)  # "Hello, World!\n"
+        >>> print(result.exit_code)  # 0
+        >>>
+        >>> # Usage with additional imports
+        >>> executor = PyExecutor(additional_imports=["numpy", "pandas"])
+        >>> result = executor.run("import numpy as np\\nprint(np.array([1, 2, 3]))")
+        >>> print(result.stdout)  # "[1 2 3]\n"
+    """
+
+    def __init__(self, additional_imports: list[str] | None = None):
+        """
+        Initialize the PyExecutor with a LocalPythonExecutor instance.
+
+        Args:
+            additional_imports: List of additional module names to authorize for import.
+                              Defaults to an empty list if not provided.
+        """
+        if additional_imports is None:
+            additional_imports = []
+        self._executor = LocalPythonExecutor(
+            additional_authorized_imports=additional_imports
+        )
+        # Initialize tools to make BASE_PYTHON_TOOLS available (including print)
+        self._executor.send_tools({})
+
+    def run(self, code: str) -> CodeExecResult:
+        """
+        Execute Python code and return the result.
+
+        Args:
+            code: Python code string to execute
+
+        Returns:
+            CodeExecResult containing stdout, stderr, and exit_code
+
+        Example:
+            >>> executor = PyExecutor()
+            >>> result = executor.run("x = 5 + 3\\nprint(x)")
+            >>> print(result.stdout)  # "8\n"
+            >>> print(result.exit_code)  # 0
+            >>>
+            >>> # Error handling
+            >>> result = executor.run("1 / 0")
+            >>> print(result.exit_code)  # 1
+            >>> print(result.stderr)  # Contains error message
+        """
+        try:
+            # Execute the code using LocalPythonExecutor
+            # LocalPythonExecutor returns a CodeOutput object with output, logs, is_final_answer
+            exec_result = self._executor(code)
+
+            # Extract the logs (which contain print outputs) as stdout
+            # The output field contains the return value of the code
+            stdout = exec_result.logs
+            stderr = ""
+            exit_code = 0  # Success
+
+            return CodeExecResult(
+                stdout=stdout,
+                stderr=stderr,
+                exit_code=exit_code,
+            )
+
+        except Exception as e:
+            # LocalPythonExecutor raises InterpreterError for various issues
+            # (syntax errors, forbidden operations, runtime errors, etc.)
+            return CodeExecResult(
+                stdout="",
+                stderr=str(e),
+                exit_code=1,  # Non-zero indicates error
+            )

src/envs/nle_env/README.md

@@ -0,0 +1,316 @@
+# NetHack Learning Environment (NLE) for OpenEnv
+
+A reinforcement learning environment based on NetHack 3.6.6, wrapped for the OpenEnv framework.
+
+## Overview
+
+NetHack is one of the oldest and most challenging roguelike games, featuring:
+- **Procedurally generated dungeons** - Every episode is unique
+- **Complex action space** - 113+ discrete actions (movement, combat, magic, inventory management)
+- **Rich observation space** - 14+ observation types including dungeon map, stats, inventory, messages
+- **Challenging gameplay** - One of the hardest RL benchmarks available
+- **Deterministic (with seeding)** - Reproducible episodes for evaluation
+
+This environment wraps the [NetHack Learning Environment (NLE)](https://github.com/facebookresearch/nle) project, which provides a Gym interface to NetHack.
+
+## Quick Start
+
+### Using Docker (Recommended)
+
+```python
+from envs.nle_env import NLEEnv, NLEAction
+
+# Automatically start container and connect
+env = NLEEnv.from_docker_image("nle-env:latest")
+
+# Reset to start a new game
+result = env.reset()
+print(f"Episode started: {result.observation.message}")
+
+# Take actions in the game
+for step in range(100):
+    # Action IDs: 0-112 (movement, commands, etc.)
+    action = NLEAction(action_id=0)  # Move north
+    result = env.step(action)
+
+    print(f"Step {step}: Reward={result.reward}, Done={result.done}")
+
+    if result.done:
+        print("Episode ended!")
+        break
+
+env.close()
+```
+
+### Building the Docker Image
+
+```bash
+# Build from repository root (not from server directory)
+cd /Users/sanyambhutani/GH/OpenEnv
+docker build -f src/envs/nle_env/server/Dockerfile -t nle-env:latest .
+```
+
+**Note:** Building NLE from source can take 5-10 minutes as it compiles NetHack C code.
+
+### Running the Server Locally
+
+```bash
+# Install NLE (requires cmake, build-essential)
+pip install nle gym
+
+# Run the server
+python -m envs.nle_env.server.app
+
+# Server will be available at http://localhost:8000
+```
+
+## Action Space
+
+NLE uses a discrete action space with 113 actions:
+
+| Action ID Range | Category | Examples |
+|----------------|----------|----------|
+| 0-7 | Cardinal movement | North, South, East, West |
+| 8-15 | Diagonal movement | NE, SE, SW, NW |
+| 16-20 | Stair navigation | Up, Down |
+| 21-112 | Commands | Eat, Search, Apply, Quaff, Read, etc. |
+
+Common actions:
+```python
+# Movement
+NLEAction(action_id=0)   # Move north (k)
+NLEAction(action_id=1)   # Move east (l)
+NLEAction(action_id=2)   # Move south (j)
+NLEAction(action_id=3)   # Move west (h)
+
+# Interactions
+NLEAction(action_id=37)  # Eat (e)
+NLEAction(action_id=50)  # Search (s)
+NLEAction(action_id=104) # Inventory (i)
+NLEAction(action_id=86)  # Wait (.)
+```
+
+For a complete action mapping, see [NLE Actions Documentation](https://github.com/facebookresearch/nle/blob/main/nle/nethack/actions.py).
+
+## Observation Space
+
+NLE provides rich observations about the game state. With OpenEnv's beefy compute assumption, all observations are included by default:
+
+### Core Observations
+- **glyphs** `(21, 79)`: Symbolic dungeon map representation
+- **blstats** `(26,)`: Bottom-line stats (HP, MaxHP, XP, Gold, etc.)
+- **message** `(256,)`: Latest game message as byte array
+
+### Visual Observations
+- **chars** `(21, 79)`: ASCII character display
+- **colors** `(21, 79)`: Color codes for display
+- **specials** `(21, 79)`: Special attributes (bold, inverse, etc.)
+
+### Inventory Observations
+- **inv_glyphs** `(55,)`: Inventory item glyphs
+- **inv_strs** `(55, 80)`: Inventory item descriptions
+- **inv_letters** `(55,)`: Inventory item letters (a-z, A-Z)
+- **inv_oclasses** `(55,)`: Inventory object classes
+
+### Terminal Observations (for rendering)
+- **tty_chars** `(24, 80)`: Full terminal character display
+- **tty_colors** `(24, 80)`: Full terminal colors
+- **tty_cursor** `(2,)`: Terminal cursor position [row, col]
+
+### Extended Observations
+- **screen_descriptions** `(21, 79, 80)`: Text descriptions of dungeon cells
+- **program_state** `(6,)`: Internal program state
+- **internal** `(9,)`: Internal game state
+- **misc** `(4,)`: Miscellaneous info
+
+All observations are serialized as nested lists (converted from numpy arrays) for JSON compatibility.
+
+## Reward Structure
+
+By default, NLE uses **score delta** as the reward:
+```
+reward = current_score - previous_score
+```
+
+Score increases by:
+- Defeating monsters
+- Collecting gold
+- Advancing to deeper dungeon levels
+- Finding items
+- Gaining experience points
+
+## Episode Termination
+
+Episodes end when:
+1. **Death** - Character dies (most common)
+2. **Ascension** - Player completes the game (very rare!)
+3. **Aborted** - Max episode steps reached (default: 5000)
+4. **Task Successful** - For task-specific environments
+
+Check the end status:
+```python
+result = env.step(action)
+if result.done:
+    state = env.state()
+    print(f"End status: {state.end_status}")
+    # Possible values: RUNNING, DEATH, TASK_SUCCESSFUL, ABORTED
+```
+
+## Configuration
+
+Configure the environment via environment variables or Docker args:
+
+```bash
+# Task variant (default: score)
+export NLE_TASK=score
+
+# Character (role-race-gender-alignment)
+export NLE_CHARACTER=mon-hum-neu-mal
+
+# Max episode steps (default: 5000)
+export NLE_MAX_STEPS=10000
+```
+
+### Character Options
+
+Format: `role-race-gender-alignment`
+
+**Roles:** Archaeologist (arc), Barbarian (bar), Caveman (cav), Healer (hea), Knight (kni), Monk (mon), Priest (pri), Ranger (ran), Rogue (rog), Samurai (sam), Tourist (tou), Valkyrie (val), Wizard (wiz)
+
+**Races:** Human (hum), Dwarf (dwa), Elf (elf), Gnome (gno), Orc (orc)
+
+**Genders:** Male (mal), Female (fem)
+
+**Alignments:** Lawful (law), Neutral (neu), Chaotic (cha)
+
+Example: `wiz-elf-fem-cha` = Female Elven Chaotic Wizard
+
+## Example: Random Agent
+
+```python
+import random
+from envs.nle_env import NLEEnv, NLEAction
+
+env = NLEEnv.from_docker_image("nle-env:latest")
+
+episodes = 10
+for episode in range(episodes):
+    result = env.reset()
+    total_reward = 0
+
+    while True:
+        # Random action
+        action = NLEAction(action_id=random.randint(0, 112))
+        result = env.step(action)
+
+        total_reward += result.reward or 0
+
+        if result.done:
+            state = env.state()
+            print(f"Episode {episode}: Reward={total_reward:.1f}, "
+                  f"Steps={state.step_count}, Status={state.end_status}")
+            break
+
+env.close()
+```
+
+## Example: Rendering Game State
+
+```python
+import numpy as np
+from envs.nle_env import NLEEnv, NLEAction
+
+env = NLEEnv.from_docker_image("nle-env:latest")
+result = env.reset()
+
+# Get terminal display
+tty_chars = np.array(result.observation.tty_chars)
+tty_colors = np.array(result.observation.tty_colors)
+
+# Print ASCII display
+for row in tty_chars:
+    print(''.join(chr(c) for c in row))
+
+# Get game message
+message = bytes(result.observation.message)
+print(f"Message: {message[:message.index(b'\\0')].decode('ascii')}")
+
+# Get stats
+blstats = result.observation.blstats
+print(f"HP: {blstats[10]}/{blstats[11]}, Gold: {blstats[13]}, "
+      f"XP Level: {blstats[18]}")
+
+env.close()
+```
+
+## Performance Considerations
+
+With **beefy compute** (64+ cores, 256GB+ RAM, 10Gbps network):
+- Observation size: ~140KB per step (all observation types)
+- Network overhead: Negligible (<1ms on fast network)
+- Memory: ~200-500MB per container
+- Throughput: 100+ parallel environments easily
+
+**Optimizations are NOT needed** - just run it simple with JSON serialization!
+
+## Task Variants (Future)
+
+Current implementation: **NetHackScore** (maximize game score)
+
+Planned task variants:
+- **NetHackStaircase** - Reach the stairs down
+- **NetHackOracle** - Find the Oracle
+- **NetHackGold** - Collect gold
+- **NetHackEat** - Maximize hunger satisfaction
+- **NetHackScout** - Maximize exploration
+
+## Troubleshooting
+
+### Build Issues
+
+If Docker build fails with cmake errors:
+```bash
+# Ensure cmake is recent enough (3.15+)
+cmake --version
+```
+
+### Container Won't Start
+
+Check logs:
+```bash
+docker logs <container-id>
+```
+
+Common issues:
+- NLE compilation failed → Check cmake, build-essential installed
+- Import errors → Check PYTHONPATH set correctly
+- Port already in use → Use different port mapping
+
+### Slow Performance
+
+If you experience slowness even with beefy compute:
+1. Check network latency: `ping <server-ip>`
+2. Monitor CPU: NLE is CPU-intensive for dungeon generation
+3. Check Docker resources: Ensure containers have sufficient CPU allocation
+
+## References
+
+- [NLE GitHub](https://github.com/facebookresearch/nle)
+- [NLE Paper (NeurIPS 2020)](https://arxiv.org/abs/2006.13760)
+- [NetHack Wiki](https://nethackwiki.com)
+- [NetHack Official Site](https://nethack.org)
+
+## Citation
+
+If you use NLE in your research, please cite:
+
+```bibtex
+@inproceedings{kuettler2020nethack,
+  title={The NetHack Learning Environment},
+  author={K{\"u}ttler, Heinrich and Nardelli, Nantas and Miller, Alexander H and
+          Raileanu, Roberta and Selvatici, Marco and Grefenstette, Edward and
+          Rockt{\"a}schel, Tim},
+  booktitle={Proceedings of NeurIPS},
+  year={2020}
+}
+```

src/envs/nle_env/__init__.py

@@ -0,0 +1,12 @@
+# 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.
+
+"""NetHack Learning Environment - OpenEnv integration."""
+
+from .client import NLEEnv
+from .models import NLEAction, NLEObservation, NLEState
+
+__all__ = ["NLEAction", "NLEObservation", "NLEState", "NLEEnv"]

src/envs/nle_env/client.py

@@ -0,0 +1,147 @@
+# 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.
+
+"""
+NetHack Learning Environment HTTP Client.
+
+This module provides the client for connecting to an NLE Environment server
+over HTTP.
+"""
+
+from typing import Dict
+
+from core.client_types import StepResult
+from core.http_env_client import HTTPEnvClient
+
+from .models import NLEAction, NLEObservation, NLEState
+
+
+class NLEEnv(HTTPEnvClient[NLEAction, NLEObservation]):
+    """
+    HTTP client for the NetHack Learning Environment.
+
+    This client connects to an NLEEnvironment HTTP server and provides
+    methods to interact with NetHack: reset(), step(), and state access.
+
+    With beefy compute, we use simple JSON serialization. The server sends
+    all observation arrays as nested lists, which we keep as-is or convert
+    back to numpy arrays as needed.
+
+    Example:
+        >>> # Connect to a running server
+        >>> client = NLEEnv(base_url="http://localhost:8000")
+        >>> result = client.reset()
+        >>> print(result.observation.blstats)  # [HP, MaxHP, ...]
+        >>>
+        >>> # Take a step (move north)
+        >>> result = client.step(NLEAction(action_id=0))
+        >>> print(result.reward)
+        >>> print(result.done)
+
+    Example with Docker:
+        >>> # Automatically start container and connect
+        >>> client = NLEEnv.from_docker_image("nle-env:latest")
+        >>> result = client.reset()
+        >>>
+        >>> # Play NetHack!
+        >>> for _ in range(100):
+        ...     action = NLEAction(action_id=random.randint(0, 112))
+        ...     result = client.step(action)
+        ...     if result.done:
+        ...         break
+    """
+
+    def _step_payload(self, action: NLEAction) -> Dict:
+        """
+        Convert NLEAction to JSON payload for step request.
+
+        Args:
+            action: NLEAction instance with action_id
+
+        Returns:
+            Dictionary representation suitable for JSON encoding
+        """
+        return {
+            "action_id": action.action_id,
+        }
+
+    def _parse_result(self, payload: Dict) -> StepResult[NLEObservation]:
+        """
+        Parse server response into StepResult[NLEObservation].
+
+        The server sends all arrays as nested lists. With beefy compute,
+        we just keep them as lists - no need to convert back to numpy
+        unless the user specifically needs it.
+
+        Args:
+            payload: JSON response from server
+
+        Returns:
+            StepResult with NLEObservation
+        """
+        obs_data = payload.get("observation", {})
+
+        # Extract standard fields
+        done = obs_data.get("done", False)
+        reward = obs_data.get("reward")
+        metadata = obs_data.get("metadata", {})
+
+        # Build observation with all the array fields
+        # Keep them as lists - simple and works great with beefy compute
+        observation = NLEObservation(
+            # Core observations
+            glyphs=obs_data.get("glyphs"),
+            blstats=obs_data.get("blstats"),
+            message=obs_data.get("message"),
+            # Visual observations
+            chars=obs_data.get("chars"),
+            colors=obs_data.get("colors"),
+            specials=obs_data.get("specials"),
+            # Inventory observations
+            inv_glyphs=obs_data.get("inv_glyphs"),
+            inv_strs=obs_data.get("inv_strs"),
+            inv_letters=obs_data.get("inv_letters"),
+            inv_oclasses=obs_data.get("inv_oclasses"),
+            # Terminal observations
+            tty_chars=obs_data.get("tty_chars"),
+            tty_colors=obs_data.get("tty_colors"),
+            tty_cursor=obs_data.get("tty_cursor"),
+            # Extended observations
+            screen_descriptions=obs_data.get("screen_descriptions"),
+            program_state=obs_data.get("program_state"),
+            internal=obs_data.get("internal"),
+            misc=obs_data.get("misc"),
+            # Standard fields
+            done=done,
+            reward=reward,
+            metadata=metadata,
+        )
+
+        return StepResult(
+            observation=observation,
+            reward=reward,
+            done=done,
+        )
+
+    def _parse_state(self, payload: Dict) -> NLEState:
+        """
+        Parse server response into NLEState object.
+
+        Args:
+            payload: JSON response from /state endpoint
+
+        Returns:
+            NLEState object with episode and game information
+        """
+        return NLEState(
+            episode_id=payload.get("episode_id"),
+            step_count=payload.get("step_count", 0),
+            game_over=payload.get("game_over", False),
+            end_status=payload.get("end_status", "RUNNING"),
+            in_normal_game=payload.get("in_normal_game", False),
+            character=payload.get("character", "mon-hum-neu-mal"),
+            task_name=payload.get("task_name", "NetHackScore-v0"),
+        )

src/envs/nle_env/models.py

@@ -0,0 +1,110 @@
+# 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 NetHack Learning Environment (NLE).
+
+The NLE environment wraps the NetHack 3.6.6 game as a reinforcement learning
+environment, providing rich observations and a complex action space.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional
+
+from core.env_server import Action, Observation, State
+
+
+@dataclass
+class NLEAction(Action):
+    """
+    Action for the NetHack Learning Environment.
+
+    Uses discrete action space where action_id maps to NetHack commands
+    (movement, interactions, etc.). The action space has ~113 actions.
+
+    Examples:
+        - action_id=0: Move North (k)
+        - action_id=1: Move East (l)
+        - action_id=37: Eat (e)
+        - action_id=50: Search (s)
+    """
+
+    action_id: int  # Index into nethack.USEFUL_ACTIONS (0-112)
+
+
+@dataclass
+class NLEObservation(Observation):
+    """
+    Observation from the NetHack Learning Environment.
+
+    Contains a subset of NLE's 14+ observation types. All numpy arrays are
+    serialized as nested lists for JSON compatibility.
+
+    Observation types (all optional, configured at env creation):
+        - glyphs: (21, 79) - Symbolic dungeon map representation
+        - chars: (21, 79) - ASCII character display
+        - colors: (21, 79) - Color codes for display
+        - specials: (21, 79) - Special attributes
+        - blstats: (26,) - Bottom-line stats (HP, XP, gold, etc.)
+        - message: (256,) - Game message as byte array
+        - inv_glyphs: (55,) - Inventory item glyphs
+        - inv_strs: (55, 80) - Inventory item descriptions
+        - inv_letters: (55,) - Inventory item letters (a-z, A-Z)
+        - inv_oclasses: (55,) - Inventory object classes
+        - tty_chars: (24, 80) - Full terminal character display
+        - tty_colors: (24, 80) - Full terminal colors
+        - tty_cursor: (2,) - Terminal cursor position [row, col]
+        - screen_descriptions: (21, 79, 80) - Text descriptions of dungeon
+
+    With beefy compute, we include all observations by default.
+    """
+
+    # Core observations (always useful)
+    glyphs: Optional[List[List[int]]] = None
+    blstats: Optional[List[int]] = None
+    message: Optional[List[int]] = None
+
+    # Visual observations
+    chars: Optional[List[List[int]]] = None
+    colors: Optional[List[List[int]]] = None
+    specials: Optional[List[List[int]]] = None
+
+    # Inventory observations
+    inv_glyphs: Optional[List[int]] = None
+    inv_strs: Optional[List[List[int]]] = None
+    inv_letters: Optional[List[int]] = None
+    inv_oclasses: Optional[List[int]] = None
+
+    # Terminal observations (for rendering)
+    tty_chars: Optional[List[List[int]]] = None
+    tty_colors: Optional[List[List[int]]] = None
+    tty_cursor: Optional[List[int]] = None
+
+    # Extended observations
+    screen_descriptions: Optional[List[List[List[int]]]] = None
+    program_state: Optional[List[int]] = None
+    internal: Optional[List[int]] = None
+    misc: Optional[List[int]] = None
+
+
+@dataclass
+class NLEState(State):
+    """
+    Extended state for the NLE environment.
+
+    Includes NetHack-specific state information beyond basic episode tracking.
+    """
+
+    # NLE-specific state
+    game_over: bool = False
+    end_status: str = "RUNNING"  # RUNNING, DEATH, TASK_SUCCESSFUL, ABORTED
+    in_normal_game: bool = False
+    character: str = "mon-hum-neu-mal"  # role-race-gender-alignment
+
+    # Task-specific info
+    task_name: str = "NetHackScore-v0"

src/envs/nle_env/server/Dockerfile

@@ -0,0 +1,60 @@
+# 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.
+
+# NLE requires build dependencies, so we start from a base image with build tools
+# Using Python 3.11 for kw_only dataclass support (required by OpenEnv core)
+FROM python:3.11-slim
+
+# Install system dependencies needed for NLE
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    cmake \
+    git \
+    libbz2-dev \
+    flex \
+    bison \
+    libncurses5-dev \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Install Python dependencies
+# NLE requires cmake to be available during installation
+RUN pip install --no-cache-dir \
+    fastapi \
+    uvicorn \
+    requests \
+    pydantic \
+    numpy
+
+# Install NLE (this will compile NetHack from source)
+# Using the stable version from PyPI
+RUN pip install --no-cache-dir nle gym
+
+# Copy OpenEnv core
+COPY src/core/ /app/src/core/
+
+# Copy NLE environment implementation
+COPY src/envs/nle_env/ /app/src/envs/nle_env/
+
+# Copy README for web interface documentation
+COPY src/envs/nle_env/README.md /app/README.md
+
+# Set PYTHONPATH so imports work
+ENV PYTHONPATH=/app/src
+
+# Expose port
+EXPOSE 8000
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
+    CMD curl -f http://localhost:8000/health || exit 1
+
+# Run the FastAPI server
+# Note: workers=1 because NLE uses C extension with global state
+CMD ["uvicorn", "envs.nle_env.server.app:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"]

src/envs/nle_env/server/__init__.py

@@ -0,0 +1,7 @@
+# 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.
+
+"""Server module for NLE environment."""

src/envs/nle_env/server/app.py

@@ -0,0 +1,54 @@
+# 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 NetHack Learning Environment.
+
+This module creates an HTTP server that exposes the NLE environment
+over HTTP endpoints, making it compatible with HTTPEnvClient.
+
+Usage:
+    # Development (with auto-reload):
+    uvicorn envs.nle_env.server.app:app --reload --host 0.0.0.0 --port 8000
+
+    # Production:
+    uvicorn envs.nle_env.server.app:app --host 0.0.0.0 --port 8000 --workers 1
+
+    # Or run directly:
+    python -m envs.nle_env.server.app
+
+Note:
+    NLE is single-threaded (uses C extension with global state), so workers=1
+"""
+
+import os
+
+from core.env_server.http_server import create_app
+
+from ..models import NLEAction, NLEObservation
+from .nle_environment import NLEEnvironment
+
+# Read configuration from environment variables
+TASK_NAME = os.getenv("NLE_TASK", "score")
+CHARACTER = os.getenv("NLE_CHARACTER", "mon-hum-neu-mal")
+MAX_STEPS = int(os.getenv("NLE_MAX_STEPS", "5000"))
+
+# Create the environment instance
+env = NLEEnvironment(
+    task_name=TASK_NAME,
+    character=CHARACTER,
+    max_episode_steps=MAX_STEPS,
+)
+
+# Create the app with web interface and README integration
+app = create_app(env, NLEAction, NLEObservation, env_name="nle_env")
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    # NLE must run single-threaded (workers=1) due to C extension
+    uvicorn.run(app, host="0.0.0.0", port=8000, workers=1)

src/envs/nle_env/server/nle_environment.py

@@ -0,0 +1,241 @@
+# 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.
+
+"""
+NetHack Learning Environment Implementation.
+
+This module wraps the NLE (NetHack Learning Environment) as an OpenEnv
+environment, providing HTTP-based access to NetHack for RL training.
+"""
+
+import time
+from typing import Optional
+
+from core.env_server.interfaces import Environment, Transform
+
+from ..models import NLEAction, NLEObservation, NLEState
+
+# Import NLE - will be installed in Docker
+try:
+    from nle.env import NLE
+except ImportError:
+    NLE = None  # type: ignore
+
+
+class NLEEnvironment(Environment):
+    """
+    OpenEnv wrapper for the NetHack Learning Environment.
+
+    This environment wraps NLE's gym interface and provides OpenEnv-compatible
+    reset(), step(), and state access.
+
+    With beefy compute, we use simple JSON serialization and include all
+    observation types by default. No optimization needed - compute handles it.
+
+    Example:
+        >>> env = NLEEnvironment()
+        >>> obs = env.reset()
+        >>> print(obs.reward)  # 0.0
+        >>>
+        >>> obs = env.step(NLEAction(action_id=0))  # Move north
+        >>> print(obs.reward)  # Score delta
+        >>> print(env.state.step_count)  # 1
+    """
+
+    def __init__(
+        self,
+        task_name: str = "score",
+        character: str = "mon-hum-neu-mal",
+        max_episode_steps: int = 5000,
+        observation_keys: tuple = (
+            "glyphs",
+            "chars",
+            "colors",
+            "specials",
+            "blstats",
+            "message",
+            "inv_glyphs",
+            "inv_strs",
+            "inv_letters",
+            "inv_oclasses",
+            "tty_chars",
+            "tty_colors",
+            "tty_cursor",
+        ),
+        transform: Optional[Transform] = None,
+    ):
+        """
+        Initialize the NLE environment.
+
+        Args:
+            task_name: Task variant (score, staircase, oracle, gold, etc.)
+            character: Character definition (role-race-gender-alignment)
+            max_episode_steps: Maximum steps before episode is aborted
+            observation_keys: Which observations to include
+            transform: Optional observation transform
+        """
+        super().__init__(transform=transform)
+
+        if NLE is None:
+            raise ImportError(
+                "NLE is not installed. Install with: pip install nle\n"
+                "For Docker builds, this will be installed automatically."
+            )
+
+        self._task_name = task_name
+        self._character = character
+        self._observation_keys = observation_keys
+
+        # Create NLE gym environment
+        # With beefy compute: no ttyrec saving, all observations enabled
+        self.nle_env = NLE(
+            character=character,
+            observation_keys=observation_keys,
+            max_episode_steps=max_episode_steps,
+            save_ttyrec_every=0,  # Disable by default (can enable via env var)
+            wizard=False,  # Can enable via env var for debugging
+            spawn_monsters=True,
+        )
+
+        # Episode tracking
+        self._episode_id: Optional[str] = None
+        self._step_count = 0
+        self._last_reward = 0.0
+        self._last_done = False
+        self._end_status = "RUNNING"
+        self._in_normal_game = False
+
+    def reset(self) -> NLEObservation:
+        """
+        Reset the environment and return initial observation.
+
+        Returns:
+            NLEObservation with initial game state
+        """
+        # Reset NLE gym env
+        # Note: Gym 0.26+ returns (obs, info) tuple from reset()
+        reset_result = self.nle_env.reset()
+
+        # Handle both old gym API (returns obs dict) and new API (returns tuple)
+        if isinstance(reset_result, tuple):
+            gym_obs, _ = reset_result  # Unpack (observation, info)
+        else:
+            gym_obs = reset_result  # Old API
+
+        # Initialize episode tracking
+        self._episode_id = f"nle_{int(time.time() * 1000000)}"
+        self._step_count = 0
+        self._last_reward = 0.0
+        self._last_done = False
+        self._end_status = "RUNNING"
+        self._in_normal_game = self.nle_env.nethack.in_normal_game()
+
+        # Convert gym observation to OpenEnv observation
+        obs = self._convert_observation(gym_obs, reward=0.0, done=False)
+
+        return self._apply_transform(obs)
+
+    def step(self, action: NLEAction) -> NLEObservation:  # type: ignore[override]
+        """
+        Execute action in NetHack and return observation.
+
+        Args:
+            action: NLEAction with action_id (0-112)
+
+        Returns:
+            NLEObservation with game state after action
+        """
+        # Execute action in NLE
+        # Note: Gym 0.26+ returns (obs, reward, terminated, truncated, info)
+        #       Older gym returns (obs, reward, done, info)
+        step_result = self.nle_env.step(action.action_id)
+
+        # Handle both old and new gym APIs
+        if len(step_result) == 5:
+            # New gym API (0.26+): (obs, reward, terminated, truncated, info)
+            gym_obs, reward, terminated, truncated, info = step_result
+            done = terminated or truncated
+        elif len(step_result) == 4:
+            # Old gym API: (obs, reward, done, info)
+            gym_obs, reward, done, info = step_result
+        else:
+            raise ValueError(f"Unexpected step result length: {len(step_result)}")
+
+        # Update tracking
+        self._step_count += 1
+        self._last_reward = float(reward)
+        self._last_done = bool(done)
+        self._end_status = str(info.get("end_status", "RUNNING"))
+        self._in_normal_game = self.nle_env.nethack.in_normal_game()
+
+        # Convert observation
+        obs = self._convert_observation(gym_obs, reward=reward, done=done)
+
+        # Add metadata from NLE
+        obs.metadata.update(
+            {
+                "end_status": self._end_status,
+                "is_ascended": info.get("is_ascended", False),
+            }
+        )
+
+        return self._apply_transform(obs)
+
+    @property
+    def state(self) -> NLEState:
+        """
+        Get current environment state.
+
+        Returns:
+            NLEState with episode and game information
+        """
+        return NLEState(
+            episode_id=self._episode_id,
+            step_count=self._step_count,
+            game_over=self._last_done,
+            end_status=self._end_status,
+            in_normal_game=self._in_normal_game,
+            character=self._character,
+            task_name=self._task_name,
+        )
+
+    def _convert_observation(
+        self, gym_obs: dict, reward: float, done: bool
+    ) -> NLEObservation:
+        """
+        Convert NLE gym observation to NLEObservation.
+
+        With beefy compute, we just convert numpy arrays to lists.
+        No compression, no optimization - simplicity first.
+
+        Args:
+            gym_obs: Dictionary from NLE gym env
+            reward: Reward for this step
+            done: Whether episode is done
+
+        Returns:
+            NLEObservation with serialized arrays
+        """
+        obs_dict = {
+            "reward": float(reward),
+            "done": bool(done),
+            "metadata": {},
+        }
+
+        # Convert each observation type from numpy array to nested list
+        # This is simple and works perfectly with JSON + beefy compute
+        for key in self._observation_keys:
+            if key in gym_obs:
+                array = gym_obs[key]
+                # Convert numpy array to nested list for JSON serialization
+                obs_dict[key] = array.tolist()
+
+        return NLEObservation(**obs_dict)
+
+    def close(self):
+        """Clean up NLE environment."""
+        if hasattr(self, "nle_env"):
+            self.nle_env.close()