Ondra fix pypi readme

README_pypi.md

@@ -0,0 +1,81 @@
+# NetSecGame
+
+**NetSecGame (NSG)** is a framework for training and evaluating AI agents in network security environments. Developed at the [Stratosphere Laboratory](https://www.stratosphereips.org/) at CTU in Prague, NSG provides a fast, highly configurable testbed for both offensive and defensive security operations.
+
+Unlike traditional static datasets or rigid simulations, NetSecGame offers a dynamic playground adopting standard Reinforcement Learning (RL) principles. It is built natively on top of the CYST network simulator to allow for scalable experimentation. It provides a rich `GameState` representation than standard interfaces, enabling complex and realistic security interactions where:
+- **Attackers** learn to scan networks, discover services, exploit vulnerabilities, and exfiltrate data.
+- **Defenders** learn to monitor traffic, detect anomalies, block malicious actors, and protect critical assets.
+- **Benign Users** learn to simulate routine administrative or end-user behaviors that provide realistic background activity.
+
+It natively includes a stochastic **Global Defender** (SIEM-like simulation) to provide realistic opposition and noise for attackers, reducing the need for pairs or trained agents to challenge offensive operations.
+
+## Installation
+
+You can install NetSecGame as an agent development framework via pip:
+
+```bash
+pip install netsecgame
+```
+
+To install the dependencies necessary for locally running the game server and network simulation engine:
+
+```bash
+pip install netsecgame[server]
+```
+
+## Running the Game Environment
+
+NetSecGame separates the game server from the interacting agents, ensuring flexibility in deployment. The easiest way to run the NetSecGame server is via the [official Docker image](https://hub.docker.com/r/stratosphereips/netsecgame):
+
+```bash
+docker pull stratosphereips/netsecgame
+docker run -d --rm --name nsg-server \
+    -v $(pwd)/<scenario-configuration>.yaml:/netsecgame/netsecenv_conf.yaml \
+    -v $(pwd)/logs:/netsecgame/logs \
+    -p 9000:9000 stratosphereips/netsecgame
+```
+
+Alternatively, you can run the server directly on your local machine using the Python module:
+
+```bash
+python3 -m netsecgame.game.worlds.NetSecGame \
+  --task_config=./examples/example_task_configuration.yaml \
+  --game_port=9000
+```
+
+## Creating Agents
+
+It's simple to jump into creating agents. We provide a companion repository, [NetSecGameAgents](https://github.com/stratosphereips/NetSecGameAgents), complete with reference implementations for Random, Tabular, and LLM-based agents. 
+
+Here is a quick look at implementing an agent:
+
+```python
+from netsecgame import BaseAgent, Action, GameState, Observation, AgentRole
+
+class MyAgent(BaseAgent):
+    def __init__(self, host, port, role: str):
+        super().__init__(host, port, role)
+
+    def choose_action(self, observation: Observation) -> Action:
+        # Define logic to interact with observation.state
+        pass
+
+def main():
+    agent = MyAgent(host="localhost", port=9000, role=AgentRole.Attacker)
+    observation = agent.register()
+
+    while not observation.end:
+        action = agent.choose_action(observation)
+        observation = agent.make_step(action)
+
+    agent.terminate_connection()
+```
+
+## Discover More
+
+Refer to our official channels and repositories for configuration instructions, architecture documents, and contributing instructions!
+
+*   **Official Documentation**: [https://stratosphereips.github.io/NetSecGame/](https://stratosphereips.github.io/NetSecGame/)
+*   **GitHub**: [https://github.com/stratosphereips/NetSecGame](https://github.com/stratosphereips/NetSecGame)
+*   **Docker Hub**: [https://hub.docker.com/r/stratosphereips/netsecgame](https://hub.docker.com/r/stratosphereips/netsecgame)
+*   **Stratosphere Laboratory**: [https://www.stratosphereips.org/](https://www.stratosphereips.org/)

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta"
 name = "netsecgame"
 dynamic = ["version"]
 description = "A package for coordinating AI-driven network simulation games."
-readme = "README.md"
+readme = "README_pypi.md"
 license = "GPL-3.0-or-later"
 license-files = ["LICENSE"]
 authors = [