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Rushisagar221/
pokerforge-bots

stable-baselines3

reinforcement-learning

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PokerForge PPO Poker Bots

This repository contains runtime artifacts for PokerForge, a full-stack AI poker platform built around heads-up No-Limit Texas Hold'em abstractions.

Files

models/medium/ppo_medium_final.zip - PPO medium bot trained for 1M timesteps vs easy.
models/hard/ppo_hard_final.zip - PPO hard bot trained for 5M timesteps vs frozen medium.
models/*/best_model.zip - best checkpoints from training/evaluation callbacks.
reports/evaluation_report.* - latest reproducible bot-vs-bot evaluation report.
reports/representative_hands.json - replay-ready sample hand logs for the frontend dashboard.

Runtime Contract

Framework: Stable-Baselines3 PPO
Observation space: Box(18,)
Action space: Discrete(3) where 0=fold, 1=check/call, 2=raise
Expected local paths inside PokerForge:
- backend/data/models/medium/ppo_medium_final.zip
- backend/data/models/hard/ppo_hard_final.zip

Evaluation Summary

The latest evaluation report is included under reports/. The current honest finding is that medium and hard both beat easy, while hard only shows a marginal, statistically weak edge over medium. This is attributed mainly to the limited 3-action abstraction creating a ceiling on behavioral differentiation.

Reproduce In PokerForge

bash

cd backend
python tools/download_models.py --repo-id Rushisagar221/pokerforge-bots --if-missing
python server.py

Manifest

json

{
  "repo_id": "Rushisagar221/pokerforge-bots",
  "generated_at": "2026-04-23T14:08:03.040902",
  "artifacts": [
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      "path": "models/medium/ppo_medium_final.zip",
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    },
    {
      "path": "models/medium/best_model.zip",
      "bytes": 162116,
      "sha256": "31d26001f967b7d221af016ec1a4c5b1a33f32b71630cb2eea3bf9c8a2e59956"
    },
    {
      "path": "models/hard/ppo_hard_final.zip",
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    }
  ]
}