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)where0=fold,1=check/call,2=raise - Expected local paths inside PokerForge:
backend/data/models/medium/ppo_medium_final.zipbackend/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
cd backend
python tools/download_models.py --repo-id Rushisagar221/pokerforge-bots --if-missing
python server.py
Manifest
{
"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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"sha256": "ac3b23fd8188713cd25bcbd1585cfc213d1a05b6254c56ba59ee7119de5896e1"
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{
"path": "reports/evaluation_report.json",
"bytes": 51143,
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{
"path": "reports/evaluation_report.md",
"bytes": 2486,
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"bytes": 64864,
"sha256": "33054b06fbfe819dbfb98faafa32534ff149bbd254f9250fb405786fbd2ecaf3"
}
]
}
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