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cjami/pokerbot-3000

Analysis updated 2026-05-18

1PythonAudience · developerComplexity · 4/5Setup · moderate

TLDR

A live three-player Texas Hold'em game where a human speaks their moves out loud and plays against two AI characters, with card recognition handled by a vision-language model and voices provided by ElevenLabs.

Mindmap

mindmap
  root((PokerBot 3000))
    What It Does
      Three seat poker game
      Voice input for human
      AI opponents speak and act
    Card Recognition
      Camera reads board cards
      Gemma 4 31B vision model
      Private cards stay hidden
    Tech Stack
      Python FastAPI
      Cerebras inference
      ElevenLabs voices
      Tailwind CSS
    Setup
      API keys required
      uv and Node.js
      Four command start
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Run a three-seat Texas Hold'em game with one human player and two AI opponents that speak and react in real time.

USE CASE 2

Test multimodal AI card recognition using a camera feed and Gemma 4 31B to read poker cards from video frames.

USE CASE 3

Build on top of the FastAPI streaming game-state architecture to create your own live multi-agent card or board game.

What is it built with?

PythonFastAPIUvicornTailwind CSSesbuildGemma 4 31BCerebrasElevenLabs

How does it compare?

cjami/pokerbot-3000a-bissell/unleash-liteabhiinnovates/whatsapp-hr-assistant
Stars111
LanguagePythonPythonPython
Setup difficultymoderatehardhard
Complexity4/54/53/5
Audiencedeveloperresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires paid Cerebras and ElevenLabs API keys, camera and microphone access needed in the browser.

In plain English

PokerBot 3000 is a live poker game where a human plays against two AI-powered characters at a three-seat Texas Hold'em table. It was built in 24 hours for a hackathon. The AI opponents are named Eliza and Reachy Mini, a small physical robot. The game uses cameras to read playing cards on the table, including the shared community cards and each AI's private hand. A microphone picks up the human player's spoken commands, such as "call", "raise to 100", or "all in". The system transcribes those commands and advances the game accordingly. The two AI opponents make their own decisions, speak out loud during play using synthesized voices, and can display emotion cues. Under the hood, a large AI vision-language model called Gemma 4 31B, running on the Cerebras inference service, handles both card recognition from camera frames and decision-making for the AI players. ElevenLabs provides speech-to-text for the human player's voice and text-to-speech for the agents' spoken responses. The game state, events, and audio are streamed to an operator dashboard in the browser. Private cards are kept hidden from opposing players throughout. The backend is built with Python 3.12 using FastAPI and Uvicorn. The browser interface uses Tailwind CSS and is bundled with esbuild. Running the project requires API keys for both Cerebras and ElevenLabs, which you configure in a local environment file. Setup uses the uv package manager and Node.js for front-end assets, and the whole thing starts with four shell commands. A physical Reachy Mini robot can optionally be connected for gesture and movement responses, though the game runs without it. The repository includes commands for tests, linting, and formatting. It was described as a hackathon project and is not positioned as a production application.

Copy-paste prompts

Prompt 1
Using PokerBot 3000, show me how to configure the .env file with a Cerebras API key and ElevenLabs voice IDs to get the three-seat Hold'em table running locally.
Prompt 2
How does PokerBot 3000 use Gemma 4 31B as a vision-language model to read playing cards from a camera frame? Walk me through the card recognition flow.
Prompt 3
I want to swap out the Eliza AI character in PokerBot 3000 for a different personality. Where in the FastAPI backend should I change the agent prompt and voice settings?
Prompt 4
Show me how PokerBot 3000 streams game state and events to the browser dashboard using FastAPI and Uvicorn.

Frequently asked questions

What is pokerbot-3000?

A live three-player Texas Hold'em game where a human speaks their moves out loud and plays against two AI characters, with card recognition handled by a vision-language model and voices provided by ElevenLabs.

What language is pokerbot-3000 written in?

Mainly Python. The stack also includes Python, FastAPI, Uvicorn.

How hard is pokerbot-3000 to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is pokerbot-3000 for?

Mainly developer.

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