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what is polymarket-ai-trading fr?

trading-2028/polymarket-ai-trading — explained in plain English

Analysis updated 2026-05-18

219HTMLAudience · developerComplexity · 3/5Setup · moderate

tl;dr

A research and paper-trading toolkit that runs mean-reversion strategies against live Polymarket data without risking real money by default.

vibe map

mindmap
  root((Polymarket AI Trading))
    Strategy
      Mean reversion
      Conservative mode
      Moderate mode
      Aggressive mode
    Stack
      Node.js and Express
      SQLite storage
      Docker
    Extras
      Optional AI scoring
      Web dashboard
    Use cases
      Research prediction markets
      Learn trading systems

Code map

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filefunction / class

what do people make with this?

VIBE 1

Simulate mean-reversion trading strategies against live Polymarket data with no real funds.

VIBE 2

Compare Conservative, Moderate, and Aggressive risk profiles for the same strategy.

VIBE 3

Watch live signals and simulated performance on a web dashboard.

what's the stack?

Node.jsExpressSQLiteDocker

how it stacks up fr

trading-2028/polymarket-ai-tradingvoxybuns/at-iconskeyai/calculusmadeeasy-zh
Stars219222215
LanguageHTMLHTMLHTML
Setup difficultymoderateeasyeasy
Complexity3/51/51/5
Audiencedeveloperdeveloperwriter

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

how do i run it?

Difficulty · moderate time til it works · 30min

Runs with Docker, an OpenAI key is optional for the AI scoring layer.

in plain english

This is a research and paper trading toolkit for Polymarket, a prediction market platform where people bet on real-world outcomes. The system connects to live Polymarket data and runs automated strategies that simulate trading without moving any real money by default. The core strategy is called mean reversion, which is based on the idea that prices that drift far from their historical average tend to drift back. The system runs three versions of this idea simultaneously with different risk levels: Conservative (smaller bets, stricter entry rules), Moderate (middle ground), and Aggressive (larger simulated bets, looser entry rules). An optional AI layer can help score market quality when you provide an OpenAI key. All trade history is stored in a local SQLite database, and a web dashboard lets you watch signals, model performance, and AI scoring panels in real time. You would use this if you want to study prediction markets, test trading ideas in simulation, or learn how automated market systems work without risking money. It is built for people comfortable with Node.js and Docker who want a structured research environment. The stack is Node.js with Express for the backend API, SQLite for storage, Docker for running all services together, and a static web dashboard that can be deployed to a hosting platform. No real wallet or funds are required to run the default paper trading mode.

prompts (copy fr)

prompt 1
Help me run this Polymarket paper trading toolkit locally with Docker.
prompt 2
Explain how the mean-reversion strategy in this toolkit decides when to trade.
prompt 3
Show me how to add an OpenAI key to enable the AI market-scoring layer.

Frequently asked questions

what is polymarket-ai-trading fr?

A research and paper-trading toolkit that runs mean-reversion strategies against live Polymarket data without risking real money by default.

What language is polymarket-ai-trading written in?

Mainly HTML. The stack also includes Node.js, Express, SQLite.

How hard is polymarket-ai-trading to set up?

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

Who is polymarket-ai-trading for?

Mainly developer.

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