开源交易 bot：Jev 每 300ms 决定买或卖
有人把整套交易循环开源到 GitHub，用 Jev 读订单簿返回买卖概率，代码负责挂单，可先无密钥干跑。
stop scrolling and clone this before it gets paywalled. someone put their entire trading loop on GitHub. the model, the order logic, the dashboard. all of it. it makes one decision every ~300 milliseconds and quotes a fresh limit order on every single block. the brain is Jev. it can't write a word. it looks at the order book and returns buy or sell with a probability. what the loop does each block: -> reads the live order book -> asks Jev: buy or sell? -> posts a post-only limit order one tick inside the touch -> replaces the last order -> waits for a taker to hit it the useful part: it never crosses the spread. fills only happen when someone else takes the order, so the bot is built to earn the spread instead of paying it. and every block is logged: the decision, the probabilities, the latency, the quote. the setup: git clone https://github.com/jarrodwatts/jev-trader cp .env.example .env bun install bun run start -> with no private key it dry-runs: real book, real decisions, simulated fills then in .env: MODEL=jev TYPESAFE_AI_API_KEY=your-key -> swaps the built-in momentum stand-in for Jev want the full desk instead of one loop? -> QuantDinger ships Jev as a pre-trade gate: research, Python strategies, backtest, paper and live https://github.com/OpenByteInc/QuantDinger the workflow: order book in -> Jev decides -> code prices the order -> the market fills it or doesn't start here: one clone -> dry run -> watch 1,000 blocks of decisions before a single real order the catch: fast is not the same as right. quoting inside the spread can still lose money when the price moves against you. none of this is an ATM. > let the big model do the research. > let Jev make the call. > let code place the order. clone it now. dry-run it tonight. decide tomorrow.
这条是引用着另一条写的：x.com/thegreatest_sv/status/2102802378378621355