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CommunityTools & Integrations156 starsVerified 2026-09-22

Jev X Sentiment Analysis

An on-demand crypto decision-support terminal that ingests 50-1,000 tweets through a two-tier statistical pipeline, then has Jev's System One answer four typed questions and return a decision card with entry ranges, stop losses, and targets without executing trades.

Category
Tools & Integrations
Published by
Community
Author
brainstormity
Added
2026-09-22
Tagscommunitypythontradingconfidencedata

Highlights

  • Ingests 50 to 1,000 tweets per request alongside CCXT price, funding-rate, and open-interest data.
  • Tier 1 Python stats compute engagement velocity, author diversity, and keyword sentiment polarity.
  • SQLite dedup halts pagination at the first known tweet ID, so repeat searches mostly hit local cache.
  • Jev answers four typed questions concurrently: trade action, sentiment spectrum, squeeze risk, and catalyst significance.
  • Returns a decision card with calibrated confidence, entry range, stop loss, and targets; trades stay manual.

Quickstart

bash
pip install -r requirements.txt

Watch out

MIT-licensed. Needs TypeSafe and TwitterAPI.io API keys, and searches cost roughly $0.009 to $0.15 depending on sample size; it is decision support, not financial advice.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

The open System One roundup

Jev 发布没几天,开源社区已经开始疯狂复刻了🔥 最值得推荐的五个模型: 1、Laya 421M:原生决策模型,支持 Mac 2、Decider-2B:最像 Jev,基于 Qwen3.5 3、NanoJev 0.6B:专门的 Decision Head 4、Reflex:Qwen3.5 + Direct Logits 5、System-One 4B:专门做概率校准 Show more

小墨同学
小墨同学
@xiaomovps

Jev 刚发布没几天,开源社区就出现了同款🔥 Decider-2B模型,是基于 Qwen3.5-2B 做了特殊调整 它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型 但两者还是有几个明显区别: 1、模型 Jev:闭源 System One Model Decider:Qwen3.5-2B,约 1.9B 参数,Apache 2.0 开源 2、价格

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The launch post

Trading bot, one decision per block

Classifying 1,500 real emails

this model is actually insane at email classification i tested it on 1500 of my own emails to see how well it works and I am blown away

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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Fast browser use with Stagehand

we built blazing fast computer/browser use with Jev + @Stagehanddev. this task cost $0.001 and executed at near instant speed (in a remote browser btw) the loop: observe the page, send a11y tree as state + actions as questions, Jev decides the next action, then Stagehand Show more

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

LLM-as-a-judge, sped up

Jev has spoken. It picked which model is AGI. 20–200x faster. 40–400x cheaper. This could make things like LLM-as-a-judge insanely fast and nearly free. (I tried a bunch of prompts and still didn’t burn through $0.10.)

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Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply