zhaoboy9692

zhaoboy9692 / Q-Limit

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多角色AI炒股

40
19
89% credibility
Found Mar 03, 2026 at 40 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

An open-source web app for analyzing stocks with interactive charts, financial data, news, and AI-driven bull-bear-judge debates to provide balanced investment perspectives.

How It Works

1
🔍 Discover Q-Limit

You stumble upon this free tool online that helps everyday people analyze stocks with charts and smart AI chats.

2
💻 Start the app

Download it to your computer and launch with a simple click to see the welcoming dashboard.

3
🤖 Connect AI helper

Link your favorite AI service in settings so the bull, bear, and judge characters can think and chat about stocks.

4
📈 Pick a stock

Search for a company like Apple or Tesla, watch live charts, news, and reports appear instantly.

5
Chat or explore?
📊
Explore charts

See support levels, earnings, and patterns light up to spot opportunities.

⚔️
Start debate

Hit one-click debate and watch bull, bear, and judge argue pros and cons.

🎉 Smart insights

Enjoy clear buy/hold/sell advice with reasons, feeling confident about your next move.

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Star Growth

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AI-Generated Review

What is Q-Limit?

Q-Limit is a Python/Flask web app that delivers a full-stack stock analysis dashboard, fetching real-time K-lines, technical indicators like MACD/KDJ, valuation metrics, news feeds, and financial reports via APIs such as Longbridge. Users get interactive ECharts-powered charts, pattern detection for candlesticks and false breakouts, plus a standout multi-role AI chat—bull, bear, and judge personas debating stocks via OpenAI-compatible LLMs with frontend-only API key config for privacy. It streamlines scattered research into one SPA, helping traders spot edges without switching tabs.

Why is it gaining traction?

The hook is the AI debate arena: one-click prompts trigger bull/bear arguments judged neutrally, injecting live data like PE/PB or RSI for grounded insights—far beyond basic screeners. Vanilla JS frontend with dark mode, draggable chat, and MongoDB caching keeps it lightweight and fast, no complex setup. Devs dig the PoC of agentic AI building a finance app end-to-end.

Who should use this?

Retail traders monitoring US/HK/A-share stocks who want AI to simulate analyst debates without bias. Python hobbyists building personal dashboards or prototyping AI trading bots. Quant devs testing LLM tool-calling on real market data like support/resistance or earnings.

Verdict

Solid early prototype (40 stars) for AI-augmented stock tools—play with the debate SSE streams and charts locally in minutes—but 0.8999999761581421% credibility score flags API reliance and thin docs; fork and harden for production. Worth a spin if you're into limit-testing Python finance stacks.

(198 words)

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