quant-python-ai — Agent Tool by aidatatools

by aidatatools · Agent Tool · ★ 77

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About quant-python-ai

Quant Python AI 量化投資研究 AI Agent（CLI）— 自動搜尋財經新聞、彙整重點、分析市場情緒與風險因素，並輸出帶有來源引用的報告。 注意：本專案僅做資訊整理與研究輔助，不構成投資建議；不提供買賣點、停損停利等交易指令。 功能 新聞研究 — 透過 Tavily API 搜尋近期新聞/財報相關資訊 LLM 分析 — 將研究來源（視為 UNTRUSTED）整理後交給 LLM 進行摘要、情緒判斷與觀察重點 風險審查 — 由 LLM 以風險管理角度補充風險因素與可觀察指標（不提供交易建議） 引用來源（Citations） — LLM 輸出需以 格式引用；報告同時輸出來源 URL 表 多模型切換（OpenAI-compatible） — 以 形式切換 ：直接使用 OpenAI API ：透過 OpenRouter 使用大量第三方模型（同為 OpenAI-compatible API） 專案結構 展示 安裝 前置需求 Python = 3.13 uv（推薦）或 pip 步驟 如果不用 uv： bash python -m venv .venv source .venv

ai-agentsai-tools

Quick Facts

Stars77
Forks33
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score37.75/100
Open Issues3
Last Updated2026-02-23
Created2026-02-12
Platformscli, python
Est. Tokens~617k

Compatible Skills

These tools work well together with quant-python-ai for enhanced workflows:

  • agentor — semantic(0.38)+complementary+same_lang+similar_pop+shared_platform (58%)
  • agent-builder — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • aser — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (55%)

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Frequently Asked Questions

What is quant-python-ai?

quant-python-ai is 量化投資研究 AI Agent — 透過 CLI 互動介面，自動搜尋財經新聞、分析市場情緒、產生風險評估報告。可接OpenClaw。. It is categorized as a Agent Tool with 77 GitHub stars.

What programming language is quant-python-ai written in?

quant-python-ai is primarily written in Python. It covers topics such as ai-agents, ai-tools.

How do I install or use quant-python-ai?

You can find installation instructions and usage details in the quant-python-ai GitHub repository at github.com/aidatatools/quant-python-ai. The project has 77 stars and 33 forks, indicating an active community.

What license does quant-python-ai use?

quant-python-ai is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to quant-python-ai?

The top alternatives to quant-python-ai on Agent Skills Hub include Agentfy, kindly-web-search-mcp-server, flyto-core. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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