dojoagents 0.1.0

AI Agent

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DojoAgents: Full-Market AI Copilot for Personal Investment

DojoAgents is a full-market AI agent framework designed specifically for personal investment. Built to bridge the gap between individual investors and institutional-grade tools, its true powerhouse is a state-of-the-art Agent Loop engine. Instead of a simple dashboard, DojoAgents deploys an autonomous reasoning agent that lives alongside your portfolio, handling everything from full-market data cognition to dynamic cross-market strategy deduction.

✨ Why DojoAgents?

🧠 Loop-Driven Cognitive Portfolio Agent (Our Core Engine): Most financial AI tools are built for quick outputs: news summaries, single-stock explanations, basic indicator readings, or generic market commentary. Our Loop-Driven Cognitive Portfolio Agent is built for portfolio-aware reasoning, connecting your holdings with market data and running structured analysis across four dimensions:

• Fundamental Data Cognition: Instantly fetches, structures, and cross-references raw multi-market data (K-lines, financials, news).
• Advanced Logic Analysis: Interprets valuation bands, momentum indicators, and sector taxonomy to uncover hidden market mechanics.
• Cross-Market Strategy Deduction: Formulates macro asset allocation and maps market linkages (e.g., autonomously reasoning through "Why US semiconductor software dropped while A-shares surged" via multi-step tool execution).
• Dynamic Portfolio Management: Continuously diagnoses risk exposure, monitors net-worth curves, and evaluates performance attribution to support more informed rebalancing decisions.

📊 Four-Pillar Dashboard: An out-of-the-box, institutional-grade React SPA featuring:

• Portfolio (The Command Center): Net worth curves, live risk exposure, and smart position tracking.
• Markets: Cross-market heatmaps (US/HK/A-shares) and index tracking.
• Sectors: Deep-dive L1/L2/L3 taxonomy and momentum curves.
• Equities: K-lines, PE bands, financials, and news—all in one unified view.

🤖 Autonomous Quant Analyst: Powered by multi-agent collaboration, it autonomously conducts background market research, tracks sector rotations, and monitors your risk exposure while you sleep.

**📱 Planned Omnichannel Updates: Future versions will support personalized daily briefings and alert notifications through Slack, Telegram, Discord, Feishu, WeChat, or email.

🚀 Quick Start

Deploying your DojoAgents environment is designed to be frictionless. We strongly recommend using uv for lightning-fast dependency management.

1. Requirements

• Python >= 3.11
• Node.js: >= 18 (for frontend build)
• npm: >= 9
• An LLM API Key (OpenAI, Gemini, Anthropic, etc.)

2. Core Installation

Runtime dependencies are listed in both pyproject.toml and requirements.txt.

# 1. Create and activate a virtual environment
uv venv && source .venv/bin/activate

# 2. OPTION - For Developers & Contributors:
# Install in "editable mode" with dev tools. Any source code changes will take 
# effect immediately—perfect for building custom tools or debugging the Agent Loop.
uv pip install -e ".[dev]"

# 3. Install the core dependencies.
uv pip install -r requirements.txt

3. Dashboard Build

The DojoAgents Dashboard is a high-performance React SPA powered by Vite, communicating with a FastAPI backend via an OpenAI-compatible chat API and SSE streaming for dynamic Canvas chart rendering.

If you are building from source, you will need Node.js (>= 18) and npm (>= 9).

cd dojoagents/dashboard/web
npm install
npm run build

4. Launching the Server

dojoagents dashboard --host 127.0.0.1 --port 8765

Open http://127.0.0.1:8765/ in your browser to access your personal financial command center.

5. Configure Your LLM Engine (In-App)

Once the dashboard is live, click on the Settings icon. DojoAgents features a comprehensive graphical interface to securely configure your preferred Large Language Models.

• Supported Providers: Out-of-the-box presets for OpenAI, Anthropic, Google Gemini, Zhipu GLM, and DeepSeek.
• Local & Custom Endpoints: Easily override Base URLs to connect to local instances like Ollama, llama.cpp, or vLLM.
• Secure Storage: All API keys and endpoint settings entered in the UI are securely written to your local ~/.dojo/agents.yaml file.

🧠 Core Architecture

DojoAgents is engineered for scale, deep contextual reasoning, and absolute privacy.

• Agent Loop Engine: The core reasoning runtime. Handles multi-turn tool orchestration, context window compression, and strict guardrails to prevent financial hallucinations.
• Execution Sandbox: A secure, isolated environment for on-the-fly Python code execution, technical indicator calculations, and local web data extraction.
• Memory & SKILLS: Automatically distills successful, multi-step market analysis workflows into reusable, programmatic SKILLS for future execution.
• Cron & Gateway: Decoupled delivery pipelines that push scheduled, automated insights directly to your preferred chat applications, without blocking the main Agent reasoning loop.

📚 Documentation & Deep Dives

Ready to build custom quantitative skills, integrate proprietary data, or deploy a multi-agent swarm? Dive into our comprehensive developer guides:

• System Architecture & Design Philosophy
• Writing Custom Plugins & Claude Skills
• Chat Gateways & Omnichannel Setup
• Dashboard UI Customization Guide

🤝 Contributing

We are building the ultimate open-source financial AI, and we'd love your help! Check out our Contribution Guidelines to see how you can add new tools, refine the agent prompts, or expand market coverage.

License: DojoAgents is open-source under the Apache License 2.0.

⚠️ Disclaimer

This project is for educational, research, and demonstration purposes only and does not provide investment advice or trading recommendations. Trading financial instruments involves significant risk, including possible loss of capital. All data, analysis, and outputs are for reference only and may not be accurate, complete, or up to date. Users are responsible for their own investment decisions, and this project and its contributors are not liable for any loss resulting from reliance on the information provided. Third-party names, logos, and brands are used for identification purposes only and do not imply endorsement or affiliation.