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Fund Ai Assistant

基金组合追踪器，具备AI分析、多智能体辩论、技术指标（VaR/Sortino/Calmar）、宏观监测和再平衡提醒。

person作者: tempest-01hubclawhub
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Fund AI Assistant

Version: 3.0 | License: MIT-0 | LLM: Any OpenAI-compatible provider

Overview

A local-first fund investment assistant running entirely on your machine. Fetches data from East Money, analyzes with any LLM provider, and supports scheduled tasks via OpenClaw or crontab.

⚠️ Security Notice: This skill requires LLM_MODEL + LLM_API_KEY. Use a dedicated API key. See Section 7 for all security considerations.

1. Features

| Feature | Description | |---------|-------------| | 📊 Technical Analysis | MACD / KDJ / RSI / Bollinger Bands / MA + VaR / Sortino / Calmar | | 🤖 AI Quantitative Analysis | Any LLM (OpenAI-compatible), outputs buy/sell/hold with price targets | | ⚖️ Multi-Agent Debate | 6 roles → game-theory judge verdict | | 📋 Portfolio Rebalancing | Detects allocation drift, outputs precise rebalancing instructions | | 🎯 Entry Timing | RSI + Bollinger + trend composite score | | 🌡️ Correlation Heatmap | Pairwise correlation matrix for diversification | | 🌍 Macro Event Monitor | CSI300 / USD-CNY / FOMC / LPR alerts |

2. Environment Variables

Required

| Variable | Description | |----------|-------------| | LLM_MODEL | Model name, e.g. gpt-4o-mini | | LLM_API_KEY | Your LLM API key |

Optional

| Variable | Description | |----------|-------------| | LLM_API_BASE | ⚠️ Custom API URL — if untrusted, your key and data go there. Use endpoints you control. Default: https://api.openai.com/v1 | | TAVILY_API_KEY | Tavily API for real-time macro search | | FUND_SCENE_DIR | Directory with optional .md scene templates (default: ./scenes/) | | PUSH_WEBHOOK_URL | Generic HTTP POST webhook (WeCom / Feishu / Slack) | | BARK_PUSH_URL | iOS Bark notification URL | | PUSH_EMAIL | Target email for SMTP push | | SMTP_HOST/PORT/USER/PASS | SMTP configuration (used with PUSH_EMAIL) | | QQ_WEBHOOK_URL | QQ bot HTTP interface (go-cqhttp / Lagrange) |

Setup Example

export LLM_MODEL="gpt-4o-mini"
export LLM_API_KEY="sk-xxx"

# Optional
export TAVILY_API_KEY="tvly-xxx"
export PUSH_WEBHOOK_URL="https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=YOUR_KEY"

3. Installation

# 1. Clone
git clone https://github.com/tempest-01/fund-ai-assistant.git
cd fund-ai-assistant

# 2. Install optional dependencies (charts)
pip install -r requirements.txt

# 3. Configure
cp config.example.json config.json
cp positions.example.json positions.json

# 4. Set environment variables (see Section 2)
export LLM_MODEL="your_model"
export LLM_API_KEY="your_key"

# 5. Verify
python3 analyzer.py list
python3 analyzer.py analyze

4. Script Reference

| Script | Function | Usage | |--------|----------|-------| | analyzer.py | Main entry, tracking + analysis | python3 analyzer.py list | | ai_analysis.py | AI quantitative analysis | python3 ai_analysis.py | | debate_analyzer.py | Multi-agent debate | python3 debate_analyzer.py <code> | | rebalance.py | Portfolio drift detection | python3 rebalance.py | | recommend.py | Entry timing suggestions | python3 recommend.py | | event_monitor.py | Macro event monitor | python3 event_monitor.py | | correlation_v2.py | Correlation heatmap | python3 correlation_v2.py | | fund_api.py | East Money data API | python3 fund_api.py | | technical.py | Technical indicators | python3 technical.py | | chart_generator.py | PIL chart generation | python3 chart_generator.py | | positions.py | Position record management | python3 positions.py | | macro_fetcher.py | Macro data fetcher | python3 macro_fetcher.py | | strip_color.py | ANSI strip for cron | cmd \| python3 strip_color.py | | llm.py | Unified LLM interface | from llm import get_llm_config, call_llm |

5. Scheduled Tasks (Reference)

# OpenClaw users
openclaw cron add --cron "0 8 * * 1-5" \
  --message "cd /path/to/fund-ai-assistant && python3 event_monitor.py --dry-run"

openclaw cron add --cron "30 9 * * 1-5" \
  --message "cd /path/to/fund-ai-assistant && python3 analyzer.py analyze"

# crontab users
0 8 * * 1-5 cd /path/to/fund-ai-assistant && python3 event_monitor.py >> /var/log/fund.log 2>&1

6. File Structure

fund-ai-assistant/
├── .gitignore
├── _meta.json              # Registry metadata
├── SKILL.md               # This file
├── README.md              # Full bilingual documentation
├── config.example.json     # Tracking list template
├── positions.example.json  # Position record template
├── requirements.txt       # Optional: Pillow / numpy / matplotlib
├── llm.py                # Unified LLM interface
├── analyzer.py            # Main entry
├── ai_analysis.py         # AI quantitative analysis
├── debate_analyzer.py    # Multi-agent debate
├── rebalance.py           # Portfolio drift detection
├── recommend.py          # Entry timing
├── event_monitor.py      # Macro event monitor
├── correlation_v2.py     # Correlation heatmap
├── fund_api.py           # East Money API
├── technical.py          # Technical indicators
├── chart_generator.py    # PIL chart generation
├── macro_fetcher.py      # Macro data
├── positions.py          # Position records
├── strip_color.py        # ANSI color strip
└── assets/             # Chart output (auto-created)

7. Security Notes

Read carefully before installing and running.

Required Credentials

  • LLM_MODEL and LLM_API_KEY are required. Use a dedicated API key, not a high-value production key.
  • Before first run, inspect llm.py and fund_api.py to confirm no credential exfiltration.

Filesystem Access

  • FUND_SCENE_DIR: The skill reads .md template files from the directory you specify.
    • Do NOT point it at system directories, home directories, or folders containing secrets.
    • If unset, defaults to {skill_dir}/scenes/ (which is created empty).
    • Only .md files in that directory are read.

Network Access

  • East Money APIs: fundgz.1234567.com.cn, api.fund.eastmoney.com — public fund data.
  • Tavily (if TAVILY_API_KEY set): Real-time macro search.
  • Push endpoints (if configured): Analysis summaries are sent to the URLs you provide.

Push Channels

If any of these are set, analysis output will be transmitted externally:

| Variable | Transmission | |----------|-------------| | PUSH_WEBHOOK_URL | HTTP POST to your webhook URL | | BARK_PUSH_URL | GET request to your Bark URL | | PUSH_EMAIL | SMTP email to your address | | QQ_WEBHOOK_URL | HTTP POST to your QQ bot |

Use endpoints you control. Do not set these with untrusted third-party URLs.

Data Privacy

  • All fund data is fetched from East Money on demand; no persistent storage of market data.
  • Position records (positions.json) are stored locally in the skill directory only.
  • LLM API key is sent only to the configured LLM_API_BASE endpoint.
  • No telemetry, no external analytics, no data sent to third parties without explicit configuration.

Recommended Precautions

  1. Use a dedicated LLM API key — not your main production key.
  2. ⚠️ Inspect LLM_API_BASE — if set to an untrusted endpoint, your API key and fund data will be sent there. Only use https://api.openai.com/v1 or endpoints you control.
  3. Review llm.py and fund_api.py before first run.
  4. Run in an isolated environment (container or VM) on first use.
  5. Do not set FUND_SCENE_DIR to sensitive directories.
  6. Do not share your LLM_API_KEY or push endpoint URLs.

8. Inspiration & Attribution

  • astrbot_plugin_fund_analyzer — Multi-agent debate framework inspiration; adapted from stock to fund analysis with added portfolio management features.
  • OpenClaw — Scheduling and notification infrastructure.
  • East Money (东方财富) — Fund price and history data source.
  • Tencent Finance (腾讯财经) — CSI300 real-time data source.

This skill was developed with AI assistance.