AI Stock Analysis System

AI-powered stock analysis system for A-shares / Hong Kong / US stocks

Analyze your watchlist daily → generate a decision dashboard → push to multiple channels (Telegram/Discord/Slack/Email/WeChat Work/Feishu)

Zero-cost deployment · Runs on GitHub Actions · No server required

Quick Start · Key Features · Sample Output · Full Guide · FAQ · Contributing · All Docs

English | 简体中文 | 繁體中文

💖 Sponsors

Easily scrape real-time financial news data from search engines - SerpApi

✨ Key Features

Module	Feature	Description
AI	Decision Dashboard	One-sentence conclusion + precise entry/exit levels + action checklist
Analysis	Multi-dimensional Analysis	Technicals + chip distribution + sentiment + real-time quotes
Market	Global Markets	A-shares, Hong Kong stocks, US stocks
Review	Market Review	Daily overview, sectors, northbound capital flow
Backtest	AI Backtest Validation	Auto-evaluate historical analysis accuracy, direction win rate, SL/TP hit rates
Agent Q&A	Strategy Chat	Multi-turn strategy chat with 11 built-in trading strategies (internally loaded as skills) (Web/Bot/API)
Notifications	Multi-channel Push	Telegram, Discord, Slack, Email, WeChat Work, Feishu, etc.
Automation	Scheduled Runs	GitHub Actions scheduled execution, no server required

Tech Stack & Data Sources

Type	Supported
LLMs	Gemini (free), OpenAI-compatible, DeepSeek, Qwen, Claude, Ollama
Market Data	AkShare, Tushare, Pytdx, Baostock, YFinance
News Search	Tavily, SerpAPI, Bocha, Brave, MiniMax

Built-in Trading Rules

Rule	Description
No chasing highs	Auto warn when deviation > 5%
Trend trading	Bull alignment: MA5 > MA10 > MA20
Precise levels	Entry, stop loss, target
Checklist	Each condition marked as Pass / Watch / Fail

🚀 Quick Start

Option 1: GitHub Actions (Recommended, Zero Cost)

No server needed, runs automatically every day!

1. Fork this repository

Click the Fork button in the upper right corner

2. Configure Secrets

Go to your forked repo → Settings → Secrets and variables → Actions → New repository secret

AI Model Configuration (Choose one)

For detailed configuration, see LLM Config Guide (three-tier config, channels, Vision, Agent, troubleshooting).

Secret Name	Description	Required
`GEMINI_API_KEY`	Get free API key from Google AI Studio	✅*
`OPENAI_API_KEY`	OpenAI-compatible API Key (supports DeepSeek, Qwen, etc.)	Optional
`OPENAI_BASE_URL`	OpenAI-compatible API endpoint (e.g., `https://api.deepseek.com/v1`)	Optional
`OPENAI_MODEL`	Model name (e.g., `deepseek-chat`)	Optional
`OLLAMA_API_BASE`	Ollama local service address (e.g. `http://localhost:11434`), for local/Docker deployment; do not use `OPENAI_BASE_URL` for Ollama, see LLM Config Guide - Ollama	Optional

*Note: Configure at least one of GEMINI_API_KEY, OPENAI_API_KEY, or OLLAMA_API_BASE (local). Ollama requires OLLAMA_API_BASE; using OPENAI_BASE_URL causes 404.

Notification channels (expand, choose at least one)

Secret Name	Description	Required
`TELEGRAM_BOT_TOKEN`	Telegram Bot Token (Get from @BotFather)	Optional
`TELEGRAM_CHAT_ID`	Telegram Chat ID	Optional
`TELEGRAM_MESSAGE_THREAD_ID`	Telegram Topic ID (For sending to topics)	Optional
`DISCORD_WEBHOOK_URL`	Discord Webhook URL	Optional
`DISCORD_BOT_TOKEN`	Discord Bot Token (choose one with Webhook)	Optional
`DISCORD_MAIN_CHANNEL_ID`	Discord Channel ID (required when using Bot)	Optional
`SLACK_BOT_TOKEN`	Slack Bot Token (recommended, supports image upload; takes priority over Webhook when both set)	Optional
`SLACK_CHANNEL_ID`	Slack Channel ID (required when using Bot)	Optional
`SLACK_WEBHOOK_URL`	Slack Incoming Webhook URL (text only, no image support)	Optional
`EMAIL_SENDER`	Sender email (e.g., `xxx@qq.com`)	Optional
`EMAIL_PASSWORD`	Email authorization code (not login password)	Optional
`EMAIL_RECEIVERS`	Receiver emails (comma-separated, leave empty to send to yourself)	Optional
`WECHAT_WEBHOOK_URL`	WeChat Work Webhook URL	Optional
`FEISHU_WEBHOOK_URL`	Feishu Webhook URL	Optional
`PUSHPLUS_TOKEN`	PushPlus Token (Get it here, Chinese push service)	Optional
`SERVERCHAN3_SENDKEY`	ServerChan v3 SendKey ((Get it here, Mobile app push notification service) )	Optional
`CUSTOM_WEBHOOK_URLS`	Custom Webhook URLs (supports DingTalk, etc., comma-separated)	Optional
`CUSTOM_WEBHOOK_BEARER_TOKEN`	Bearer token for custom webhooks (if required)	Optional
`SINGLE_STOCK_NOTIFY`	Send notification immediately after each stock	Optional
`REPORT_TYPE`	`simple`, `full`, or `brief` (Docker recommended: `full`)	Optional
`REPORT_LANGUAGE`	Report output language: `zh` (default Chinese) / `en` (English); affects prompt instructions, Markdown templates, notification fallbacks, and fixed labels in the Web report view	Optional
`ANALYSIS_DELAY`	Delay between stocks and market review (seconds)	Optional

Note: Configure at least one channel; multiple channels will all receive notifications.

Stock List Configuration

Secret Name	Description	Required
`STOCK_LIST`	Watchlist codes, e.g., `600519,AAPL,hk00700`	✅
`TAVILY_API_KEYS`	Tavily Search API (for news)	Recommended
`MINIMAX_API_KEYS`	MiniMax Coding Plan Web Search (structured search results)	Optional
`BRAVE_API_KEYS`	Brave Search API (privacy-focused, US stocks optimized)	Optional
`SERPAPI_API_KEYS`	SerpAPI Backup search	Optional
`BOCHA_API_KEYS`	Bocha Search Web Search API (Chinese search optimized, supports AI summaries, multiple keys comma-separated)	Optional
`SEARXNG_BASE_URLS`	SearXNG self-hosted instances (quota-free fallback, enable format: json in settings.yml); when empty the app auto-discovers public instances	Optional
`SEARXNG_PUBLIC_INSTANCES_ENABLED`	Auto-discover public SearXNG instances from `searx.space` when `SEARXNG_BASE_URLS` is empty (default `true`)	Optional
`TUSHARE_TOKEN`	Tushare Pro Token	Optional
`TICKFLOW_API_KEY`	TickFlow API key (CN market review index enhancement; breadth also uses TickFlow when the plan supports universe queries)	Optional
`WECHAT_MSG_TYPE`	WeChat Work message type, default `markdown`, set to `text` for plain markdown text	Optional
`AGENT_MODE`	Enable Agent strategy chat mode (internally normalized as `skill`, `true`/`false`, default `false`)	Optional
`AGENT_LITELLM_MODEL`	Optional Agent-only primary model; when empty it inherits `LITELLM_MODEL`, and bare names are normalized to `openai/<model>`	Optional
`AGENT_MAX_STEPS`	Max reasoning steps for Agent mode (default `10`)	Optional
`AGENT_SKILLS`	Comma-separated active strategy-skill ids. Leave empty to use the primary default strategy skill declared in metadata (built-in default: `bull_trend`); use `all` to activate every loaded strategy skill.	Optional
`AGENT_SKILL_DIR`	Custom strategy-skill directory (default built-in `strategies/` compatibility path)	Optional

Stock Code Format

Market	Format	Examples
A-shares	6-digit number	`600519`, `000001`, `300750`
BSE (Beijing)	8/4/92 prefix, 6-digit	`920748`, `838163`, `430047`
HK Stocks	hk + 5-digit number	`hk00700`, `hk09988`
US Stocks	1-5 uppercase letters	`AAPL`, `TSLA`, `GOOGL`

3. Enable Actions

Go to Actions tab → Click I understand my workflows, go ahead and enable them

4. Manual Test

Actions → Daily Stock Analysis → Run workflow → Select mode → Run workflow

5. Done!

The system will:

Run automatically at scheduled time (default: 18:00 Beijing Time)
Send analysis reports to all configured channels
Save reports locally

Option 2: Local Deployment

1. Clone Repository

git clone https://github.com/ZhuLinsen/daily_stock_analysis.git
cd daily_stock_analysis

2. Install Dependencies

# Create virtual environment (recommended)
python3 -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

3. Configure Environment Variables

# Copy configuration template
cp .env.example .env

# Edit .env file
nano .env  # or use any editor

Configure the following:

# AI Model (Choose one)
GEMINI_API_KEY=your_gemini_api_key_here

# Stock Watchlist (Mixed markets supported)
STOCK_LIST=600519,AAPL,hk00700

# Notification Channel (Choose at least one)
TELEGRAM_BOT_TOKEN=your_bot_token
TELEGRAM_CHAT_ID=your_chat_id

# News Search (Optional)
TAVILY_API_KEYS=your_tavily_key

4. Run

# One-time analysis
python main.py

# Scheduled mode (runs daily at 18:00)
python main.py --schedule

# Analyze specific stocks
python main.py --stocks AAPL,TSLA,GOOGL

# Market review only
python main.py --market-review

API Endpoints

Endpoint	Method	Description
`/`	GET	Configuration page
`/health`	GET	Health check
`/analysis?code=xxx`	GET	Trigger async analysis for a single stock
`/analysis/history`	GET	Query analysis history records
`/tasks`	GET	Query all task statuses
`/task?id=xxx`	GET	Query a single task status

📱 Supported Notification Channels

1. Telegram (Recommended)

Talk to @BotFather → /newbot → get Bot Token
Get Chat ID: send a message to @userinfobot
Configure:

TELEGRAM_BOT_TOKEN=123456789:ABCdefGHIjklMNOpqrsTUVwxyz
TELEGRAM_CHAT_ID=123456789

2. Discord

Webhook:

DISCORD_WEBHOOK_URL=https://discord.com/api/webhooks/xxx/yyy

Bot:

DISCORD_BOT_TOKEN=your_bot_token
DISCORD_MAIN_CHANNEL_ID=your_channel_id

3. Slack

Bot (recommended, supports image upload; takes priority when both set):

SLACK_BOT_TOKEN=xoxb-...
SLACK_CHANNEL_ID=C01234567

Webhook (text only):

SLACK_WEBHOOK_URL=https://hooks.slack.com/services/T.../B.../xxx

4. Email

EMAIL_SENDER=your_email@gmail.com
EMAIL_PASSWORD=your_app_password
EMAIL_RECEIVERS=receiver@example.com  # Optional

5. WeChat Work / Feishu

WeChat Work:

WECHAT_WEBHOOK_URL=https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=xxx

Feishu:

FEISHU_WEBHOOK_URL=https://open.feishu.cn/open-apis/bot/v2/hook/xxx

6. PushPlus

PUSHPLUS_TOKEN=your_token_here

🎨 Sample Output

Decision Dashboard Format

# 🎯 2026-01-24 Decision Dashboard

> Total **3** stocks analyzed | 🟢Buy:1 🟡Hold:1 🔴Sell:1

## 📊 Analysis Summary

🟢 **AAPL(Apple Inc.)**: Buy | Score 85 | Strong Bullish
🟡 **600519(Kweichow Moutai)**: Hold | Score 65 | Bullish
🔴 **TSLA(Tesla)**: Sell | Score 35 | Bearish

---

## 🟢 AAPL (Apple Inc.)

### 📰 Key Information
**💭 Sentiment**: Positive news on iPhone 16 sales
**📊 Earnings**: Q1 2024 earnings beat expectations

### 📌 Core Conclusion

**🟢 Buy** | Strong Bullish

> **One-sentence Decision**: Strong technical setup with positive catalyst, ideal entry point

⏰ **Time Sensitivity**: Within this week

| Position | Action |
|----------|--------|
| 🆕 **No Position** | Buy at pullback |
| 💼 **With Position** | Continue holding |

### 📊 Data Perspective

**MA Alignment**: MA5>MA10>MA20 | Bull Trend: ✅ Yes | Trend Strength: 85/100

| Price Metrics | Value |
|--------------|-------|
| Current | $185.50 |
| MA5 | $183.20 |
| MA10 | $180.50 |
| MA20 | $177.80 |
| Bias (MA5) | +1.26% ✅ Safe |
| Support | $183.20 |
| Resistance | $190.00 |

**Volume**: Ratio 1.8 (Moderate increase) | Turnover 2.3%
💡 *Volume confirms bullish momentum*

### 🎯 Action Plan

**📍 Sniper Points**

| Level Type | Price |
|-----------|-------|
| 🎯 Ideal Entry | $183-184 |
| 🔵 Secondary Entry | $180-181 |
| 🛑 Stop Loss | $177 |
| 🎊 Target | $195 |

**💰 Position Sizing**: 20-30% of portfolio
- Entry Plan: Enter in 2-3 batches
- Risk Control: Strict stop loss at $177

**✅ Checklist**

- ✅ Bull trend confirmed
- ✅ Price near MA5 support
- ✅ Volume confirms trend
- ⚠️ Monitor market volatility

---

🔧 Advanced Configuration

Environment Variables

# === Analysis Behavior ===
ANALYSIS_DELAY=10              # Delay between analysis (seconds) to avoid API rate limit
REPORT_TYPE=full               # Report type: simple/full
SINGLE_STOCK_NOTIFY=true       # Push immediately after each stock analysis

# === Schedule ===
SCHEDULE_ENABLED=true          # Enable scheduled task
SCHEDULE_TIME=18:00            # Daily run time (HH:MM, 24-hour format)
MARKET_REVIEW_ENABLED=true     # Enable market review

# === Data Source ===
TUSHARE_TOKEN=your_token       # Tushare Pro (priority data source if configured)

# === System ===
MAX_WORKERS=3                  # Concurrent threads (3 recommended to avoid blocking)
DEBUG=false                    # Enable debug logging

🧩 FastAPI Web Service (Optional)

Enable the FastAPI service for configuration management and triggering analysis when running locally.

Startup Methods

Command	Description
`python main.py --serve`	Start API service + run full analysis once
`python main.py --serve-only`	Start API service only, manually trigger analysis

URL: http://127.0.0.1:8000
API docs: http://127.0.0.1:8000/docs

Features

📝 Configuration Management - View/modify watchlist
🚀 Quick Analysis - Trigger analysis via API
📊 Real-time Progress - Analysis task status updates in real-time, supports parallel tasks
🤖 Agent Strategy Chat - Multi-turn strategy Q&A via /chat (enable with AGENT_MODE=true)
📈 Backtest Validation - Evaluate historical analysis accuracy, query direction win rate and simulated returns

API Endpoints

Endpoint	Method	Description
`/api/v1/analysis/analyze`	POST	Trigger stock analysis
`/api/v1/analysis/tasks`	GET	Query task list
`/api/v1/analysis/status/{task_id}`	GET	Query task status
`/api/v1/history`	GET	Query analysis history
`/api/v1/backtest/run`	POST	Trigger backtest
`/api/v1/backtest/results`	GET	Query backtest results (paginated)
`/api/v1/backtest/performance`	GET	Get overall backtest performance
`/api/v1/backtest/performance/{code}`	GET	Get per-stock backtest performance
`/api/v1/agent/skills`	GET	Get available built-in/custom strategy skills
`/api/v1/agent/chat/stream`	POST (SSE)	Stream multi-turn Agent strategy chat
`/api/health`	GET	Health check

Note: POST /api/v1/analysis/analyze supports only one stock when async_mode=false; batch stock_codes requires async_mode=true. The async 202 response returns a single task_id for one stock, or an accepted / duplicates summary for batch requests.

For detailed instructions, see Full Guide - API Service

📖 Documentation

☕ Support the Project

Alipay	WeChat Pay	Ko-fi

🤝 Contributing

Contributions are welcome! Please:

Fork this repository
Create your feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a Pull Request

See CONTRIBUTING.md for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⭐ Star History

Made with ❤️ by AI enthusiasts | Star ⭐ this repo if you find it useful!

⚠️ Disclaimer

This tool is for informational and educational purposes only. The analysis results are generated by AI and should not be considered as investment advice. Stock market investments carry risk, and you should:

Do your own research before making investment decisions
Understand that past performance does not guarantee future results
Only invest money you can afford to lose
Consult with a licensed financial advisor for personalized advice

The developers of this tool are not liable for any financial losses resulting from the use of this software.

🙏 Acknowledgments

AkShare - Stock data source
Google Gemini - AI analysis engine
Tavily - News search API
All contributors who helped improve this project

📞 Contact

GitHub Issues: Report bugs or request features
Discussions: Join discussions
Email: zhuls345@gmail.com

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File metadata and controls

AI Stock Analysis System

💖 Sponsors

✨ Key Features

Tech Stack & Data Sources

Built-in Trading Rules

🚀 Quick Start

Option 1: GitHub Actions (Recommended, Zero Cost)

1. Fork this repository

2. Configure Secrets

3. Enable Actions

4. Manual Test

5. Done!

Option 2: Local Deployment

1. Clone Repository

2. Install Dependencies

3. Configure Environment Variables

4. Run

API Endpoints

📱 Supported Notification Channels

1. Telegram (Recommended)

2. Discord

3. Slack

4. Email

5. WeChat Work / Feishu

6. PushPlus

🎨 Sample Output

Decision Dashboard Format

🔧 Advanced Configuration

Environment Variables

🧩 FastAPI Web Service (Optional)

Startup Methods

Features

API Endpoints

📖 Documentation

☕ Support the Project

🤝 Contributing

📄 License

⭐ Star History

⚠️ Disclaimer

🙏 Acknowledgments

📞 Contact