daily-stock-analysis

$27

Method 1: GitHub Actions (Recommended, Zero Cost)

Step 1: Fork the repository

https://github.com/ZhuLinsen/daily_stock_analysis

Step 2: Configure Secrets (Settings → Secrets and variables → Actions)

Required — at least one LLM key:

GEMINI_API_KEY        # Google AI Studio (free tier available)

OPENAI_API_KEY        # OpenAI or compatible (DeepSeek, Qwen, etc.)

OPENAI_BASE_URL       # e.g. https://api.deepseek.com/v1

OPENAI_MODEL          # e.g. deepseek-chat, gpt-4o

AIHUBMIX_KEY          # AIHubMix (recommended, covers Gemini+GPT+Claude+DeepSeek)

ANTHROPIC_API_KEY     # Claude

Required — stock list:

STOCKS                # e.g. 600519,300750,AAPL,TSLA,00700.HK

Required — at least one notification channel:

TELEGRAM_BOT_TOKEN

TELEGRAM_CHAT_ID

FEISHU_WEBHOOK_URL

WECHAT_WEBHOOK_URL

EMAIL_SENDER / EMAIL_PASSWORD / EMAIL_RECEIVERS

DISCORD_WEBHOOK_URL

Step 3: Trigger manually or wait for cron

Go to Actions → stock_analysis → Run workflow

Method 2: Local / Docker

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

cd daily_stock_analysis

cp .env.example .env

# Edit .env with your keys

pip install -r requirements.txt

python main.py

Docker:

docker build -t stock-analysis .

docker run --env-file .env stock-analysis

Docker Compose:

docker-compose up -d

Configuration

.env File (Local)

# LLM - pick one or more

GEMINI_API_KEY=your_gemini_key

OPENAI_API_KEY=your_openai_key

OPENAI_BASE_URL=https://api.deepseek.com/v1

OPENAI_MODEL=deepseek-chat

AIHUBMIX_KEY=your_aihubmix_key

# Stock list (comma-separated)

STOCKS=600519,300750,AAPL,TSLA,00700.HK

# Notification

TELEGRAM_BOT_TOKEN=your_bot_token

TELEGRAM_CHAT_ID=your_chat_id

# Optional settings

REPORT_TYPE=full           # simple | full | brief

ANALYSIS_DELAY=10          # seconds between stocks (avoid rate limiting)

MAX_WORKERS=3              # concurrent analysis threads

SINGLE_STOCK_NOTIFY=false  # push each stock immediately when done

NEWS_MAX_AGE_DAYS=3        # ignore news older than N days

Multi-Channel LLM (Advanced)

LLM_CHANNELS=gemini,deepseek,claude

LLM_GEMINI_PROTOCOL=google

LLM_GEMINI_API_KEY=your_key

LLM_GEMINI_MODELS=gemini-2.0-flash,gemini-1.5-pro

LLM_GEMINI_ENABLED=true

LLM_DEEPSEEK_PROTOCOL=openai

LLM_DEEPSEEK_BASE_URL=https://api.deepseek.com/v1

LLM_DEEPSEEK_API_KEY=your_key

LLM_DEEPSEEK_MODELS=deepseek-chat

LLM_DEEPSEEK_ENABLED=true

Stock Grouping (Send Different Stocks to Different Emails)

STOCK_GROUP_1=600519,300750,000858

EMAIL_GROUP_1=investor1@example.com

STOCK_GROUP_2=AAPL,TSLA,NVDA

EMAIL_GROUP_2=investor2@example.com

Market Review Mode

MARKET_REVIEW=cn      # cn | us | both

# cn = A-share three-phase review strategy

# us = US Regime Strategy (risk-on/neutral/risk-off)

# both = both markets

Key Commands (CLI)

# Run full analysis immediately

python main.py

# Analyze specific stocks only

STOCKS=600519,AAPL python main.py

# Run web dashboard

python web_app.py

# Access at http://localhost:5000

# Run with Docker (env file)

docker run --env-file .env stock-analysis python main.py

# Run schedule mode (waits for cron, then runs)

SCHEDULE_RUN_IMMEDIATELY=true python main.py

GitHub Actions Workflow

The workflow file .github/workflows/stock_analysis.yml runs on schedule:

# Default schedule - customize in the workflow file

on:

  schedule:

    - cron: '30 1 * * 1-5'   # 9:30 AM CST (UTC+8) weekdays

  workflow_dispatch:          # manual trigger

To change schedule: Edit .github/workflows/stock_analysis.yml cron expression.

To add secrets via GitHub CLI:

gh secret set GEMINI_API_KEY --body "$GEMINI_API_KEY"

gh secret set STOCKS --body "600519,300750,AAPL,TSLA"

gh secret set TELEGRAM_BOT_TOKEN --body "$TG_TOKEN"

gh secret set TELEGRAM_CHAT_ID --body "$TG_CHAT_ID"

Code Examples

Programmatic Analysis (Python)

# Run analysis for specific stocks programmatically

import asyncio

from analyzer import StockAnalyzer

async def analyze():

    analyzer = StockAnalyzer()

    # Analyze a single A-share stock

    result = await analyzer.analyze_stock("600519")  # Moutai

    print(result['conclusion'])

    print(result['buy_price'])

    print(result['stop_loss'])

    print(result['target_price'])

asyncio.run(analyze())

Custom Notification Integration

from notifier import NotificationManager

notifier = NotificationManager()

# Send to Telegram

await notifier.send_telegram(

    token=os.environ['TELEGRAM_BOT_TOKEN'],

    chat_id=os.environ['TELEGRAM_CHAT_ID'],

    message="📈 Analysis complete\n600519: BUY at 1680, SL: 1620, TP: 1800"

)

# Send to Feishu webhook

await notifier.send_feishu(

    webhook_url=os.environ['FEISHU_WEBHOOK_URL'],

    content=analysis_report

)

Using the Agent API

import requests

# Ask the stock agent a strategy question

response = requests.post('http://localhost:5000/api/agent/chat', json={

    "message": "600519现在适合买入吗？用均线金叉策略分析",

    "stock_code": "600519",

    "strategy": "ma_crossover"  # ma_crossover, elliott_wave, chan_theory, etc.

})

print(response.json()['reply'])

Backtest Analysis Accuracy

import requests

# Trigger backtest for a stock

response = requests.post('http://localhost:5000/api/backtest', json={

    "stock_code": "600519",

    "days": 30  # evaluate last 30 days of AI predictions

})

result = response.json()

print(f"Direction accuracy: {result['direction_accuracy']}%")

print(f"Take-profit hit rate: {result['tp_hit_rate']}%")

print(f"Stop-loss hit rate: {result['sl_hit_rate']}%")

Import Stocks from Image (Vision LLM)

import requests

# Upload screenshot of stock list for AI extraction

with open('watchlist_screenshot.png', 'rb') as f:

    response = requests.post(

        'http://localhost:5000/api/stocks/import/image',

        files={'image': f}

    )

stocks = response.json()['extracted_stocks']

# Returns: [{"code": "600519", "name": "贵州茅台", "confidence": 0.98}, ...]

Web Dashboard Features

Start the web app:

python web_app.py

Route

Feature

/

Today's analysis dashboard

/portfolio

Holdings management, P&L tracking

/history

Past analysis reports (bulk delete supported)

/backtest

AI prediction accuracy backtest

/agent

Multi-turn strategy Q&A

/settings

LLM channels, notification config

/import

Import stocks from image/CSV/clipboard

Supported Stock Formats

# A-shares (6-digit code)

600519    # 贵州茅台

300750    # 宁德时代

000858    # 五粮液

# HK stocks (5-digit + .HK)

00700.HK  # 腾讯控股

09988.HK  # 阿里巴巴

# US stocks (ticker)

AAPL

TSLA

NVDA

# US indices

SPX       # S&P 500

DJI       # Dow Jones

IXIC      # NASDAQ

Built-in Trading Rules

Rule

Config

No chasing highs

DEVIATION_THRESHOLD=5 (%, auto-relaxed for strong trend)

Trend trading

MA5 > MA10 > MA20 bullish alignment required

Precise targets

Buy price, stop-loss, take-profit per stock

News freshness

NEWS_MAX_AGE_DAYS=3 (skip stale news)

Checklist

Each condition marked: ✅ Satisfied / ⚠️ Caution / ❌ Not Met

Troubleshooting

Analysis runs but no push received:

# Check notification config

python -c "from notifier import test_all_channels; test_all_channels()"

# Verify secrets are set (GitHub Actions)

gh secret list

LLM API errors / rate limiting:

ANALYSIS_DELAY=15        # increase delay between stocks

MAX_WORKERS=1            # reduce concurrency

LITELLM_FALLBACK_MODELS=gemini-1.5-flash,deepseek-chat  # add fallbacks

AkShare data fetch fails (A-shares):

pip install akshare --upgrade

# A-share data requires Chinese network or proxy

YFinance US stock data issues:

pip install yfinance --upgrade

# US stocks use YFinance exclusively for consistency

GitHub Actions not triggering:

• Check Actions are enabled: Settings → Actions → General → Allow all actions

• Verify cron syntax at crontab.guru

• Check workflow file exists: .github/workflows/stock_analysis.yml

Web auth issues (admin password):

# If auth was disabled and re-enabled, current password required

# Reset via environment variable

WEB_ADMIN_PASSWORD=new_password

Multi-worker deployment auth state:

# Auth toggle only applies to current process

# Must restart all workers to sync state

docker-compose restart

Report Types

REPORT_TYPE=simple   # Concise: conclusion + key prices only

REPORT_TYPE=full     # Complete: all technical + fundamental + news analysis

REPORT_TYPE=brief    # 3-5 sentence summary

Full report includes:

• 一句话核心结论 (one-line core conclusion)

• 技术面分析 (technical: MA alignment, chip distribution)

• 基本面 (valuation, growth, earnings, institutional holdings)

• 舆情情报 (news sentiment, social media — US stocks)

• 精确买卖点位 (precise entry/exit levels)

• 操作检查清单 (action checklist)

• 板块涨跌榜 (sector performance boards)

LLM Priority Order

Gemini → Anthropic → OpenAI/AIHubMix/Compatible

AIHubMix is recommended for single-key access to all major models without VPN:

AIHUBMIX_KEY=$AIHUBMIX_KEY  # covers Gemini, GPT, Claude, DeepSeek

# No OPENAI_BASE_URL needed — auto-configured