Quickstart

(coming soon...)

Zara is an autonomous AI agent that provides trading insights and interactive experiences through a modular framework. This guide will help you get started with setting up and using Zara.

Prerequisites

• Python 3.9+

• Docker (optional)

Installation

1. Clone Repository

will be open-source soon.

git clone https://github.com/z-agent/zara.git
cd zara

2. Environment Setup

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
.\venv\Scripts\activate   # Windows

# Install dependencies
pip install -r requirements.txt

3. Configuration

# Copy example env file
cp .env.example .env

# Edit .env with your credentials
SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key
OPENAI_API_KEY=your_openai_key
TELEGRAM_BOT_TOKEN=your_telegram_token

4. Database Setup

# Create database

Basic Usage

1. Start Services

# run with a single command

2. API Endpoints

Market Analysis

# Analyze token
/api/analyze

Content Generation

# Generate insight
/api/generate

Social Engagement

# Post tweet
/api/tweet

Tasks

1. Token Analysis

from src.services.crypto_service import CryptoService

async def analyze_token():
    service = CryptoService()
    analysis = await service.analyze_token("ETH")
    print(analysis)

2. Generate Content

from src.services.content_generator import ContentGenerator

async def generate_content():
    generator = ContentGenerator()
    content = await generator.generate_insight(analysis_id="123")
    print(content)

3. Manage Tweets

from src.services.twitter_manager import TwitterManager

async def manage_tweets():
    manager = TwitterManager()
    tweets = await manager.get_mentions()
    for tweet in tweets:
        await manager.process_tweet(tweet)

Docker Deployment

1. Build Image

# Build Docker image
docker build -t zara:latest .

2. Run Container

# Run with Docker Compose
docker-compose up -d

3. Monitor Logs

# View logs
docker-compose logs -f

Cloud Run Deployment

1. Setup

# Configure gcloud
gcloud init
gcloud auth configure-docker

2. Deploy

# Deploy to Cloud Run
gcloud run deploy zara-api \
  --source . \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

Development

1. Code Structure

zara/
├── src/
│   ├── main.py           # Main application
│   ├── routes/           # API routes
│   ├── services/         # Business logic
│   ├── models/           # Data models
│   └── utils/            # Utilities
├── tests/                # Test files
├── scripts/              # Helper scripts
└── docs/                 # Documentation

2. Running Tests

# Run tests
pytest

# Run with coverage
pytest --cov=src

3. Code Style

# Format code
black src/

# Check types
mypy src/

# Lint code
flake8 src/

Troubleshooting

1. Common Issues

Database Connection

Best Practices

1. Code

• Use type hints

• Write tests

• Document functions

• Handle errors

• Follow PEP 8

2. Deployment

• Use version control

• Monitor resources

• Backup data

• Update dependencies

• Review security

3. Operations

• Check logs regularly

• Monitor performance

• Update documentation

• Review errors

• Test backups

Next Steps

1. Explore advanced features

2. Add custom indicators

3. Enhance analysis

4. Contribute code

5. Join community

Getting Help

• Documentation: /docs

• Issues: GitHub Issues

• Community: Discord

Resources

• API Reference: /docs/api

• Architecture: /docs/architecture

• Contributing: /docs/contributing