aquanet-bot-lib/README.md

A library for building aquaculture chatbots with LLM integration

# Aquanet Bot Library

A powerful library for building aquaculture chatbots with LLM integration. This library provides a comprehensive set of tools for analyzing water quality, diagnosing diseases, optimizing feeding, predicting growth, analyzing costs, and more.

## Features

- 🌊 **Water Quality Analysis**: Analyze water parameters and get recommendations
- 🦐 **Disease Diagnosis**: Identify potential diseases and get treatment suggestions
- 🍽️ **Feeding Optimization**: Optimize feeding strategies for better growth
- 📈 **Growth Prediction**: Predict growth rates based on environmental conditions
- 💰 **Cost Analysis**: Analyze operational costs and get optimization suggestions
- 🔧 **Technical Advice**: Get expert advice on farm management
- 📊 **Market Analysis**: Analyze market trends and pricing strategies
- 🌿 **Environmental Impact**: Assess environmental impact and sustainability

## Installation

```bash
npm install aquanet-bot-lib
# or
yarn add aquanet-bot-lib
# or
pnpm add aquanet-bot-lib
```

## Quick Start

```typescript
import { AquacultureService, LLMProviders } from 'aquanet-bot-lib';

// Initialize the service
const service = new AquacultureService({
  provider: LLMProviders.DEEPSEEK,
  apiKey: 'your-api-key',
  model: 'deepseek-chat',
  defaultParams: {
    temperature: 0.7,
    maxTokens: 2000,
  }
});

// Example data
const data = {
  environmentalData: {
    waterQuality: {
      temperature: 28,
      pH: 7.5,
      dissolvedOxygen: 5.2,
    }
  },
  biologicalData: {
    species: 'shrimp',
    stage: 'juvenile',
  },
  metadata: {
    farmId: 'farm-123',
    pondId: 'pond-456',
    timestamp: new Date(),
    source: 'sensor'
  }
};

// Analyze water quality
const result = await service.analyzeWaterQuality(data);
console.log(result);

// Get disease diagnosis
const diagnosis = await service.diagnoseDiseases(data);
console.log(diagnosis);
```

## API Reference

### AquacultureService

The main class for interacting with the aquaculture analysis features.

#### Constructor

```typescript
constructor(config: LLMConfig)
```

- `config`: Configuration object for the LLM provider
  - `provider`: LLM provider (currently supports DEEPSEEK)
  - `apiKey`: API key for the provider
  - `model`: Model name to use
  - `defaultParams`: Default parameters for the model

#### Methods

- `analyzeWaterQuality(data: AquacultureData): Promise<string>`
- `diagnoseDiseases(data: AquacultureData): Promise<string>`
- `optimizeFeeding(data: AquacultureData): Promise<string>`
- `predictGrowth(data: AquacultureData): Promise<string>`
- `analyzeCosts(data: AquacultureData): Promise<string>`
- `getTechnicalAdvice(data: AquacultureData): Promise<string>`
- `analyzeMarket(data: AquacultureData): Promise<string>`
- `assessEnvironmentalImpact(data: AquacultureData): Promise<string>`

### Data Types

```typescript
interface AquacultureData {
  environmentalData: {
    waterQuality: {
      temperature: number;
      pH: number;
      dissolvedOxygen: number;
      [key: string]: any;
    };
    [key: string]: any;
  };
  biologicalData: {
    species: string;
    stage: string;
    [key: string]: any;
  };
  metadata: {
    farmId: string;
    pondId: string;
    timestamp: Date;
    source: string;
    [key: string]: any;
  };
  [key: string]: any;
}
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

MIT License - see the [LICENSE](LICENSE) file for details.