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aquanet-bot-lib

v0.2.1

Published

A library for building aquaculture chatbots with LLM integration

Downloads

32

Readme

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

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

Quick Start

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

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

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 file for details.