Nutrline AI API

const axios = require('axios');
const CircuitBreaker = require('opossum');

class NutrlineAIClient {
  constructor(config = {}) {
    this.baseURL = 'https://api.nutrline.space/v1';
    this.timeout = config.timeout || 30000;
    this.circuitBreaker = new CircuitBreaker(this._makeRequest.bind(this), {
      timeout: this.timeout,
      errorThresholdPercentage: 50,
      resetTimeout: 30000
    });
  }

  async _makeRequest(payload) {
    const response = await axios.post(`${this.baseURL}/learn/data`, payload, {
      timeout: this.timeout,
      headers: { 'Content-Type': 'application/json' }
    });
    return response.data;
  }

  async query(userQuery, userId = 'anonymous', firstInteraction = false) {
    try {
      return await this.circuitBreaker.fire({
        user: userId,
        query: userQuery,
        firstInteraction
      });
    } catch (error) {
      throw new Error(`API Error: ${error.message}`);
    }
  }
}

module.exports = NutrlineAIClient;

import requests
import json
import logging
from typing import Dict, Optional
from dataclasses import dataclass
from datetime import datetime

@dataclass
class APIResponse:
    status: str
    data: Dict
    meta: Dict
    timestamp: datetime

class NutrlineAIClient:
    def __init__(self, base_url: str = "https://api.nutrline.space/v1"):
        self.base_url = base_url
        self.session = requests.Session()
        self.session.headers.update({'Content-Type': 'application/json'})
        
    def query(self, query: str, user_id: str = "researcher", 
              first_interaction: bool = False) -> APIResponse:
        """
        Execute intelligent query processing with academic research optimization
        """
        payload = {
            "user": user_id,
            "query": query,
            "firstInteraction": first_interaction
        }
        
        try:
            response = self.session.post(
                f"{self.base_url}/learn/data", 
                json=payload, 
                timeout=60
            )
            response.raise_for_status()
            
            data = response.json()
            return APIResponse(
                status=data['status'],
                data=data['data'],
                meta=data['meta'],
                timestamp=datetime.now()
            )
            
        except requests.RequestException as e:
            logging.error(f"API request failed: {e}")
            raise

#!/bin/bash
# Production-grade API request with comprehensive error handling

ENDPOINT="https://api.nutrline.space/v1/learn/data"
USER_ID="academic_research_$(date +%s)"
QUERY="Implement advanced neural architecture search algorithms for automated machine learning"

curl -X POST "$ENDPOINT" \
  -H "Content-Type: application/json" \
  -H "User-Agent: NutrlineAI-Client/1.0" \
  --connect-timeout 30 \
  --max-time 60 \
  --retry 3 \
  --retry-delay 5 \
  --fail \
  -d '{
    "user": "'$USER_ID'",
    "query": "'$QUERY'",
    "firstInteraction": true
  }' | jq -r '.data.reply'

{
  "status": "error",
  "message": "Request validation failed: missing required parameter 'query'",
  "code": "VALIDATION_ERROR",
  "details": {
    "parameter": "query",
    "expected": "string",
    "received": "null"
  },
  "timestamp": "2025-09-15T16:24:00.000Z"
}