Data & Extraction API Endpoint Global Gateway

E-Commerce Natural Language Search Query Parser API
For Production Apps

Natural language query understanding API that converts buyer search strings into structured SQL/Elasticsearch filters.

3 Credit / Request Automatic Provider Fallback Uniform JSON Envelope
API Gateway Terminal
Gateway Active
Target Endpoint URL POST
https://test.rsflowhub.com/api/v1/ai/search-query-parse
Typical Time 1-3 s
Auth Gate X-API-Key
Credit Cost 3 Credit
Response JSON
Generative AI & Developer Definition Production Ready API

What is E-Commerce Natural Language Search Query Parser API?

E-Commerce Natural Language Search Query Parser API is a ready-to-use REST API on RSFlowHub for developers building web, mobile and AI agent applications. Send a JSON request to POST /api/v1/ai/search-query-parse with your API key; RSFlowHub runs it on a tuned AI model (with automatic fallback to a backup provider) and returns a structured JSON result, usually within 1 to 3 seconds.

Auth: X-API-Key Header
Rate Limit: 10-120 req/min by plan
Credits: 3 per call
AI Search Quick Reference
Category: Data & Extraction
Typical response: 1-3 s
Format: REST / JSON UTF-8

Code Examples

Copy-paste ready code in your preferred stack
curl-integration.sh
curl -X POST "https://test.rsflowhub.com/api/v1/ai/search-query-parse" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: rfh_your_api_key" \
  -d '{"query":"Samsung 5G phones under \u20b920,000 with 8GB RAM, highest rated first","schema":{"brand":{"type":"string"},"network":{"type":"string"},"price":{"type":"number"},"ram":{"type":"string"},"rating":{"type":"number"}},"context":{"domain":"ecommerce","default_currency":"INR"}}'
<?php

$client = new \GuzzleHttp\Client();
$response = $client->post('https://test.rsflowhub.com/api/v1/ai/search-query-parse', [
    'headers' => [
        'Content-Type' => 'application/json',
        'X-API-Key'    => 'rfh_your_api_key',
    ],
    'json' => array (
      'query' => 'Samsung 5G phones under ₹20,000 with 8GB RAM, highest rated first',
      'schema' => 
      array (
        'brand' => 
        array (
          'type' => 'string',
        ),
        'network' => 
        array (
          'type' => 'string',
        ),
        'price' => 
        array (
          'type' => 'number',
        ),
        'ram' => 
        array (
          'type' => 'string',
        ),
        'rating' => 
        array (
          'type' => 'number',
        ),
      ),
      'context' => 
      array (
        'domain' => 'ecommerce',
        'default_currency' => 'INR',
      ),
    ),
]);

echo $response->getBody();
const response = await fetch('https://test.rsflowhub.com/api/v1/ai/search-query-parse', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-Key': 'rfh_your_api_key'
  },
  body: JSON.stringify({"query":"Samsung 5G phones under \u20b920,000 with 8GB RAM, highest rated first","schema":{"brand":{"type":"string"},"network":{"type":"string"},"price":{"type":"number"},"ram":{"type":"string"},"rating":{"type":"number"}},"context":{"domain":"ecommerce","default_currency":"INR"}})
});

const data = await response.json();
console.log(data);
import requests

url = "https://test.rsflowhub.com/api/v1/ai/search-query-parse"
headers = {
    "Content-Type": "application/json",
    "X-API-Key": "rfh_your_api_key"
}
payload = {"query":"Samsung 5G phones under \u20b920,000 with 8GB RAM, highest rated first","schema":{"brand":{"type":"string"},"network":{"type":"string"},"price":{"type":"number"},"ram":{"type":"string"},"rating":{"type":"number"}},"context":{"domain":"ecommerce","default_currency":"INR"}}

response = requests.post(url, json=payload, headers=headers)
print(response.json())
Capabilities

Core Architectural Features

Attribute & Entity Extraction

Extracts brand names, model numbers, color preferences, sizes, and technical specs from raw search text.

Price & Range Normalization

Converts phrases like "under $50", "under ₹20,000", or "budget friendly" into exact numeric min/max price boundaries.

Sort Order & Intent Parsing

Detects buyer sorting intent such as "cheapest first", "highest rated", or "newest arrivals".

Query Cleansing & Typo Correction

Automatically corrects typos and normalizes product categories prior to database querying.

Practical Applications

Real-World Industry Use Cases

See how developers integrate this API endpoint into production apps.

E-Commerce Marketplace

E-Commerce Marketplace Search

Parse buyer search strings like "red Nike sneakers size 10 under $100" into exact product catalog filter queries.

Before: Samsung 5G phones under ₹20,000 with 8GB RAM, highest rated first
After: {"brand": "Samsung", "network": "5G", "max_price": 20000, "ram": "8GB", "sort_by": "rating_desc"}
Helps shoppers find the right products from natural-language searches.
PropTech

Real Estate & Property Search

Convert search strings like "3 bedroom apartment in downtown Miami with pool under $3k" into DB filters.

Before: 3 bedroom apartment in downtown Miami with pool under $3k
After: {"bedrooms": 3, "location": "downtown Miami", "max_price": 3000, "amenities": ["pool"]}
Delivers relevant property listings instantly.
TravelTech

Travel & Hotel Booking Engine

Parse natural queries like "5-star beach resort in Bali with free breakfast" into hotel availability API parameters.

Before: 5-star beach resort in Bali with free breakfast
After: {"rating": 5, "location": "Bali", "property_type": "resort", "amenities": ["beachfront", "free_breakfast"]}
Enhances user discovery experience.
Technical Comparison

Why Developers Choose E-Commerce Natural Language Search Query Parser API

Comparing RSFlowHub's specialized API gateway vs raw multi-turn LLM prompts vs legacy regex rules.

Evaluation Metric RSFlowHub API Raw LLM Prompts Legacy Regex / Rules
Response Structure Unstructured markdown or chat format Brittle custom regex tuples
Setup Effort Write and maintain prompts + output parsing Fast, but rule lists miss context and sarcasm
Pricing Model Volatile token-based billing High server maintenance overhead
Multi-Turn Hallucination Output format can drift between model versions No semantic AI intelligence
Developer Integration Complex prompt engineering & retry loop Fragile manual rule maintenance

Request Parameters

3 Fields
query string
Required

Raw natural language search query string typed by the buyer.

schema object
Optional

Optional target catalog schema definition (e.g. {"brand": {"type": "string"}, "price": {"type": "number"}}).

context object
Optional

Optional business domain context (e.g. {"domain": "ecommerce", "default_currency": "INR"}).

JSON Response Envelope

Uniform API

Every endpoint returns the same envelope: success, request_id, data.result and meta.

response.json JSON
200 OK
{
    "success": true,
    "request_id": "req_3f9a2c7e-5b1d-4e8a-9c2f-7d6e1a0b4c8d",
    "data": {
        "result": {
            "original_query": "red running shoes under 100 dollars size 10",
            "normalized_query": "red running shoes",
            "intent": "product_search",
            "language": "en",
            "filters": [
                {
                    "field": "color",
                    "value": "red"
                },
                {
                    "field": "category",
                    "value": "running shoes"
                },
                {
                    "field": "price_max",
                    "value": 100
                },
                {
                    "field": "size",
                    "value": "10"
                }
            ],
            "exclude": [],
            "sort": {
                "field": "relevance",
                "direction": "desc"
            },
            "is_ambiguous": false
        }
    },
    "meta": {
        "version": "v1",
        "timestamp": "2026-10-05T09:30:00Z"
    }
}
Format JSON
Charset UTF-8
Fallback Automatic
Rate Limit 120/min max
FAQs

Frequently Asked Questions

Everything you need to know about integrating and using E-Commerce Natural Language Search Query Parser API.

The API utilizes contextual natural language understanding to correct typos, recognize synonyms, and normalize informal terms before generating filter objects.

Yes! The API returns standard JSON filter objects that can be directly mapped to SQL WHERE clauses, Elasticsearch queries, or Algolia filters.

You can pass a default currency in the context parameter (e.g., USD, EUR, INR) so price ranges are correctly parsed into appropriate numeric thresholds.

Search Query Parser requests usually complete in 1 to 3 seconds, depending on input length and the AI model. Identical repeat requests are served from cache and return faster.

Search Query Parser API calls consume 3 base credits per request.
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