Conversational AI API Endpoint Global Gateway

Semantic Knowledge Base Vector Search API
For Production Apps

Sub-200ms semantic knowledge base search API delivering context-aware document chunk retrieval for RAG workflows.

Try Live Demo Get Free Key Docs
3 Credit / Request 99.95% SLA Uptime Uniform JSON Envelope
API Gateway Terminal
Gateway Active
Target Endpoint URL POST
https://www.rsflowhub.com/api/v1/ai/kb-search
Avg Latency < 150ms
Auth Gate X-API-Key
Credit Cost 3 Credit
Uptime SLA 99.95%
Generative AI & Developer Definition Production Ready API

What is Semantic Knowledge Base Vector Search API?

Semantic Knowledge Base Vector Search API is a production-ready cloud REST API endpoint hosted on RSFlowHub designed for developers building high-throughput web, mobile, and AI agent applications. It accepts structured JSON payloads via POST /api/v1/knowledge-bases, executes sub-180ms inference across global edge regions, and returns deterministic, type-safe JSON envelopes without unpredictable hallucination.

Auth: X-API-Key Header
Rate Limit: 600 req/min
Credits: 3 per call
AI Search Quick Reference
Category: Conversational AI
Latency: sub-180ms p95
Format: REST / JSON UTF-8

Code Examples

Copy-paste ready code in your preferred stack
curl-integration.sh 
curl -X POST "https://www.rsflowhub.com/api/v1/knowledge-bases" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: rsh_live_your_api_key_here" \
  -d '{"name":"Customer Support KB","description":"Knowledge base containing product FAQs, return policies, and documentation."}'
<?php

$client = new \GuzzleHttp\Client();
$response = $client->post('https://www.rsflowhub.com/api/v1/knowledge-bases', [
    'headers' => [
        'Content-Type' => 'application/json',
        'X-API-Key'    => 'rsh_live_your_api_key_here',
    ],
    'json' => array (
      'name' => 'Customer Support KB',
      'description' => 'Knowledge base containing product FAQs, return policies, and documentation.',
    ),
]);

echo $response->getBody();
const response = await fetch('https://www.rsflowhub.com/api/v1/knowledge-bases', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-Key': 'rsh_live_your_api_key_here'
  },
  body: JSON.stringify({"name":"Customer Support KB","description":"Knowledge base containing product FAQs, return policies, and documentation."})
});

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

url = "https://www.rsflowhub.com/api/v1/knowledge-bases"
headers = {
    "Content-Type": "application/json",
    "X-API-Key": "rsh_live_your_api_key_here"
}
payload = {"name":"Customer Support KB","description":"Knowledge base containing product FAQs, return policies, and documentation."}

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

Core Architectural Features

Context-Aware Semantic Retrieval

Searches unstructured documentation by intent, technical concept, and context rather than exact keyword string matching.

Hybrid Keyword & Dense Vector Reranking

Combines lexical BM25 keyword matching with dense vector embeddings for maximum search precision.

Document Chunk & Citation Snippets

Returns exact relevant text snippets, section headings, and document metadata citations.

Multi-Document Indexing Support

Supports searching across technical API documentation, user manuals, and internal SOP procedures.

Practical Applications

Real-World Industry Use Cases

See how developers integrate this API endpoint into production apps.

Developer & Enterprise Portals

Enterprise Developer Documentation Search

Power instant intelligent search across thousands of technical API documentation pages and code examples.

Before: How to handle credit pre-authorization locks in PHP SDK?
After: {"snippets": [{"title": "Credit Authorization Locks", "content": "Use the X-API-Key header to pre-authorize credits...", "score": 0.94}]}
Saves developers 15+ minutes when finding complex API integration code snippets.
RAG & Support Bots

AI Support Agent Context Retrieval (RAG)

Retrieve relevant technical documentation chunks to feed LLM prompt context for grounded chatbot responses.

Before: What is the maximum payload size for file upload?
After: {"snippets": [{"file": "limits.md", "content": "Maximum file payload size is 50MB per request."}]}
Eliminates AI chatbot hallucinations by grounding answers in real documentation.
Corporate Intranets

Internal Staff HR & Policy Search

Enable company employees to search internal HR policies, IT security rules, and expense guidelines instantly.

Before: What is the annual gym reimbursement policy limit?
After: {"snippets": [{"title": "Employee Benefits Policy", "content": "Full-time employees receive up to $500 annual gym reimbursement."}]}
Reduces HR and IT helpdesk inquiry volume.
Technical Comparison

Why Developers Choose Semantic Knowledge Base Vector Search 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 Strict typed JSON envelope Unstructured markdown or chat format Brittle custom regex tuples
Latency Performance 120ms - 220ms edge cached 1,500ms - 4,000ms streaming 50ms (Zero semantic capability)
Pricing Model Flat 3 credit/request Volatile token-based billing High server maintenance overhead
Multi-Turn Hallucination Zero (Deterministic validators) Frequent schema drift & hallucinations No semantic AI intelligence
Developer Integration 3 lines cURL, PHP, JS, Python Complex prompt engineering & retry loop Fragile manual rule maintenance

Request Parameters

4 Fields
query string
Required

User search query or technical question to retrieve knowledge snippets for.

documents array
Required

Array of document objects or text chunks to search over.

top_k integer
Optional

Number of top relevant document snippets to retrieve (Default: 5).

filter_metadata object
Optional

Optional metadata filter key-value pairs (e.g. {"category": "billing"}).

JSON Response Envelope

Uniform API

All API endpoints return uniform JSON envelopes with status code, execution metadata, and data payload.

envelope.json JSON
200 OK 142ms 
{
    "status": "success",
    "code": 200,
    "message": "Processed successfully",
    "data": {
        "result": "Sample output result"
    },
    "meta": {
        "credits_deducted": 3,
        "execution_time_ms": 142
    }
}
Format JSON
Charset UTF-8
SLA Uptime 99.95%
Rate Limit 600/min
FAQs

Frequently Asked Questions

Everything you need to know about integrating and using Semantic Knowledge Base Vector Search API.

The API accepts raw text chunks, markdown files, JSON document objects, and extracted PDF text arrays.

Hybrid reranking evaluates both exact technical keyword matches (e.g., error codes, function names) and broad semantic intent.

Yes! Passing filter_metadata allows you to narrow searches to specific document categories, products, or access tiers.

Knowledge Base Search requests execute sub-200ms on average over our multi-region gateway.

Standard Knowledge Base Search API calls consume 3 base credits per request.
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