Conversational AI API Endpoint Global Gateway

AI Support Chatbots Orchestration API
For Production Apps

Deploy intelligent, RAG-grounded support chatbots with persistent session memory, persona rules, and tool actions.

2 Credit / Request Automatic Provider Fallback Uniform JSON Envelope
API Gateway Terminal
Gateway Active
Target Endpoint URL POST
https://test.rsflowhub.com/api/v1/ai/chatbots
Typical Time 1-3 s
Auth Gate X-API-Key
Credit Cost 2 Credit
Response JSON
Generative AI & Developer Definition Production Ready API

What is AI Support Chatbots Orchestration API?

AI Support Chatbots Orchestration 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/chatbots 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: 2 per call
AI Search Quick Reference
Category: Conversational AI
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/chatbots" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: rfh_your_api_key" \
  -d '{"name":"E-Commerce Assistant","mode":"support","description":"Customer support chatbot assisting buyers with orders and returns."}'
<?php

$client = new \GuzzleHttp\Client();
$response = $client->post('https://test.rsflowhub.com/api/v1/chatbots', [
    'headers' => [
        'Content-Type' => 'application/json',
        'X-API-Key'    => 'rfh_your_api_key',
    ],
    'json' => array (
      'name' => 'E-Commerce Assistant',
      'mode' => 'support',
      'description' => 'Customer support chatbot assisting buyers with orders and returns.',
    ),
]);

echo $response->getBody();
const response = await fetch('https://test.rsflowhub.com/api/v1/chatbots', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-Key': 'rfh_your_api_key'
  },
  body: JSON.stringify({"name":"E-Commerce Assistant","mode":"support","description":"Customer support chatbot assisting buyers with orders and returns."})
});

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

url = "https://test.rsflowhub.com/api/v1/chatbots"
headers = {
    "Content-Type": "application/json",
    "X-API-Key": "rfh_your_api_key"
}
payload = {"name":"E-Commerce Assistant","mode":"support","description":"Customer support chatbot assisting buyers with orders and returns."}

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

Core Architectural Features

RAG Grounded in Vector Knowledge

Automatically queries attached pgvector knowledge bases to answer customer questions grounded in your own content.

Client Action Calls & Tools

Supports tool execution e.g. checking order status, booking appointments, or generating tracking links.

Persistent Session Memory

Maintains multi-turn context across chat sessions with token-efficient rolling conversation buffers.

Custom Persona & Guardrails

Define bot tone, forbidden topics, escalation triggers, and canned fallbacks with strict system prompts.

Practical Applications

Real-World Industry Use Cases

See how developers integrate this API endpoint into production apps.

E-Commerce

24/7 E-Commerce Order Assistant

Provide real-time order tracking, return requests, and product recommendations directly on storefronts.

Before: Where is my order #US-98124 and when will it arrive?
After: Your order is out for delivery with FedEx and expected today by 4:00 PM.
Answers routine shopping questions without a human agent.
SaaS Product

SaaS Technical Onboarding Bot

Guide newly signed up developers through API key generation, webhook setup, and code snippets.

Before: How do I authenticate requests using Python?
After: Pass your key in the X-API-Key header e.g. headers={"X-API-Key": "rf_live_..."}
Helps new developers find answers on their own during onboarding.
Customer Support

Automated Helpdesk Tier-1 Triage

Collect customer details, troubleshoot common bugs, and escalate unresolved cases to live agents.

Before: I forgot my 2FA backup codes and cannot log in to my admin dashboard.
After: I have initiated a secure 2FA reset request and emailed verification instructions to your inbox.
Keeps helpdesk queues manageable during peak hours.
Technical Comparison

Why Developers Choose AI Support Chatbots Orchestration 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
message string
Required

Latest user chat message in the conversation.

session_id string
Optional

Unique conversation session ID for persistent multi-turn memory.

chatbot_id integer
Optional

Optional ID of a pre-configured Chatbot in your RSFlowHub studio.

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": {
            "message": "See the API reference for the full result schema."
        }
    },
    "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 AI Support Chatbots Orchestration API.

When a knowledge base is linked, the engine performs 768-dimensional cosine vector similarity search on Supabase pgvector to supply factual context.

Yes! The chatbot can output structured ActionCall objects enabling client applications to trigger webhooks, query databases, or execute transactions.

Sessions are stored per conversation, and a rolling context window keeps up to 20 recent turns per thread.

Yes. You can specify custom system prompts, brand persona guidelines, and strict negative constraints to prevent off-brand replies.

Standard chatbot conversational turns consume 2 base credits per interaction.
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