RAG Grounded in Vector Knowledge
Automatically queries attached pgvector knowledge bases to answer customer questions grounded in your own content.
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Deploy intelligent, RAG-grounded support chatbots with persistent session memory, persona rules, and tool actions.
https://test.rsflowhub.com/api/v1/ai/chatbots
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.
X-API-Key Header
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())
Automatically queries attached pgvector knowledge bases to answer customer questions grounded in your own content.
Supports tool execution e.g. checking order status, booking appointments, or generating tracking links.
Maintains multi-turn context across chat sessions with token-efficient rolling conversation buffers.
Define bot tone, forbidden topics, escalation triggers, and canned fallbacks with strict system prompts.
See how developers integrate this API endpoint into production apps.
Provide real-time order tracking, return requests, and product recommendations directly on storefronts.
Guide newly signed up developers through API key generation, webhook setup, and code snippets.
Collect customer details, troubleshoot common bugs, and escalate unresolved cases to live agents.
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 | Validated JSON envelope | Unstructured markdown or chat format | Brittle custom regex tuples |
| Setup Effort | One POST request, no prompts | Write and maintain prompts + output parsing | Fast, but rule lists miss context and sarcasm |
| Pricing Model | Flat 2 credit/request | Volatile token-based billing | High server maintenance overhead |
| Multi-Turn Hallucination | Zero (Deterministic validators) | Output format can drift between model versions | No semantic AI intelligence |
| Developer Integration | 3 lines cURL, PHP, JS, Python | Complex prompt engineering & retry loop | Fragile manual rule maintenance |
message
string
Latest user chat message in the conversation.
session_id
string
Unique conversation session ID for persistent multi-turn memory.
chatbot_id
integer
Optional ID of a pre-configured Chatbot in your RSFlowHub studio.
Every endpoint returns the same envelope: success, request_id, data.result and meta.
{
"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"
}
}
Everything you need to know about integrating and using AI Support Chatbots Orchestration API.
Get started in minutes with free welcome credits and instant API key generation.
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💡 Need a custom endpoint? Tell us what you need and we will scope it with you.