RAG Grounded in Vector Knowledge
Automatically queries attached pgvector knowledge bases to answer complex customer questions without hallucinations.
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Deploy intelligent, RAG-grounded support chatbots with persistent session memory, persona rules, and tool actions.
https://www.rsflowhub.com/api/v1/ai/chatbots
AI Support Chatbots Orchestration 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/chatbots, executes sub-180ms inference across global edge regions, and returns deterministic, type-safe JSON envelopes without unpredictable hallucination.
X-API-Key Header
curl -X POST "https://www.rsflowhub.com/api/v1/chatbots" \
-H "Content-Type: application/json" \
-H "X-API-Key: rsh_live_your_api_key_here" \
-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://www.rsflowhub.com/api/v1/chatbots', [
'headers' => [
'Content-Type' => 'application/json',
'X-API-Key' => 'rsh_live_your_api_key_here',
],
'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://www.rsflowhub.com/api/v1/chatbots', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-Key': 'rsh_live_your_api_key_here'
},
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://www.rsflowhub.com/api/v1/chatbots"
headers = {
"Content-Type": "application/json",
"X-API-Key": "rsh_live_your_api_key_here"
}
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 complex customer questions without hallucinations.
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 | 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 2 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 |
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.
All API endpoints return uniform JSON envelopes with status code, execution metadata, and data payload.
{
"status": "success",
"code": 200,
"message": "Processed successfully",
"data": {
"result": "Sample output result"
},
"meta": {
"credits_deducted": 2,
"execution_time_ms": 142
}
}
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.
⚡ 24h Bug Fix SLA: If you face any issues, submit them & we fix them within 24 hours.
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