Multi-Turn Conversation History
Preserves multi-turn chat message arrays with user, assistant, and system roles for contextual continuity.
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Conversational text completion and multi-turn chat API for building intelligent assistants and interactive web apps.
https://test.rsflowhub.com/api/v1/ai/chat
AI Conversational Chat 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/chat 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/ai/chat" \
-H "Content-Type: application/json" \
-H "X-API-Key: rfh_your_api_key" \
-d '{"message":"What is the capital of France?","conversation":[{"role":"user","content":"Hello AI."},{"role":"assistant","content":"Hello! How can I help you?"}],"system_prompt":"You are a helpful geography expert."}'
<?php
$client = new \GuzzleHttp\Client();
$response = $client->post('https://test.rsflowhub.com/api/v1/ai/chat', [
'headers' => [
'Content-Type' => 'application/json',
'X-API-Key' => 'rfh_your_api_key',
],
'json' => array (
'message' => 'What is the capital of France?',
'conversation' =>
array (
0 =>
array (
'role' => 'user',
'content' => 'Hello AI.',
),
1 =>
array (
'role' => 'assistant',
'content' => 'Hello! How can I help you?',
),
),
'system_prompt' => 'You are a helpful geography expert.',
),
]);
echo $response->getBody();
const response = await fetch('https://test.rsflowhub.com/api/v1/ai/chat', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-Key': 'rfh_your_api_key'
},
body: JSON.stringify({"message":"What is the capital of France?","conversation":[{"role":"user","content":"Hello AI."},{"role":"assistant","content":"Hello! How can I help you?"}],"system_prompt":"You are a helpful geography expert."})
});
const data = await response.json();
console.log(data);
import requests
url = "https://test.rsflowhub.com/api/v1/ai/chat"
headers = {
"Content-Type": "application/json",
"X-API-Key": "rfh_your_api_key"
}
payload = {"message":"What is the capital of France?","conversation":[{"role":"user","content":"Hello AI."},{"role":"assistant","content":"Hello! How can I help you?"}],"system_prompt":"You are a helpful geography expert."}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
Preserves multi-turn chat message arrays with user, assistant, and system roles for contextual continuity.
Control assistant persona, business guardrails, and system grounding rules via system prompts.
High-throughput infrastructure optimized for real-time chat widgets and web application backends.
Returns structured JSON envelopes with status code, execution metrics, and clean response payload.
See how developers integrate this API endpoint into production apps.
Deploy intelligent in-app chat assistants to answer common customer inquiries 24/7.
Build interactive learning bots that guide students step-by-step through complex subjects.
Embed conversational prompts inside SaaS dashboards to help users perform complex actions.
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 1 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
The user text prompt or message to process.
conversation
array
Optional array of previous chat turns (e.g. [{"role": "user", "content": "..."}, ...]).
system_prompt
string
Custom persona, role grounding, or system instructions.
safe_mode
boolean
Enforce strict safety and content filtering (Default: true).
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": "Here are three ideas: 1) PocketPlan, 2) CampusCash, 3) SemesterSaver."
}
},
"meta": {
"version": "v1",
"timestamp": "2026-10-05T09:30:00Z"
}
}
Everything you need to know about integrating and using AI Conversational Chat API.
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