FAQ Collections
Create and manage collections of FAQ items for semantic search matching.
/api/v1/ai/faq-collections
RAG synthesis and semantic vector search APIs with source citations to reduce hallucinations.
{
"collection_id": 12,
"query": "how long does a refund take?"
}
{
"data": {
"result": {
"matches": [
{
"question": "How long do refunds take?",
"answer": "Refunds are processed within 5-7 business days after approval.",
"score": 0.94
}
]
}
}
}
2 credits per call. Each one has its own page with parameters, code and examples.
Create and manage collections of FAQ items for semantic search matching.
/api/v1/ai/faq-collections
Match a search query semantically against an FAQ collection using a hybrid vector-similarity algorithm.
/api/v1/ai/faq-match
RSFlowHub RAG & Knowledge Base APIs deliver grounded information retrieval and semantic vector search over corporate documents and FAQ collections. Combining dense embeddings with source citations to reduce hallucinations, these endpoints synthesize answers with explicit citations (e.g., [Doc 1, Page 3]) so users can verify every claim.
X-API-Key headerA real request to POST /api/v1/ai/faq-match. Every API in this category works the same way.
curl -X POST "https://rsflowhub.com/api/v1/ai/faq-match" \
-H "X-API-Key: rfh_your_api_key" \
-H "Content-Type: application/json" \
-d '{"collection_id":12,"query":"how long does a refund take?"}'
<?php
$response = (new \GuzzleHttp\Client())->post('https://rsflowhub.com/api/v1/ai/faq-match', [
'headers' => ['X-API-Key' => 'rfh_your_api_key'],
'json' => json_decode('{"collection_id":12,"query":"how long does a refund take?"}', true),
]);
print_r(json_decode($response->getBody(), true));
const response = await fetch("https://rsflowhub.com/api/v1/ai/faq-match", {
method: "POST",
headers: {
"X-API-Key": "rfh_your_api_key",
"Content-Type": "application/json"
},
body: JSON.stringify({"collection_id":12,"query":"how long does a refund take?"})
});
console.log(await response.json());
import requests
response = requests.post(
"https://rsflowhub.com/api/v1/ai/faq-match",
headers={"X-API-Key": "rfh_your_api_key"},
json={"collection_id":12,"query":"how long does a refund take?"},
)
print(response.json())
{
"success": true,
"request_id": "req_3f9a2c7e-5b1d-4e8a-9c2f-7d6e1a0b4c8d",
"data": {
"result": {
"matches": [
{
"question": "How long do refunds take?",
"answer": "Refunds are processed within 5-7 business days after approval.",
"score": 0.94
}
]
}
},
"meta": {
"version": "v1",
"timestamp": "2026-10-05T09:30:00Z"
}
}
Matches user questions against FAQ databases by sentence intent and concept rather than exact keyword strings.
Appends explicit source citations (e.g. [Doc 1, Page 4]) to every generated answer in RAG pipelines.
Constrains generated answers strictly to facts present in provided context chunks.
Typical pipelines built with RAG, FAQ & Knowledge Base APIs.
Match customer questions against your existing FAQ database semantically, resolving inquiries instantly without human intervention.
Search across API specs, markdown files, and code repositories to answer technical developer questions with source line references.
Allow employees to query internal employee handbooks, compliance checklists, and benefits policies securely with zero data training risk.
How the RAG, FAQ & Knowledge Base APIs compare with calling a provider directly or running your own models.
| Topic | RSFlowHub | Provider SDK | Self-hosted |
|---|---|---|---|
| Anti-Hallucination | Strict Context Grounding Guardrails | Prone to Plausible Hallucinations | Requires Complex Eval Setup |
| Vector Indexing | Managed pgvector Pipeline | Requires Separate Pinecone/Weaviate | Manual Milvus/Chroma Cluster |
| Search Latency | Hybrid Vector + Keyword Search | Multiple API Network Roundtrips | Depends on Dedicated Memory |
Free plan with 100 credits/month + 1,000 bonus credits when you sign in before 23 Nov. One key works for every API in every category.
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