Text Filter API checks text for content safety signals and returns flagged status, score, risk level, and credits in a simple FlaqAI response. Built for free testing and stable API workflows.
API Examples
Submit Example
const response = await fetch('https://api.flaq.ai/api/v1/content/filter', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'content-filter-text-standard',
type: 'nsfw',
text: 'Sample text to check'
})
});
const result = await response.json();
console.log(result.data);
Submit Example
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/content/filter',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'content-filter-text-standard',
'type': 'nsfw',
'text': 'Sample text to check'
}
)
result = response.json()
print(result['data'])
Submit Example
curl -X POST https://api.flaq.ai/api/v1/content/filter \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "content-filter-text-standard",
"type": "nsfw",
"text": "Sample text to check"
}'
No result yet
Run a content detection request to see the structured response here.
Content Filter Text Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
Fast & Affordable Text Filter API (FlaqAI Text Safety Detection)
FlaqAI Text Filter API delivers fast, affordable text safety detection for developers building user-generated content workflows, AI apps, community platforms, and moderation pipelines. This content moderation API helps you submit text and receive structured safety signals, including flagged status, risk level, score, and credit usage in a simple response. Built for production API integration on Flaq AI, Content Filter Text provides a practical way to screen text before publishing, storing, or sending it into downstream model workflows.
Key Features of Text Filter API
- Fast Text Safety Detection: Check submitted text quickly with a streamlined content filter API designed for moderation gates, pre-publish review, and real-time product flows.
- Cost-Effective API Pricing: Use an affordable text moderation API for repeated safety checks across comments, prompts, captions, messages, and other user-generated text.
- Structured Risk Signals: Receive clear flagged status, confidence score, and risk level fields so your application can decide whether to allow, block, queue, or review content.
- Content Detection: Detect adult or unsafe text signals with a focused content safety workflow suitable for apps that need simple and reliable policy enforcement.
- Developer-Friendly Integration: Add text safety checks through a lightweight API request without building a custom classifier, moderation dashboard, or scoring infrastructure.
- Production Workflow Support: Use consistent responses for moderation queues, audit trails, prompt filtering, community safety tools, and automated trust-and-safety operations.
How to Use Text Filter API for Text Safety on Flaq AI
- Input: Natural language text submitted for safety detection, such as comments, prompts, bios, captions, messages, or moderation queue items.
- Output: Structured content filter results with flagged status, risk level, score, and credit usage through the FlaqAI text safety API.
- Detection Type: Focused text detection for applications that need practical content safety screening.
- Capabilities: Fast text moderation, risk scoring, automated safety gates, content review routing, and developer-friendly API integration for scalable moderation workflows.
Best Use Cases for Text Filter API Integration
- User-Generated Content Moderation: Screen comments, profile text, forum posts, and community submissions before they become visible in your product.
- AI Prompt Safety Checks: Review prompts before sending them into image, video, chat, or automation models to reduce unsafe generation attempts.
- Messaging & Social Apps: Add a lightweight moderation layer for chat messages, captions, replies, and social interactions with simple structured results.
- Marketplace & Listing Review: Check product descriptions, service listings, seller notes, and uploaded text before publishing them to buyers.
- Moderation Queue Automation: Route risky text to human review while letting low-risk content move through faster, improving operational efficiency.
Note Content safety results should be used as part of a broader moderation strategy. Review your own policies, handle edge cases carefully, and apply human review for sensitive decisions when needed.
Content Filter Text vs Competitors: Comparative Analysis
-
Content Filter Text vs. OpenAI Moderation API
OpenAI Moderation provides broad safety classification for text and image inputs. Content Filter Text focuses on a lightweight FlaqAI text safety workflow with simple flagged, score, and risk level outputs for teams that want affordable moderation inside Flaq AI production pipelines. -
Content Filter Text vs. Google Perspective API
Google Perspective API is well known for analyzing comment quality and toxicity signals. Content Filter Text is designed for direct content safety screening with practical detection and straightforward API responses for product moderation gates. -
Content Filter Text vs. Azure AI Content Safety
Azure AI Content Safety offers a broader enterprise safety platform for text and image moderation. Content Filter Text emphasizes fast setup, cost-effective API usage, and a focused response structure for developers who need simple text checks without managing a larger safety stack. -
Content Filter Text vs. Hive Moderation
Hive Moderation supports large-scale moderation across multiple media types and policy categories. Content Filter Text is a leaner option for teams that specifically need affordable text safety detection through a direct API workflow. -
Content Filter Text vs. Custom Text Classifiers
Custom classifiers can be tuned for specialized policy needs but require dataset preparation, model maintenance, evaluation, and deployment work. Content Filter Text provides ready-to-use safety detection for teams that want to ship moderation faster with less infrastructure overhead.