82trust / 100
Sentiment Analyze
by NetIntel in AI models & inference
x402 APIPassing, checked 54 min ago
Sentiment analysis API — analyze sentiment of text and get a text sentiment score in one call: classifies positive / negative / neutral / mixed polarity with a -1 to +1 sentiment score, plus emotion detection in text (joy, anger, sadness, fear, surprise, disgust, trust, anticipation). Aspect-based sentiment and opinion mining for customer feedback analysis — analyze reviews, support tickets, social posts, chat messages. Via Claude Haiku.
POST https://netintel.dev/sentiment/analyze
Last 30 days
All checks passedSome failedAll failedNot checked
- Uptime
- 100%
- Response time
- 187 ms typical, 187 ms slowest 5%
- Last check
- 54 min ago
- Next check
- any minute now
How to call it
# See the payment challenge (nothing is charged)
curl -i -X POST "https://netintel.dev/sentiment/analyze" \
-H "content-type: application/json" \
-d '{"aspects":["food","service","price"],"text":"The food was absolutely delicious and the staff were so friendly, but the prices were a bit steep."}'import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { ExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";
const client = new x402Client().register(
"eip155:8453",
new ExactEvmScheme(privateKeyToAccount(process.env.AGENT_KEY)),
);
const pay = wrapFetchWithPayment(fetch, client);
// Not sure it's safe to pay? Preflight it first for $0.005:
// GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fnetintel.dev%2Fsentiment%2Fanalyze
const res = await pay("https://netintel.dev/sentiment/analyze", {
method: "POST",
headers: { "content-type": "application/json" },
body: JSON.stringify({"aspects":["food","service","price"],"text":"The food was absolutely delicious and the staff were so friendly, but the prices were a bit steep."}),
});
console.log(await res.json());Example input
{
"aspects": [
"food",
"service",
"price"
],
"text": "The food was absolutely delicious and the staff were so friendly, but the prices were a bit steep."
}Example output
{
"aspects": {
"food": {
"polarity": "positive",
"score": 0.9
},
"price": {
"polarity": "negative",
"score": -0.4
},
"service": {
"polarity": "positive",
"score": 0.8
}
},
"confidence": 0.86,
"emotions": [
"joy",
"trust"
],
"findings": [],
"grade": "A",
"polarity": "mixed",
"score": 0.2,
"service_score": 100
}Security scan
- No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.
Recent checks
| When | Result | HTTP | Time | Price |
|---|---|---|---|---|
| 54 min ago | Passed | 402 | 187 ms | $0.002 |
| 6 h ago | Passed | 402 | 196 ms | $0.002 |