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

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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

WhenResultHTTPTimePrice
54 min agoPassed402187 ms$0.002
6 h agoPassed402196 ms$0.002