Sentiment Analysis

1import requests
2from openai import OpenAI
3
4# 1. Extract clean text from review page
5response = requests.post(
6    "https://api.sentienceapi.com/v1/observe",
7    headers={"Authorization": "Bearer YOUR_API_KEY"},
8    json={
9        "url": "https://www.amazon.com/product-reviews/B08N5WRWNW",
10        "mode": "read",
11        "format": "text"  # Plain text for cleaner analysis
12    }
13)
14
15data = response.json()
16review_text = data["content"]
17
18# 2. Analyze sentiment with GPT-4
19client = OpenAI()
20sentiment = client.chat.completions.create(
21    model="gpt-4",
22    messages=[{
23        "role": "system",
24        "content": "Analyze sentiment: positive, negative, or neutral"
25    }, {
26        "role": "user",
27        "content": review_text
28    }]
29)
30
31print(f"Sentiment: {sentiment.choices[0].message.content}")

1urls = [
2    "https://techcrunch.com/article1",
3    "https://techcrunch.com/article2",
4    "https://techcrunch.com/article3"
5]
6
7sentiments = []
8for url in urls:
9    # Extract content (1 credit per request)
10    response = requests.post(
11        "https://api.sentienceapi.com/v1/observe",
12        headers={"Authorization": "Bearer YOUR_API_KEY"},
13        json={"url": url, "mode": "read", "format": "text"}
14    )
15    
16    content = response.json()["content"]
17    
18    # Analyze sentiment
19    sentiment = analyze_with_claude(content)
20    sentiments.append({
21        "url": url,
22        "sentiment": sentiment,
23        "word_count": response.json()["word_count"]
24    })
25
26print(f"Processed {len(sentiments)} articles")

1{
2  "status": "success",
3  "url": "https://www.amazon.com/product-reviews/B08N5WRWNW",
4  "title": "Customer reviews: Wireless Earbuds",
5  "content": "Customer Reviews\n\nJohn D. - 5 stars\n\nThese earbuds are absolutely fantastic! The sound quality is incredible and the battery life lasts all day. I've been using them for a month now and couldn't be happier. The noise cancellation works perfectly on my daily commute. Highly recommend!\n\nSarah M. - 4 stars\n\nGood value for money. The sound is clear and the fit is comfortable. Only downside is the case is a bit bulky, but overall I'm satisfied with my purchase.\n\nMike T. - 2 stars\n\nDisappointed with the build quality. The left earbud stopped working after just two weeks. Customer service was slow to respond. Would not recommend.\n\nLisa K. - 5 stars\n\nBest earbuds I've ever owned! The bass is amazing and they stay in place during workouts. Worth every penny.\n\nRobert P. - 3 stars\n\nThey're okay, nothing special. The sound quality is decent but not exceptional. For the price, I expected more features.",
6  "format": "text",
7  "author": null,
8  "published_date": null,
9  "word_count": 187,
10  "reading_time_minutes": 1,
11  "timestamp": "2025-12-18T14:30:00.123Z"
12}

1{
2  "status": "success",
3  "url": "https://news.ycombinator.com/item?id=12345678",
4  "title": "Show HN: I built a perception layer for AI agents",
5  "content": "# Show HN: I built a perception layer for AI agents\n\nWe're excited to share SentienceAPI, a new tool that helps AI agents understand web pages...\n\n## Features\n\n- Fast content extraction\n- Visual element detection\n- Clean markdown output\n\n## Comments\n\n**User123:** This looks amazing! Can't wait to try it.\n\n**User456:** Great work! The API is really fast.\n\n**User789:** Not sure about the pricing model, but the tech is solid.",
6  "format": "markdown",
7  "author": null,
8  "published_date": null,
9  "word_count": 89,
10  "reading_time_minutes": 1,
11  "timestamp": "2025-12-18T14:30:00.123Z"
12}