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📡 API Documentation

Base URL: http://localhost:8000/api

Endpoints

1. Analyze Sentiment

POST /sentiment/analyze/

Analyzes the sentiment of a review text.

Request Body:

{
  "review_text": "সিনেমাটা অসাধারণ ছিল!"
}

Response:

{
  "id": 1,
  "sentiment": "Positive",
  "confidence": 85.5,
  "word_importance": [
    {"word": "অসাধারণ", "score": 0.456},
    {"word": "ছিল", "score": 0.123}
  ],
  "colored_html": [
    {
      "word": "সিনেমাটা",
      "score": 0.045,
      "color": "rgba(200, 200, 200, 0.2)",
      "effect": "neutral"
    },
    {
      "word": "অসাধারণ",
      "score": 0.456,
      "color": "rgba(0, 200, 0, 0.7)",
      "effect": "positive"
    }
  ]
}

Status Codes:

  • 200 OK - Success
  • 400 Bad Request - Invalid input
  • 500 Internal Server Error - Analysis failed

2. Get Analysis History

GET /sentiment/history/

Returns the last 20 sentiment analyses.

Response:

[
  {
    "id": 1,
    "review_text": "সিনেমাটা অসাধারণ ছিল!",
    "sentiment": "Positive",
    "confidence": 85.5,
    "word_importance": [...],
    "created_at": "2024-01-15T10:30:00Z"
  }
]

3. List All Analyses

GET /sentiment/

Returns all sentiment analyses (paginated).

Response:

{
  "count": 50,
  "next": "http://localhost:8000/api/sentiment/?page=2",
  "previous": null,
  "results": [...]
}

4. Get Single Analysis

GET /sentiment/{id}/

Returns a specific analysis by ID.

Response:

{
  "id": 1,
  "review_text": "সিনেমাটা অসাধারণ ছিল!",
  "sentiment": "Positive",
  "confidence": 85.5,
  "word_importance": [...],
  "created_at": "2024-01-15T10:30:00Z"
}

Example Usage

Using cURL

# Analyze sentiment
curl -X POST http://localhost:8000/api/sentiment/analyze/ \
  -H "Content-Type: application/json" \
  -d '{"review_text": "সিনেমাটা অসাধারণ ছিল!"}'

# Get history
curl http://localhost:8000/api/sentiment/history/

Using JavaScript (Fetch)

// Analyze sentiment
const response = await fetch('http://localhost:8000/api/sentiment/analyze/', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    review_text: 'সিনেমাটা অসাধারণ ছিল!'
  })
});
const data = await response.json();
console.log(data);

Using Python (requests)

import requests

# Analyze sentiment
response = requests.post(
    'http://localhost:8000/api/sentiment/analyze/',
    json={'review_text': 'সিনেমাটা অসাধারণ ছিল!'}
)
print(response.json())

# Get history
response = requests.get('http://localhost:8000/api/sentiment/history/')
print(response.json())

Response Fields

Sentiment Analysis Object

Field Type Description
id integer Unique identifier
review_text string Original review text
sentiment string "Positive", "Negative", or "Neutral"
confidence float Confidence score (0-100)
word_importance array List of important words with scores
colored_html array Word-by-word visualization data
created_at datetime Timestamp of analysis

Word Importance Object

Field Type Description
word string The word
score float Importance score (-1 to 1)

Positive score = makes sentiment more positive Negative score = makes sentiment more negative

Colored HTML Object

Field Type Description
word string The word
score float Importance score
color string RGBA color for visualization
effect string "positive", "negative", or "neutral"

Error Responses

400 Bad Request

{
  "review_text": ["This field is required."]
}

500 Internal Server Error

{
  "error": "Model loading failed"
}

Rate Limiting

Currently no rate limiting. For production, consider adding:

  • Django REST Framework throttling
  • Redis-based rate limiting
  • API key authentication

CORS

CORS is enabled for:

  • http://localhost:3000
  • http://127.0.0.1:3000

To add more origins, edit backend/config/settings.py:

CORS_ALLOWED_ORIGINS = [
    "http://localhost:3000",
    "http://your-domain.com",
]