Troubleshooting

This page provides solutions to common issues you might encounter when setting up or using the Sentiment Analysis Web Application.

Installation Issues

NLTK Resource Not Found

Problem: Error message about missing NLTK resources:

LookupError: Resource stopwords not found.
Please use the NLTK Downloader to obtain the resource.

Solution: Run the following commands in a Python interpreter:

import nltk
nltk.download('stopwords')
nltk.download('punkt')

Package Installation Failures

Problem: Errors when installing required packages.

Solution:

• Make sure you have the latest version of pip: pip install --upgrade pip
• Try installing packages one by one to identify which one is causing the issue
• If you're on Windows and having issues with some packages, you might need to install a C++ compiler

Runtime Issues

Application Won't Start

Problem: Error when trying to run the application.

Solution:

• Check if all required packages are installed
• Verify that the model files (sentiment_model.pkl and tfidf_vectorizer.pkl) exist in the project directory
• Check if the port is already in use by another application

Model Loading Error

Problem: Error when the application tries to load the model files.

Solution:

• Ensure the model files are in the correct location
• If you're using a model trained with a different scikit-learn version, you might need to retrain the model with your current version

API Issues

400 Bad Request

Problem: Getting a 400 Bad Request response from the API.

Solution:

• Make sure you're sending a POST request
• Ensure the Content-Type header is set to application/json
• Check that your request body includes a "text" field
• Verify that your JSON is properly formatted

500 Internal Server Error

Problem: Getting a 500 Internal Server Error response from the API.

Solution:

• Check the server logs for more detailed error information
• Ensure the model files are correctly loaded
• Try with a simpler text input to see if the issue is with specific text content

Web Interface Issues

Results Not Displaying

Problem: After clicking "Analyze Sentiment", no results appear.

Solution:

• Check your browser's console for JavaScript errors
• Ensure JavaScript is enabled in your browser
• Verify that the API endpoint is working by testing it directly

Incorrect Sentiment Analysis

Problem: The sentiment analysis results seem incorrect.

Solution:

• Remember that the model has limitations and may not always predict correctly
• Complex language features like sarcasm, irony, or domain-specific terminology might cause incorrect predictions
• Consider retraining the model with more diverse data if this is a consistent issue

Performance Issues

Slow Response Times

Problem: The application takes a long time to analyze text.

Solution:

• For production use, make sure you're running with python run.py instead of python app.py
• Consider optimizing the text preprocessing pipeline
• If handling many requests, you might need to scale the application or implement caching

Still Having Issues?

If you're still experiencing problems after trying these solutions:

1. Check the GitHub Issues page to see if someone else has reported the same problem
2. Create a new issue with detailed information about your problem
3. Include your environment details (OS, Python version, browser, etc.)
4. Provide steps to reproduce the issue