Sentiment Analysis and Meme Generator Flask Application

This Flask application performs sentiment analysis on a given text input and generates a corresponding meme based on the sentiment. It integrates with Groq's AI API for sentiment analysis and Imgflip's API for meme generation. The app is designed to analyze emotions like Happy, Sad, Angry, Disgusted, Surprised, Fearful, or Neutral and generate a related meme dynamically.

Features

• Sentiment Analysis: Analyze the sentiment of a given text using Groq's AI API, which classifies the text into different emotional categories.
• Meme Generation: Based on the analyzed sentiment, generate a meme with a relevant template from Imgflip's API.
• Environment Configurations: The application loads environment variables from a .env file for sensitive information like API keys.
• Error Handling: The application handles exceptions gracefully and falls back to default values when necessary.

Installation

Follow these steps to set up the project locally:

1. Clone the Repository

git clone <repo-link>
cd <your-folder>

2. Set Up a Virtual Environment

It is recommended to use a virtual environment for managing dependencies.

For Linux/macOS:

python3 -m venv .venv
source .venv/bin/activate

For Windows:

python -m venv .venv
.venv\Scripts\activate

3. Install Dependencies

Install the required packages using pip.

pip install -r requirements.txt

4. Create a .env File

Create a .env file in the root directory and add the following configuration:

GROQ_API_KEY=your_groq_api_key
IMGFLIP_USERNAME=your_imgflip_username
IMGFLIP_PASSWORD=your_imgflip_password

Replace the placeholders with your actual API keys.

5. Run the Flask Application

You can run the Flask application locally by executing the following command:

python app.py

The application will run on port 10000 by default. You can visit it by navigating to http://127.0.0.1:10000 in your browser.

6. Deploy to a Cloud Provider (Optional)

For production, deploy the application to a cloud service like Heroku, Render, or AWS.

---

How It Works

1. Sentiment Analysis

The analyze_sentiment function sends a prompt to Groq's AI API. It asks Groq to analyze the sentiment of the input text and classify it into one of the following emotions:

• Happy
• Sad
• Angry
• Disgusted
• Surprised
• Fearful
• Neutral

The result is returned to the Flask app.

2. Post-Processing Sentiment

The sentiment received from the Groq API is further refined by the post_process_sentiment function. This function checks the presence of specific keywords in the text to adjust the sentiment if needed. For example:

• If the text contains words like "gross", "ew", or "disgusting", the sentiment will be classified as Disgusted.
• If words like "amazing", "happy", or "joy" are found, it will classify as Happy.

3. Meme Generation

After determining the sentiment, the app generates a meme using the Imgflip API. It selects a relevant meme template based on the sentiment and uses captions that reflect the emotional tone.

• Happy: Uses cheerful meme templates like "Success Kid" and "Doge".
• Sad: Selects sad memes like "Crying Jordan".
• Angry: Uses memes like "Drake" or "Gru".
• Disgusted: Chooses disgusted face templates.
• Surprised: Uses memes like "Pikachu Surprise".
• Fearful: Selects scared memes.
• Neutral: Uses neutral memes like "Meh".

4. API Endpoints

POST /analyze

• Description: Analyzes the sentiment of the provided text and generates a corresponding meme.
• Request Body:

  {
    "text": "I am so happy today!"
  }

• Response:

  {
    "sentiment": "Happy",
    "meme_url": "https://i.imgflip.com/your_meme.jpg"
  }

---

Environment Variables

The application requires the following environment variables:

• GROQ_API_KEY: Your API key from Groq to perform sentiment analysis.
• IMGFLIP_USERNAME: Your Imgflip username for meme generation.
• IMGFLIP_PASSWORD: Your Imgflip password for meme generation.

---

Dependencies

This project requires the following Python libraries:

• Flask: Web framework for building the app.
• requests: HTTP library to make requests to the Imgflip API.
• python-dotenv: For loading environment variables from .env file.
• groq: Groq client to interact with Groq's AI API.

These dependencies are listed in the requirements.txt file.

---

Logging

The application uses Python's logging library to log errors, especially for API calls to Groq and Imgflip. You can adjust the log level as needed during development.

---

Error Handling

The application ensures that if there's an error with the Groq or Imgflip APIs, a fallback default behavior is applied:

• If sentiment analysis fails, the default sentiment is Neutral.
• If meme generation fails, a default meme is returned.

---

Contributions

Feel free to contribute to this project by submitting a pull request or opening an issue if you encounter any bugs or have suggestions for improvements.