Update README.md

README.md

@@ -10,4 +10,85 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Sentiment Analyzer
+
+This project provides a web-based tool to analyze the sentiment of reviews using a pre-trained model from Hugging Face's `transformers` library. Users can upload a text file containing reviews, and the tool will display a DataFrame with the sentiment analysis results and a pie chart visualizing the sentiment distribution.
+
+## Features
+
+- **Sentiment Analysis**: Uses a pre-trained model to classify the sentiment of each review as positive or negative.
+- **File Upload**: Allows users to upload a text file containing reviews.
+- **DataFrame Display**: Shows a DataFrame with the original reviews, sentiment labels, and confidence scores.
+- **Pie Chart Visualization**: Displays a pie chart showing the percentage of positive and negative reviews.
+
+## Requirements
+
+- Python 3.6 or higher
+- `transformers` library
+- `pandas` library
+- `matplotlib` library
+- `gradio` library
+
+## Installation
+
+1. Clone the repository:
+    ```bash
+    git clone https://github.com/your-username/sentiment-analyzer.git
+    cd sentiment-analyzer
+    ```
+
+2. Install the required libraries:
+    ```bash
+    pip install transformers pandas matplotlib gradio
+    ```
+
+## Usage
+
+1. Save your reviews in a text file named `reviews.txt`, with each review on a new line.
+
+2. Run the script:
+    ```bash
+    python app.py
+    ```
+
+3. Open your web browser and go to the local server URL provided by Gradio (usually `http://127.0.0.1:7860`).
+
+4. Upload the `reviews.txt` file.
+
+5. The tool will display a DataFrame with the sentiment analysis results and a pie chart visualizing the sentiment distribution.
+
+## Code Explanation
+
+- **read_reviews_to_dataframe**: Reads reviews from a text file and converts them into a pandas DataFrame.
+- **analyzer**: Applies sentiment analysis to a given text and returns the label and score.
+- **evaluate_reviews**: Adds sentiment evaluation to each review in the DataFrame and splits it into 'Sentiment' and 'Score' columns.
+- **create_pie_chart**: Creates and saves a pie chart showing the distribution of sentiments.
+- **process_reviews**: Processes the uploaded file, evaluates reviews, and generates the pie chart.
+- **gradio_interface**: Function for Gradio interface that processes the file and returns the DataFrame and chart path.
+
+## Example
+
+1. Prepare a text file `reviews.txt` with the following content:
+    ```
+    The product quality is excellent!
+    The battery life is awful.
+    Very satisfied with the purchase.
+    Will not buy again, very disappointed.
+    ```
+
+2. Run the script:
+    ```bash
+    python app.py
+    ```
+
+3. Upload `reviews.txt` via the Gradio interface.
+
+4. View the DataFrame and pie chart displaying the sentiment analysis results.
+
+## License
+
+This project is licensed under the MIT License.
+
+## Author
+
+This tool was created by **Walid Ahmed**.