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Test
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# Chatbot using NLP ## Overview This project implements a chatbot using Natural Language Processing (NLP) techniques. The chatbot is designed to understand user intents and provide appropriate responses based on predefined patterns and responses. It utilizes the `nltk` library for natural language processing, `scikit-learn` for machine learning, and `streamlit` for creating an interactive web interface. --- ## Features - Understands various user intents such as greetings, farewells, gratitude, and more. - Provides relevant responses based on user input. - Maintains a conversation history that can be viewed by the user. - Built using Python and leverages popular libraries for NLP and machine learning. --- ## Technologies Used - **Python** - **NLTK** - **Scikit-learn** - **Streamlit** - **JSON** for intents data --- ## Installation ### 1. Clone the Repository ```bash git clone <repository-url> cd <repository-directory> ``` ### 2. Create a Virtual Environment (Optional but Recommended) ```bash python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate` ``` ### 3. Install Required Packages ```bash pip install -r requirements.txt ``` ### 4. Download NLTK Data ```python import nltk nltk.download('punkt') ``` --- ## Usage To run the chatbot application, execute the following command: ```bash streamlit run app.py ``` Once the application is running, you can interact with the chatbot through the web interface. Type your message in the input box and press Enter to see the chatbot's response. --- ## Intents Data The chatbot's behavior is defined by the `intents.json` file, which contains various tags, patterns, and responses. You can modify this file to add new intents or change existing ones. --- ## Conversation History The chatbot saves the conversation history in a CSV file (`chat_log.csv`). You can view past interactions by selecting the "Conversation History" option in the sidebar. --- ## Contributing Contributions to this project are welcome! If you have suggestions for improvements or features, feel free to open an issue or submit a pull request. --- ## License This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. --- ## Acknowledgments - **NLTK** for natural language processing. - **Scikit-learn** for machine learning algorithms. - **Streamlit** for building the web interface. --- Replace `<repository-url>` and `<repository-directory>` with the actual URL of your repository and the name of the directory where the project is located. Adjust any sections as necessary to better fit your project's specifics.
