This is a simple chatbot application built with Python, Streamlit, and TextBlob. The chatbot uses sentiment analysis to generate responses based on the sentiment of the user's input.

• streamlit: A fast, easy way to create web apps for machine learning and data science.
• textblob: A library for processing textual data, providing a simple API for diving into common natural language processing (NLP) tasks.

The ChatBot class is the main class in this application. It has two methods:

This is the constructor method that initializes the TextBlob object for sentiment analysis.

This method takes in a user message as input, analyzes its sentiment, and generates a response based on the sentiment score. The sentiment score ranges from -1 (negative) to 1 (positive).

• If the sentiment score is positive, the chatbot responds positively.
• If the sentiment score is negative, the chatbot offers to transfer the user to an agent.
• If the sentiment score is neutral, the chatbot asks for more information.

The Streamlit UI is simple and intuitive. It consists of a title, a text input field for the user's message, and a text area to display the chatbot's response.

"Word is Bond" for several reasons:

1. Trustworthiness: The phrase "word is bond" conveys a sense of trustworthiness and reliability. By using this name, the chatbot suggests that it will uphold its promises and commitments, fostering trust between the user and the AI.

2. Confidence in Accuracy: The term "word" implies a commitment to truth and accuracy. Users may feel confident that the chatbot will provide accurate and reliable responses to their queries or discussions about sentiments.

3. Connection to Communication: "Word is bond" has roots in colloquial language, particularly within certain cultural contexts. This connection to everyday language can make the chatbot feel more approachable and relatable to users.

4. Emotional Connection: Sentiment-based interactions often involve emotional elements. The phrase "word is bond" carries emotional weight, suggesting a bond or connection between the user and the chatbot, which can enhance the emotional resonance of the interaction.

5. Memorability: The name "Word is Bond" is memorable and catchy, making it easy for users to recall when seeking out a sentiment-based chatbot for future interactions.

To run the application, use the following command in the terminal:

streamlit run app.py