This project demonstrates the creation of a chatbot utilizing Groq technology and LangChain for conversational systems. The primary goals are to effectively manage dialogues and develop a responsive AI assistant. This chatbot is built on the Groq API using the Gemma2-9b model.
- Session-Based Memory: The model can handle multiple chat sessions and remember user-specific information across different chats.
- Dynamic Language Support: Allows language switching (e.g., English, French) for responses.
- Prompt Customization: Customizable prompts for different contexts.
- Message Trimming: Efficiently manages large conversation histories using
trim_messages.
- Research & Academia: This project can serve as a tool for researchers and students, showcasing advanced AI techniques in natural language processing and memory management in chatbot systems.
- Customer Support Systems: The chatbot's ability to maintain conversation history and adapt to various language needs makes it ideal for real-time customer service applications.
- Multilingual Assistants: With its language adaptability and dynamic response system, this chatbot can act as a virtual assistant for global markets.
- AI-driven Educational Tools: The project could be extended into interactive AI tutors, providing real-time feedback and maintaining session histories across multiple learning sessions.
This chatbot project serves as a comprehensive demonstration of applying state-of-the-art AI technologies for building a conversational agent.