To enhance chatbot engagement and reduce generic responses, integrate retrieval-augmented generation (RAG), fine-tune with diverse conversational datasets, and implement fallback strategies with context-aware rephrasing.
Here is the code snippet you can refer to:

In the above, we are using the following key points:
- Conversational Model: Uses a transformer-based text generation model (Mistral-7B-Instruct).
- Fallback Responses: Predefined context-aware responses prevent generic replies.
- Response Filtering: Checks for generic phrases and replaces them dynamically.
- Retrieval-Augmented Strategy: Enhances responses when the model lacks sufficient information.
- Engagement Tactics: Encourages user participation by prompting discussion.
Hence, by integrating retrieval-augmented fallback responses and filtering out generic phrases, the chatbot generates more engaging and context-aware conversations, improving user interaction quality.