How can I deploy fine-tuned models for real-time interactive chatbots without compromising performance in terms of speed

Question

With the help of proper code examples can you tell me How can I deploy fine-tuned models for real-time interactive chatbots without compromising performance in terms of speed?

Answer 1

To deploy fine-tuned models for real-time chatbots efficiently, use model quantization, caching, and asynchronous API calls to balance speed and accuracy.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Asynchronous Processing – Uses asyncio to handle multiple requests concurrently, reducing response latency.
• Response Caching – Implements lru_cache to store frequently requested queries, improving performance.
• Fine-Tuned Model Deployment – Uses OpenAI's fine-tuned model for customized chatbot responses.
• FastAPI Integration – Provides a lightweight, high-performance API for real-time interaction.
• Scalability – Supports large-scale deployment while maintaining low latency.

Hence, deploying fine-tuned models for real-time chatbots with asynchronous execution, caching, and optimized API handling ensures high performance without compromising speed.