How Can 2 LLM Calls Boost Your RAGs Performance?
By querying multiple LLMs, you can access a wider range of information and perspectives.
Multiple LLMs can be used to verify information and identify inconsistencies.
Different LLMs may generate different responses to the same prompt.
Using multiple LLMs can help mitigate the biases that may be present in individual models.
Combining the outputs of multiple LLMs can lead to more creative and innovative responses.
Complex queries can be broken down and distributed across multiple LLMs, improving response time and accuracy.
Using multiple LLMs can provide redundancy, ensuring that your RAGs system continues to function even if one LLM fails.
While using multiple LLMs may increase costs, it can also improve performance, potentially leading to cost savings in other areas.
Trying different combinations of LLMs can help you find the optimal configuration for your RAGs system.
As LLM technology continues to evolve, using multiple models can help your RAGs system remain adaptable and effective.