Two issues have been identified: incomplete data in RAG and poor context transfer in LLM. What to do next?

If incomplete data and poor context transfer are identified in RAG (Retrieval-Augmented Generation), the following steps should be taken:

1. Improve the quality and completeness of data for RAG:

   • Check data sources, add missing or more relevant documents.
   • Optimize the indexing and search process to retrieve more relevant fragments.

2. Optimize context transfer to LLM:

   • Ensure that the context is transmitted to the model in full and in the correct format.
   • Use compression or key information extraction techniques to not exceed token limits.
   • Consider splitting the context into parts with subsequent merging of responses.

3. Testing and iterations:

   • Conduct A/B tests with different data sets and context transfer methods.
   • Gather feedback and quality metrics of responses.

4. Implement monitoring:

   • Track the quality of generation and data completeness in real-time for quick response.

Thus, work should be done both on data sources and on the context transfer mechanism to improve the quality of the model's final responses.