Normalize AI Search Scores and Integrate PostgreSQL Signals for Re-ranking in azure-db

Currently, search scores are not normalized between 0 and 1, potentially impacting the consistency of result rankings. There's a need to implement score normalization within the range of the search results returned. Additionally, we should consider integrating other relevant signals from our PostgreSQL database to enhance the re-ranking process.

## Tasks
- Investigate the current scoring algorithm to understand the bounds of search scores.
- Develop a normalization function to scale search scores between 0 and 1 within the context of each particular set of search results.
- Design and implement a method to integrate PostgreSQL database signals with the existing search scores.

## Acceptance Criteria
- Search scores are normalized between 0 and 1 for every set of search results returned.
- PostgreSQL signals are effectively integrated into the re-ranking algorithm.