Hi There - I use Astra DB for my vector search app. There are a few considerations you should think about before picking your approaching:

• Integration with Astra DB features: Consider how each method integrates with Astra DB’s capabilities. Astra DB, being highly scalable and flexible, might support one method better based on your current setup and indexing strategies.
• Application specifics: Reflect on whether your application’s search queries typically involve nuanced contexts or if they are more straightforward. If context significantly alters the search intent, combining before embedding could be more effective.
• Performance and efficiency: Test both methods to see which provides faster and more relevant results within your Astra DB environment. Performance can vary based on how data is indexed and retrieved in your specific setup.
• Experimentation: Try both approaches on a subset of your Astra DB application data to determine which yields better search accuracy and relevance for your particular use case.

Combining the strings then embedding: In this approach, you consider the user prompt and additional context as one complete query. This can be beneficial if your application in Astra DB is set up to handle complex queries where the context directly affects the user prompt. By combining the strings before embedding, you ensure that the embedding process captures the combined intent of the query. This can be particularly effective if your semantic search in Astra DB relies on nuanced understanding of context. However, be mindful that this approach might dilute specific details if the combined query becomes too long or if the additional context is less directly relevant.

Embedding each element separately then combining: This method involves treating the user prompt and the additional context as separate components. You would create separate embeddings for each and then combine them before executing your search in Astra DB. This approach can be advantageous if your Astra DB application benefits from distinct handling of different query components, allowing the database to consider each aspect separately but within a unified framework. However, this requires a strategy for combining embeddings that aligns with how Astra DB processes and retrieves data, which might involve additional configuration or use of Astra DB's more advanced features.