Remove the prospect_id foreign key from the prompt CREATE TABLE SQL and adjust column order (model moved before data). Also delete drop_llm_table.sql which contained DROP TABLE IF EXISTS llm. Note: this updates the table creation script only—apply a DB migration if you need to remove the existing column or preserve data.

Include the original prompt in cached LinkedIn prompt lookups by adding the prompt column to the SELECT queries and updating the row index mappings. Also add a prompt key (None when not cached) to the response payload so callers receive the associated prompt along with completion, time, model, and record data.

Drop prospect_id filtering and storage from prompt APIs and DB interactions. get_prompt_records no longer accepts or handles prospect_id and always returns paginated prompt records (SELECT no longer includes prospect_id). llm_post no longer reads prospect_id from payload and INSERT into prompt omits the prospect_id column. Error handling and pagination metadata preserved.

When a LinkedIn URL is not found in cache, call Google Gemini to generate a profile analysis and store the result. Adds GEMINI_API_KEY env check, a default prompt if none supplied, and a model fallback loop that tries several Gemini models until one returns text. Inserts the completion, model, duration and metadata into the prompt table (with search_vector when available), closes DB cursors/connections earlier, and returns the generated completion and record id in the response. Improves error handling and updates response meta messages accordingly.