SEARCH BY MEANING, THEN ANSWER.
A QUESTION IS TURNED INTO A VECTOR. THE CLOSEST PASSAGES FROM YOUR OWN DOCUMENTS ARE RETRIEVED AND GIVEN TO THE MODEL AS CONTEXT.

01 EMBED02 SEARCH03 RETRIEVE04 GENERATE
NEAR IN ANGLE, NEAR IN MEANING.
COSINE SIMILARITY MEASURES THE ANGLE BETWEEN TWO VECTORS. THE SEARCH OPENS A CONE AROUND THE QUESTION UNTIL IT HOLDS K PASSAGES.
k = 3

07AUGMENTED PROMPT
QUERY TIMERETRIEVED PASSAGES ARE PASTED INTO THE PROMPT.
08GROUNDED ANSWER
QUERY TIMEA black hole is a region of spacetimewhere gravity is so strong that nothing,not even light, can escape [1]. Its edgeis the event horizon [2]. The first imageof one was published in 2019 [3].
- [1] black-holes.md §1
- [2] black-holes.md §2
- [3] eht-2019.md
THE ANSWER CITES WHAT IT USED.
Retrieval- Augmented Generation
Search by Meaning
A MODEL ONLY KNOWS WHAT IT WAS TRAINED ON. RETRIEVAL LETS IT READ FRESH OR PRIVATE DOCUMENTS AT ANSWER TIME — UPDATE THE INDEX, NOT THE WEIGHTS.
Three stacked plates: the documents cut into chunks at the bottom, the vector index in the middle, the prompt on top. A dotted line carries the question down into the index; three cyan lines carry the three retrieved passages up into the prompt as its context [1], [2], [3].
CHUNK
EMBED
d = 768 (e.g.)
SCORE
RETRIEVE
GENERATE
WHEN IT FAILS
- Bad chunks — the answer is cut in half or buried in noise.
- Missed retrieval — the right passage ranks below k.
- Stale index — the files changed, the vectors did not.