Embedding storage format#
The default output format of the llm embed
command is a JSON array of floating point numbers.
LLM stores embeddings in space-efficient format: a little-endian binary sequences of 32-bit floating point numbers, each represented using 4 bytes.
These are stored in a BLOB
column in a SQLite database.
The following Python functions can be used to convert between this format and an array of floating point numbers:
import struct
def encode(values):
return struct.pack("<" + "f" * len(values), *values)
def decode(binary):
return struct.unpack("<" + "f" * (len(binary) // 4), binary)
These functions are available as llm.encode()
and llm.decode()
.
If you are using NumPy you can decode one of these binary values like this:
import numpy as np
numpy_array = np.frombuffer(value, "<f4")
The <f4
format string here ensures NumPy will treat the data as a little-endian sequence of 32-bit floats.