lmstudio.py•1.36 kB
from typing import Literal
from openai import OpenAI
from selfmemory.configs.embeddings.base import BaseEmbedderConfig
from selfmemory.embeddings.base import EmbeddingBase
class LMStudioEmbedding(EmbeddingBase):
def __init__(self, config: BaseEmbedderConfig | None = None):
super().__init__(config)
self.config.model = (
self.config.model
or "nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"
)
self.config.embedding_dims = self.config.embedding_dims or 1536
self.config.api_key = self.config.api_key or "lm-studio"
self.client = OpenAI(
base_url=self.config.lmstudio_base_url, api_key=self.config.api_key
)
def embed(
self, text, memory_action: Literal["add", "search", "update"] | None = None
):
"""
Get the embedding for the given text using LM Studio.
Args:
text (str): The text to embed.
memory_action (optional): The type of embedding to use. Must be one of "add", "search", or "update". Defaults to None.
Returns:
list: The embedding vector.
"""
text = text.replace("\n", " ")
return (
self.client.embeddings.create(input=[text], model=self.config.model)
.data[0]
.embedding
)