33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
import logging
|
|
from typing import Optional
|
|
|
|
try:
|
|
from ollama import Client
|
|
except ImportError:
|
|
raise ImportError("Ollama Embedder requires extra dependencies. Install with `pip install ollama`") from None
|
|
|
|
from langchain_community.embeddings import OllamaEmbeddings
|
|
|
|
from embedchain.config import OllamaEmbedderConfig
|
|
from embedchain.embedder.base import BaseEmbedder
|
|
from embedchain.models import VectorDimensions
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class OllamaEmbedder(BaseEmbedder):
|
|
def __init__(self, config: Optional[OllamaEmbedderConfig] = None):
|
|
super().__init__(config=config)
|
|
|
|
client = Client(host=config.base_url)
|
|
local_models = client.list()["models"]
|
|
if not any(model.get("name") == self.config.model for model in local_models):
|
|
logger.info(f"Pulling {self.config.model} from Ollama!")
|
|
client.pull(self.config.model)
|
|
embeddings = OllamaEmbeddings(model=self.config.model, base_url=config.base_url)
|
|
embedding_fn = BaseEmbedder._langchain_default_concept(embeddings)
|
|
self.set_embedding_fn(embedding_fn=embedding_fn)
|
|
|
|
vector_dimension = self.config.vector_dimension or VectorDimensions.OLLAMA.value
|
|
self.set_vector_dimension(vector_dimension=vector_dimension)
|