OllamaEmbeddings

This notebook covers how to get started with Ollama embedding models.

Installation

install package

%pip install langchain_ollama

Setup

First, follow these instructions to set up and run a local Ollama instance:

• Download and install Ollama onto the available supported platforms (including Windows Subsystem for Linux)
• Fetch available LLM model via ollama pull <name-of-model>
  • View a list of available models via the model library
  • e.g., ollama pull llama3
• This will download the default tagged version of the model. Typically, the default points to the latest, smallest sized-parameter model.

On Mac, the models will be download to ~/.ollama/models

On Linux (or WSL), the models will be stored at /usr/share/ollama/.ollama/models

• Specify the exact version of the model of interest as such ollama pull vicuna:13b-v1.5-16k-q4_0 (View the various tags for the Vicuna model in this instance)
• To view all pulled models, use ollama list
• To chat directly with a model from the command line, use ollama run <name-of-model>
• View the Ollama documentation for more commands. Run ollama help in the terminal to see available commands too.

Usage

from langchain_ollama import OllamaEmbeddings

embeddings = OllamaEmbeddings(model="llama3")

API Reference:OllamaEmbeddings

embeddings.embed_query("My query to look up")

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# async embed query
await embeddings.aembed_query("My query to look up")

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