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Euler Graph Database

Ollama Embeddings

OllamaEmbedding¶

Overview¶

The ollama_embed function is designed to generate embeddings for a list of texts using the Ollama model. This functionality is part of the Euler Graph Database and can be accessed via the EmbedFactory class.

Arguments¶

base_url (str): The base URL for the Ollama API.
model_name (str): The name of the model to use for generating embeddings.
texts (List[str]): A list of texts to generate embeddings for.
temperature (float, optional): The temperature parameter for the model, defaults to 0.7.

Example Usage¶

Here's an example demonstrating how to use the ollama_embed function:

from euler.embed_factory import EmbedFactory

Initialize the Ollama Embedding Reader¶

openai_reader = EmbedFactory.get_llm_reader(
    'ollama_embed',
    base_url='http://localhost:11434',
    model='nomic-embed-text:latest'
)

Generate Embeddings for a Prompt¶

result = openai_reader.generate_query_embeddings("Example prompt for the OpenAI model.")
print(result if result else "No response received.")

Functions¶

`ollama_embed`¶

The ollama_embed function takes a base URL, model name, a list of texts, and an optional temperature parameter to generate embeddings for each text in the list. It returns a list of embeddings.

`process_embed`¶

The process_embed function sends a request to the Ollama API with the provided base URL, model name, prompt, and temperature. It processes the response to extract and return the embedding for the given prompt.