llama-index-embeddings-openai

import os from llama_index.core import Settings from llama_index.embeddings.openai import OpenAIEmbedding # Set your OpenAI API key as an environment variable # It's recommended to load this from a .env file in production os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "YOUR_OPENAI_API_KEY") # Ensure the API key is set if not os.environ["OPENAI_API_KEY"] or os.environ["OPENAI_API_KEY"] == "YOUR_OPENAI_API_KEY": raise ValueError("OPENAI_API_KEY environment variable not set. Please set it to your OpenAI API key.") # Initialize the OpenAI Embedding model and set it as the global default # By default, uses 'text-embedding-ada-002' Settings.embed_model = OpenAIEmbedding(model="text-embedding-ada-002") # Alternatively, create a local instance without setting it globally embed_model_local = OpenAIEmbedding(model="text-embedding-3-small") # Get a single text embedding using the local instance text = "This is a test sentence for embedding with a local model." embedding = embed_model_local.get_text_embedding(text) print(f"Embedding length: {len(embedding)}") # print(f"First 5 elements of embedding: {embedding[:5]}...") # Get embeddings for multiple texts using the global default texts_list = ["Hello world!", "LlamaIndex is great.", "OpenAI embeddings are powerful."] embeddings_for_list = Settings.embed_model.get_text_embeddings(texts_list) print(f"Number of embeddings for list: {len(embeddings_for_list)}") for i, emb in enumerate(embeddings_for_list): print(f"Embedding {i} length: {len(emb)}")