embeddings

To use, you should have langchain_ibm python package installed, and the environment variable WATSONX_API_KEY set with your API key, or pass it as a named parameter api_key to the constructor.

pip install -U langchain-ibm

# or using uv
uv add langchain-ibm

export WATSONX_API_KEY="your-api-key"

from langchain_ibm import WatsonxEmbeddings

embeddings = WatsonxEmbeddings(
    model_id="ibm/granite-embedding-278m-multilingual",
    url="https://us-south.ml.cloud.ibm.com",
    project_id="*****",
    # api_key="*****"
)

input_text = "The meaning of life is 42"
vector = embeddings.embed_query("hello")
print(vector[:3])

[-0.0020519258, 0.0147288125, -0.0090887165]

vectors = embeddings.embed_documents(["hello", "goodbye"])
# Showing only the first 3 coordinates
print(len(vectors))
print(vectors[0][:3])

2
[-0.0020519265, 0.01472881, -0.009088721]

await embeddings.aembed_query(input_text)
print(vector[:3])

# multiple:
# await embeddings.aembed_documents(input_texts)

[-0.0020519258, 0.0147288125, -0.0090887165]