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IBM watsonx.ai

WatsonxEmbeddings is a wrapper for IBM watsonx.ai foundation models.

This example shows how to communicate with watsonx.ai models using LangChain.

Setting upโ€‹

Install the package langchain-ibm.

!pip install -qU langchain-ibm

This cell defines the WML credentials required to work with watsonx Embeddings.

Action: Provide the IBM Cloud user API key. For details, see documentation.

import os
from getpass import getpass

watsonx_api_key = getpass()
os.environ["WATSONX_APIKEY"] = watsonx_api_key

Additionaly you are able to pass additional secrets as an environment variable.

import os

os.environ["WATSONX_URL"] = "your service instance url"
os.environ["WATSONX_TOKEN"] = "your token for accessing the CPD cluster"
os.environ["WATSONX_PASSWORD"] = "your password for accessing the CPD cluster"
os.environ["WATSONX_USERNAME"] = "your username for accessing the CPD cluster"
os.environ["WATSONX_INSTANCE_ID"] = "your instance_id for accessing the CPD cluster"

Load the modelโ€‹

You might need to adjust model parameters for different models.

from ibm_watsonx_ai.metanames import EmbedTextParamsMetaNames

embed_params = {
EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
EmbedTextParamsMetaNames.RETURN_OPTIONS: {"input_text": True},
}

Initialize the WatsonxEmbeddings class with previously set parameters.

Note:

  • To provide context for the API call, you must add project_id or space_id. For more information see documentation.
  • Depending on the region of your provisioned service instance, use one of the urls described here.

In this example, weโ€™ll use the project_id and Dallas url.

You need to specify model_id that will be used for inferencing.

from langchain_ibm import WatsonxEmbeddings

watsonx_embedding = WatsonxEmbeddings(
model_id="ibm/slate-125m-english-rtrvr",
url="https://us-south.ml.cloud.ibm.com",
project_id="PASTE YOUR PROJECT_ID HERE",
params=embed_params,
)

Alternatively you can use Cloud Pak for Data credentials. For details, see documentation.

watsonx_embedding = WatsonxEmbeddings(
model_id="ibm/slate-125m-english-rtrvr",
url="PASTE YOUR URL HERE",
username="PASTE YOUR USERNAME HERE",
password="PASTE YOUR PASSWORD HERE",
instance_id="openshift",
version="4.8",
project_id="PASTE YOUR PROJECT_ID HERE",
params=embed_params,
)

Usageโ€‹

Embed queryโ€‹

text = "This is a test document."

query_result = watsonx_embedding.embed_query(text)
query_result[:5]
[0.0094472, -0.024981909, -0.026013248, -0.040483925, -0.057804465]

Embed documentsโ€‹

texts = ["This is a content of the document", "This is another document"]

doc_result = watsonx_embedding.embed_documents(texts)
doc_result[0][:5]
[0.009447193, -0.024981918, -0.026013244, -0.040483937, -0.057804447]

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