Skip to main content
Open on GitHub

IBM

LangChain integrations related to IBM technologies, including the IBM watsonx.ai platform and DB2 database.

Watsonx AI​

IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers:

  • Multi-model variety and flexibility: Choose from IBM-developed, open-source and third-party models, or build your own model.
  • Differentiated client protection: IBM stands behind IBM-developed models and indemnifies the client against third-party IP claims.
  • End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides.
  • Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.

Installation and Setup​

Install the integration package with

pip install -qU langchain-ibm

Get an IBM watsonx.ai api key and set it as an environment variable (WATSONX_APIKEY)

import os

os.environ["WATSONX_APIKEY"] = "your IBM watsonx.ai api key"

Chat Model​

ChatWatsonx​

See a usage example.

from langchain_ibm import ChatWatsonx

LLMs​

WatsonxLLM​

See a usage example.

from langchain_ibm import WatsonxLLM

Embedding Models​

WatsonxEmbeddings​

See a usage example.

from langchain_ibm import WatsonxEmbeddings

Reranker​

WatsonxRerank​

See a usage example.

from langchain_ibm import WatsonxRerank

Toolkit​

WatsonxToolkit​

See a usage example.

from langchain_ibm.agent_toolkits.utility import WatsonxToolkit

DB2​

Vector stores​

The IBM DB2 relational database v12.1.2 and above offers the abilities of vector store and vector search. Installation of langchain-db2 package will give Langchain users the support of DB2 vector store and vector search.

See detailed usage examples in the guide here.

Installation: This is a separate package for vector store feature only and can be run without the langchain-ibm package.

pip install -U langchain-db2

Usage:

from langchain_db2 import db2vs
from langchain_db2.db2vs import DB2VS