Bases: BaseToolkit
IBM watsonx.ai Toolkit.
To use, you should have langchain_ibm
python package installed, and the environment variable WATSONX_APIKEY
set with your API key, or pass it as a named parameter to the constructor.
pip install -U langchain-ibm export WATSONX_APIKEY="your-api-key"
Example
from langchain_ibm import WatsonxToolkit watsonx_toolkit = WatsonxToolkit( url="https://us-south.ml.cloud.ibm.com", apikey="*****", ) tools = watsonx_toolkit.get_tools() google_search = watsonx_toolkit.get_tool(tool_name="GoogleSearch") tool_config = { "maxResults": 3, } google_search.set_tool_config(tool_config) input = { "input": "Search IBM", } search_result = google_search.invoke(input)
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
API key to the watsonx.ai Runtime.
ID of the watsonx.ai Studio project.
ID of the watsonx.ai Studio space.
Token to the watsonx.ai Runtime.
URL to the watsonx.ai Runtime.
You can pass one of following as verify: * the path to a CA_BUNDLE file * the path of directory with certificates of trusted CAs * True - default path to truststore will be taken * False - no verification will be made
Get the tool with a given name.
tool_name (str)
Get the tools in the toolkit.
list[WatsonxTool]
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