IBM watsonx.ai

WatsonxToolkit 是 IBM watsonx.ai 工具包的一个封装。

本示例展示了如何使用 LangChain 调用 watsonx.ai 工具包。

概述

集成详情

类别	包	可序列化	JS 支持	包下载量	最新包版本
WatsonxToolkit	langchain-ibm	❌	✅

设置

要访问 IBM watsonx.ai 工具包，您需要创建 IBM watsonx.ai 账户，获取 API 密钥，并安装 langchain-ibm 集成包。

凭证

此单元格定义了使用 watsonx 工具包所需的 WML 凭证。

操作： 提供 IBM Cloud 用户 API 密钥。有关详细信息，请参阅文档。

import os
from getpass import getpass

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

此外，您还可以将其他密钥作为环境变量传递。

import os

os.environ["WATSONX_URL"] = "your service instance url"
os.environ["WATSONX_TOKEN"] = "your token for accessing the service instance"

安装

LangChain IBM 集成位于 langchain-ibm 包中。

!pip install -qU langchain-ibm

实例化

初始化 WatsonxToolkit 类。

from langchain_ibm import WatsonxToolkit

watsonx_toolkit = WatsonxToolkit(
    url="https://us-south.ml.cloud.ibm.com",
)

API 参考：WatsonxToolkit

对于某些要求，可以选择将 IBM 的 APIClient 对象传递给 WatsonxToolkit 类。

from ibm_watsonx_ai import APIClient

api_client = APIClient(...)

watsonx_toolkit = WatsonxToolkit(
    watsonx_client=api_client,
)

工具

获取所有工具

可以将所有可用的工具作为 WatsonxTool 对象列表获取。

watsonx_toolkit.get_tools()

[WatsonxTool(name='GoogleSearch', description='Search for online trends, news, current events, real-time information, or research topics.', args_schema=<class 'langchain_ibm.toolkit.ToolArgsSchema'>, agent_description='Search for online trends, news, current events, real-time information, or research topics.', tool_config_schema={'title': 'config schema for GoogleSearch tool', 'type': 'object', 'properties': {'maxResults': {'title': 'Max number of results to return', 'type': 'integer', 'minimum': 1, 'maximum': 20}}}, watsonx_client=<ibm_watsonx_ai.client.APIClient object at 0x127e0f490>),
 WatsonxTool(name='WebCrawler', description='Useful for when you need to summarize a webpage. Do not use for Web search.', args_schema=<class 'langchain_ibm.toolkit.ToolArgsSchema'>, agent_description='Useful for when you need to summarize a webpage. Do not use for Web search.', tool_input_schema={'type': 'object', 'properties': {'url': {'title': 'url', 'description': 'URL for the webpage to be scraped', 'type': 'string', 'pattern': '^(https?:\/\/)?([\da-z\.-]+)\.([a-z\.]{2,6})([\/\w \.-]*)*\/?$'}}, 'required': ['url']}, watsonx_client=<ibm_watsonx_ai.client.APIClient object at 0x127e0f490>),
 WatsonxTool(name='SDXLTurbo', description='Generate an image from text using Stability.ai', args_schema=<class 'langchain_ibm.toolkit.ToolArgsSchema'>, agent_description='Generate an image from text. Not for image refining. Use very precise language about the desired image, including setting, lighting, style, filters and lenses used. Do not ask the tool to refine an image.', watsonx_client=<ibm_watsonx_ai.client.APIClient object at 0x127e0f490>),
 WatsonxTool(name='Weather', description='Find the weather for a city.', args_schema=<class 'langchain_ibm.toolkit.ToolArgsSchema'>, agent_description='Find the weather for a city.', tool_input_schema={'type': 'object', 'properties': {'location': {'title': 'location', 'description': 'Name of the location', 'type': 'string'}, 'country': {'title': 'country', 'description': 'Name of the state or country', 'type': 'string'}}, 'required': ['location']}, watsonx_client=<ibm_watsonx_ai.client.APIClient object at 0x127e0f490>),
 WatsonxTool(name='RAGQuery', description='Search the documents in a vector index.', args_schema=<class 'langchain_ibm.toolkit.ToolArgsSchema'>, agent_description='Search information in documents to provide context to a user query. Useful when asked to ground the answer in specific knowledge about {indexName}', tool_config_schema={'title': 'config schema for RAGQuery tool', 'type': 'object', 'properties': {'vectorIndexId': {'title': 'Vector index identifier', 'type': 'string'}, 'projectId': {'title': 'Project identifier', 'type': 'string'}, 'spaceId': {'title': 'Space identifier', 'type': 'string'}}, 'required': ['vectorIndexId'], 'oneOf': [{'required': ['projectId']}, {'required': ['spaceId']}]}, watsonx_client=<ibm_watsonx_ai.client.APIClient object at 0x127e0f490>)]

获取一个工具

您也可以通过名称获取特定的 WatsonxTool。

google_search = watsonx_toolkit.get_tool(tool_name="GoogleSearch")

调用

使用简单输入调用工具

search_result = google_search.invoke(input="IBM")
search_result

{'output': '[{"title":"IBM - United States","description":"Technology & Consulting. From next-generation AI to cutting edge hybrid cloud solutions to the deep expertise of IBM Consulting, IBM has what it takes to help\xa0...","url":"https://www.ibm.com/us-en"},{"title":"IBM - Wikipedia","description":"International Business Machines Corporation (using the trademark IBM), nicknamed Big Blue, is an American multinational technology company headquartered in\xa0...","url":"https://en.wikipedia.org/wiki/IBM"},{"title":"IBM Envizi ESG Suite","description":"Envizi systemizes the capture, transformation and consolidation of disparate sustainability data into a single source of truth and delivers actionable insights.","url":"https://www.ibm.com/products/envizi"},{"title":"IBM Research","description":"Tools + Code · BeeAI Framework. Open-source framework for building, deploying, and serving powerful agentic workflows at scale. · Docling. An open-source tool\xa0...","url":"https://research.ibm.com/"},{"title":"IBM SkillsBuild: Free Skills-Based Learning From Technology Experts","description":"IBM SkillsBuildPower your future in tech with job skills, courses, and credentials—for free. Power your future in tech with job skills, courses, and credentials\xa0...","url":"https://skillsbuild.org/"},{"title":"IBM | LinkedIn","description":"Locations · Primary. International Business Machines Corp. · 590 Madison Ave · 90 Grayston Dr · Plaza Independencia 721 · 388 Phahon Yothin Road · Jalan Prof.","url":"https://www.linkedin.com/company/ibm"},{"title":"International Business Machines Corporation (IBM)","description":"PROFITABILITY_AND_INCOME_STATEMENT · 9.60% · (TTM). 3.06% · (TTM). 24.06% · (TTM). 62.75B · (TTM). 6.02B · (TTM). 6.41. BALANCE_SHEET_AND_CASH_FLOW. (MRQ).","url":"https://finance.yahoo.com/quote/IBM/"},{"title":"Zurich - IBM Research","description":"The location in Zurich is one of IBM\'s 12 global research labs. IBM has maintained a research laboratory in Switzerland since 1956.","url":"https://research.ibm.com/labs/zurich"},{"title":"IBM (@ibm) • Instagram photos and videos","description":"Science, Technology & Engineering. We partner with developers, data scientists, CTOs and other creators to make the world work better.","url":"https://www.instagram.com/ibm/?hl=en"},{"title":"IBM Newsroom","description":"News and press releases from around the IBM world. Media contacts. Sources by topic and by region. IBM Media center. Explore IBM\'s latest and most popular\xa0...","url":"https://newsroom.ibm.com/"}]'}

要获取接收结果列表，您可以执行以下单元格。

import json

output = json.loads(search_result.get("output"))
output

使用配置调用工具

要检查工具是否具有配置 schema 并查看其属性，您可以查看工具的 tool_config_schema。

在此示例中，该工具具有一个配置 schema，其中包含 maxResults 参数，用于设置要返回的最大结果数量。

google_search.tool_config_schema

{'title': 'config schema for GoogleSearch tool',
 'type': 'object',
 'properties': {'maxResults': {'title': 'Max number of results to return',
   'type': 'integer',
   'minimum': 1,
   'maximum': 20}}}

要设置 tool_config 参数，您需要使用 set_tool_config() 方法并根据上述 tool_config_schema 传递正确的 dict。

import json

config = {"maxResults": 3}
google_search.set_tool_config(config)

search_result = google_search.invoke(input="IBM")
output = json.loads(search_result.get("output"))

最多应有 3 个结果。

print(len(output))

3

使用输入 schema 调用工具

为了示例目的，我们需要获取另一个工具（带有一个输入 schema）。

weather_tool = watsonx_toolkit.get_tool("Weather")

要检查工具是否具有输入 schema 并查看其属性，您可以查看工具的 tool_input_schema。

在此示例中，该工具具有一个输入 schema，其中包含一个必需参数和一个可选参数。

weather_tool.tool_input_schema

{'type': 'object',
 'properties': {'location': {'title': 'location',
   'description': 'Name of the location',
   'type': 'string'},
  'country': {'title': 'country',
   'description': 'Name of the state or country',
   'type': 'string'}},
 'required': ['location']}

要正确地将输入传递给 invoke()，您需要创建一个 invoke_input 字典，其中包含必需参数作为键及其值。

invoke_input = {
    "location": "New York",
}

weather_result = weather_tool.invoke(input=invoke_input)
weather_result

{'output': 'Current weather in New York:\nTemperature: 0°C\nRain: 0mm\nRelative humidity: 63%\nWind: 7.6km/h\n'}

这次输出是一个单一的字符串值。要获取并打印它，您可以执行以下单元格。

output = weather_result.get("output")
print(output)

Current weather in New York:
Temperature: 0°C
Rain: 0mm
Relative humidity: 63%
Wind: 7.6km/h

使用 ToolCall 调用工具

我们也可以使用 ToolCall 调用工具，在这种情况下将返回 ToolMessage。

invoke_input = {
    "location": "Los Angeles",
}
tool_call = dict(
    args=invoke_input,
    id="1",
    name=weather_tool.name,
    type="tool_call",
)
weather_tool.invoke(input=tool_call)

ToolMessage(content='{"output": "Current weather in Los Angeles:\\nTemperature: 8.6°C\\nRain: 0mm\\nRelative humidity: 61%\\nWind: 8.4km/h\\n"}', name='Weather', tool_call_id='1')

在代理中使用

from langchain_ibm import ChatWatsonx

llm = ChatWatsonx(
    model_id="meta-llama/llama-3-3-70b-instruct",
    url="https://us-south.ml.cloud.ibm.com",
    project_id="PASTE YOUR PROJECT_ID HERE",
)

API 参考：ChatWatsonx

from langgraph.prebuilt import create_react_agent

tools = [weather_tool]
agent = create_react_agent(llm, tools)

API 参考：create_react_agent

example_query = "What is the weather in Boston?"

events = agent.stream(
    {"messages": [("user", example_query)]},
    stream_mode="values",
)
for event in events:
    event["messages"][-1].pretty_print()

================================ Human Message =================================

What is the weather in Boston?
================================== Ai Message ==================================
Tool Calls:
  Weather (chatcmpl-tool-6a6c21402c824e43bdd2e8ba390af4a8)
 Call ID: chatcmpl-tool-6a6c21402c824e43bdd2e8ba390af4a8
  Args:
    location: Boston
================================= Tool Message =================================
Name: Weather

{"output": "Current weather in Boston:\nTemperature: -1°C\nRain: 0mm\nRelative humidity: 53%\nWind: 8.3km/h\n"}
================================== Ai Message ==================================

The current weather in Boston is -1°C with 0mm of rain, a relative humidity of 53%, and a wind speed of 8.3km/h.

API 参考

有关 WatsonxToolkit 所有功能和配置的详细文档，请参阅 API 参考。

相关

• 工具概念指南
• 工具操作指南