IBM watsonx.ai

WatsonxToolkit 是 IBM watsonx.ai Toolkit 的包装器。

此示例演示如何使用watsonx.aiToolkit 使用LangChain.

概述

集成详细信息

类	包	序列化	JS 支持	软件包下载	最新包装
WatsonxToolkit	langchain-ibm	❌	✅

设置

要访问 IBM watsonx.ai 工具包，您需要创建一个 IBM watsonx.ai 帐户，获取 API 密钥，并安装langchain-ibm集成包。

凭据

此单元定义使用 watsonx Toolkit 所需的 WML 凭证。

行动：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：

!pip install -qU langchain-ibm

实例

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对象复制到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

可以将所有可用工具作为WatsonxTool对象。

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>)]

获取工具

您还可以获取特定的WatsonxTool按名称。

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

调用

使用简单的输入调用工具

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/"}]'}

要获取接收结果的列表，您可以执行以下单元格。

import json

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

使用配置

要检查工具是否具有配置架构并查看其属性，您可以查看该工具的tool_config_schema.

在此示例中，该工具具有一个 config 架构，其中包含maxResults参数设置要返回的最大结果数。

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()方法并传递 correctdict根据上述tool_config_schema.

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"))

应该最多有 3 个结果。

print(len(output))

使用输入架构调用工具

我们需要获取另一个工具（带有输入架构）来用于示例目的。

weather_tool = watsonx_toolkit.get_tool("Weather")

要检查工具是否具有输入架构并查看其属性，您可以查看该工具的tool_input_schema.

在此示例中，该工具具有一个输入方案，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']}

要将输入正确地传递给invoke()，您需要创建一个invoke_input字典，其中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'}

这次输出是单个字符串值。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

我们还可以使用 ToolCall 调用该工具，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')

在代理内使用

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()

================================[1m Human Message [0m=================================

What is the weather in Boston?
==================================[1m Ai Message [0m==================================
Tool Calls:
  Weather (chatcmpl-tool-6a6c21402c824e43bdd2e8ba390af4a8)
 Call ID: chatcmpl-tool-6a6c21402c824e43bdd2e8ba390af4a8
  Args:
    location: Boston
=================================[1m Tool Message [0m=================================
Name: Weather

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

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

有关所有WatsonxToolkit功能和配置可参考 API 参考。

工具概念指南
工具操作指南

概述