ChatWatsonx 是 IBM watsonx.ai 基础模型的封装器。以下示例旨在展示如何通过
LangChain LLMs API 与 watsonx.ai 模型进行通信。
概述
集成详情
| 类 | 包 | 可序列化 | JS 支持 | 下载量 | 版本 |
|---|---|---|---|---|---|
ChatWatsonx | langchain-ibm | ❌ | ✅ |
模型功能
| 工具调用 | 结构化输出 | 图像输入 | 音频输入 | 视频输入 | Token 级流式输出 | 原生异步 | Token 用量 | 对数概率 |
|---|---|---|---|---|---|---|---|---|
| ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ✅ | ✅ |
设置
要访问 IBM watsonx.ai 模型,您需要创建 IBM watsonx.ai 账户、获取 API 密钥,并安装langchain-ibm 集成包。
凭据
以下代码块定义了使用 watsonx 基础模型推理所需的凭据。 操作: 提供 IBM Cloud 用户 API 密钥。详情请参阅 管理用户 API 密钥。Copy
import os
from getpass import getpass
watsonx_api_key = getpass()
os.environ["WATSONX_APIKEY"] = watsonx_api_key
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import os
os.environ["WATSONX_URL"] = "your service instance url"
os.environ["WATSONX_TOKEN"] = "your token for accessing the CLOUD or 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"
安装
LangChain IBM 集成位于langchain-ibm 包中:
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!pip install -qU langchain-ibm
实例化
针对不同模型或任务,您可能需要调整模型的parameters。详情请参阅 可用的 TextChatParameters。
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parameters = {
"temperature": 0.9,
"max_tokens": 200,
}
WatsonxLLM 类。
注意:
- 要为 API 调用提供上下文,您必须传入
project_id或space_id。要获取项目或空间 ID,请打开您的项目或空间,转到 管理 选项卡,然后点击 常规。更多信息请参阅:项目文档 或 部署空间文档。 - 根据您所配置服务实例的区域,请使用 watsonx.ai API 认证 中列出的相应 URL。
project_id 和 Dallas URL。
您需要指定用于推理的 model_id。所有可用模型列表请参阅 支持的聊天模型。
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from langchain_ibm import ChatWatsonx
chat = ChatWatsonx(
model_id="ibm/granite-34b-code-instruct",
url="https://us-south.ml.cloud.ibm.com",
project_id="PASTE YOUR PROJECT_ID HERE",
params=parameters,
)
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chat = ChatWatsonx(
model_id="ibm/granite-34b-code-instruct",
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=parameters,
)
model_id 外,您也可以传入此前已部署的带有 Prompt Template 引用的模型的 deployment_id。
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chat = ChatWatsonx(
deployment_id="PASTE YOUR DEPLOYMENT_ID HERE",
url="https://us-south.ml.cloud.ibm.com",
project_id="PASTE YOUR PROJECT_ID HERE",
params=parameters,
)
APIClient 对象传入 ChatWatsonx 类。
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from ibm_watsonx_ai import APIClient
api_client = APIClient(...)
chat = ChatWatsonx(
model_id="ibm/granite-34b-code-instruct",
watsonx_client=api_client,
)
调用
要获取补全结果,您可以直接使用字符串提示调用模型。Copy
# Invocation
messages = [
("system", "You are a helpful assistant that translates English to French."),
(
"human",
"I love you for listening to Rock.",
),
]
chat.invoke(messages)
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AIMessage(content="J'adore que tu escois de écouter de la rock ! ", additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 19, 'prompt_tokens': 34, 'total_tokens': 53}, 'model_name': 'ibm/granite-34b-code-instruct', 'system_fingerprint': '', 'finish_reason': 'stop'}, id='chat-ef888fc41f0d4b37903b622250ff7528', usage_metadata={'input_tokens': 34, 'output_tokens': 19, 'total_tokens': 53})
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# Invocation multiple chat
from langchain.messages import (
HumanMessage,
SystemMessage,
)
system_message = SystemMessage(
content="You are a helpful assistant which telling short-info about provided topic."
)
human_message = HumanMessage(content="horse")
chat.invoke([system_message, human_message])
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AIMessage(content='horses are quadrupedal mammals that are members of the family Equidae. They are typically farm animals, competing in horse racing and other forms of equine competition. With over 200 breeds, horses are diverse in their physical appearance and behavior. They are intelligent, social animals that are often used for transportation, food, and entertainment.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 89, 'prompt_tokens': 29, 'total_tokens': 118}, 'model_name': 'ibm/granite-34b-code-instruct', 'system_fingerprint': '', 'finish_reason': 'stop'}, id='chat-9a6e28abb3d448aaa4f83b677a9fd653', usage_metadata={'input_tokens': 29, 'output_tokens': 89, 'total_tokens': 118})
链式调用
创建ChatPromptTemplate 对象,负责生成随机问题。
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from langchain_core.prompts import ChatPromptTemplate
system = (
"You are a helpful assistant that translates {input_language} to {output_language}."
)
human = "{input}"
prompt = ChatPromptTemplate.from_messages([("system", system), ("human", human)])
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chain = prompt | chat
chain.invoke(
{
"input_language": "English",
"output_language": "German",
"input": "I love Python",
}
)
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AIMessage(content='Ich liebe Python.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 7, 'prompt_tokens': 28, 'total_tokens': 35}, 'model_name': 'ibm/granite-34b-code-instruct', 'system_fingerprint': '', 'finish_reason': 'stop'}, id='chat-fef871190b6047a7a3e68c58b3810c33', usage_metadata={'input_tokens': 28, 'output_tokens': 7, 'total_tokens': 35})
流式输出模型结果
您可以对模型输出进行流式处理。Copy
system_message = SystemMessage(
content="You are a helpful assistant which telling short-info about provided topic."
)
human_message = HumanMessage(content="moon")
for chunk in chat.stream([system_message, human_message]):
print(chunk.content, end="")
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The Moon is the fifth largest moon in the solar system and the largest relative to its host planet. It is the fifth brightest object in Earth's night sky after the Sun, the stars, the Milky Way, and the Moon itself. It orbits around the Earth at an average distance of 238,855 miles (384,400 kilometers). The Moon's gravity is about one-sixthth of Earth's and thus allows for the formation of tides on Earth. The Moon is thought to have formed around 4.5 billion years ago from debris from a collision between Earth and a Mars-sized body named Theia. The Moon is effectively immutable, with its current characteristics remaining from formation. Aside from Earth, the Moon is the only other natural satellite of Earth. The most widely accepted theory is that it formed from the debris of a collision
批量处理模型输出
您可以对模型输出进行批量处理。Copy
message_1 = [
SystemMessage(
content="You are a helpful assistant which telling short-info about provided topic."
),
HumanMessage(content="cat"),
]
message_2 = [
SystemMessage(
content="You are a helpful assistant which telling short-info about provided topic."
),
HumanMessage(content="dog"),
]
chat.batch([message_1, message_2])
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[AIMessage(content='The cat is a popular domesticated carnivorous mammal that belongs to the family Felidae. Cats arefriendly, intelligent, and independent animals that are well-known for their playful behavior, agility, and ability to hunt prey. cats come in a wide range of breeds, each with their own unique physical and behavioral characteristics. They are kept as pets worldwide due to their affectionate nature and companionship. Cats are important members of the household and are often involved in everything from childcare to entertainment.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 127, 'prompt_tokens': 28, 'total_tokens': 155}, 'model_name': 'ibm/granite-34b-code-instruct', 'system_fingerprint': '', 'finish_reason': 'stop'}, id='chat-fa452af0a0fa4a668b6a704aecd7d718', usage_metadata={'input_tokens': 28, 'output_tokens': 127, 'total_tokens': 155}),
AIMessage(content='Dogs are domesticated animals that belong to the Canidae family, also known as wolves. They are one of the most popular pets worldwide, known for their loyalty and affection towards their owners. Dogs come in various breeds, each with unique characteristics, and are trained for different purposes such as hunting, herding, or guarding. They require a lot of exercise and mental stimulation to stay healthy and happy, and they need proper training and socialization to be well-behaved. Dogs are also known for their playful and energetic nature, making them great companions for people of all ages.', additional_kwargs={}, response_metadata={'token_usage': {'completion_tokens': 144, 'prompt_tokens': 28, 'total_tokens': 172}, 'model_name': 'ibm/granite-34b-code-instruct', 'system_fingerprint': '', 'finish_reason': 'stop'}, id='chat-cae7663c50cf4f3499726821cc2f0ec7', usage_metadata={'input_tokens': 28, 'output_tokens': 144, 'total_tokens': 172})]
工具调用
ChatWatsonx.bind_tools()
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from langchain_ibm import ChatWatsonx
chat = ChatWatsonx(
model_id="mistralai/mistral-large",
url="https://us-south.ml.cloud.ibm.com",
project_id="PASTE YOUR PROJECT_ID HERE",
params=parameters,
)
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from pydantic import BaseModel, Field
class GetWeather(BaseModel):
"""Get the current weather in a given location"""
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
llm_with_tools = chat.bind_tools([GetWeather])
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ai_msg = llm_with_tools.invoke(
"Which city is hotter today: LA or NY?",
)
ai_msg
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AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'chatcmpl-tool-6c06a19bbe824d78a322eb193dbde12d', 'type': 'function', 'function': {'name': 'GetWeather', 'arguments': '{"location": "Los Angeles, CA"}'}}, {'id': 'chatcmpl-tool-493542e46f1141bfbfeb5deae6c9e086', 'type': 'function', 'function': {'name': 'GetWeather', 'arguments': '{"location": "New York, NY"}'}}]}, response_metadata={'token_usage': {'completion_tokens': 46, 'prompt_tokens': 95, 'total_tokens': 141}, 'model_name': 'mistralai/mistral-large', 'system_fingerprint': '', 'finish_reason': 'tool_calls'}, id='chat-027f2bdb217e4238909cb26d3e8a8fbf', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'chatcmpl-tool-6c06a19bbe824d78a322eb193dbde12d', 'type': 'tool_call'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'chatcmpl-tool-493542e46f1141bfbfeb5deae6c9e086', 'type': 'tool_call'}], usage_metadata={'input_tokens': 95, 'output_tokens': 46, 'total_tokens': 141})
AIMessage.tool_calls
注意,AIMessage 具有 tool_calls 属性。它以标准化的 ToolCall 格式包含工具调用信息,与模型提供商无关。
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ai_msg.tool_calls
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[{'name': 'GetWeather',
'args': {'location': 'Los Angeles, CA'},
'id': 'chatcmpl-tool-6c06a19bbe824d78a322eb193dbde12d',
'type': 'tool_call'},
{'name': 'GetWeather',
'args': {'location': 'New York, NY'},
'id': 'chatcmpl-tool-493542e46f1141bfbfeb5deae6c9e086',
'type': 'tool_call'}]
API 参考
有关ChatWatsonx 所有功能和配置的详细文档,请前往 API 参考。
将这些文档连接到 Claude、VSCode 等,通过 MCP 获取实时解答。

