ChatWatsonx

ChatWatsonx 是 IBM watsonx.ai 基础模型的包装器。

这些示例的目的是演示如何与watsonx.ai使用LangChainLLM API 的 API 中。

概述

集成详细信息

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

模型特点

工具调用	结构化输出	JSON 模式	图像输入	音频输入	视频输入	令牌级流式处理	本机异步	Token 使用情况	日志
✅	✅	✅	✅	❌	❌	✅	❌	✅	✅

设置

要访问 IBM watsonx.ai 模型，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

下面的单元格定义了使用 watsonx Foundation 模型推理所需的凭证。

行动：提供 IBM Cloud 用户 API 密钥。有关详细信息，请参阅管理用户 API 密钥。

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 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：

!pip install -qU langchain-ibm

实例

您可能需要调整模型parameters针对不同的模型或任务。有关详细信息，请参阅可用的 TextChatParameters。

parameters = {
    "temperature": 0.9,
    "max_tokens": 200,
}

初始化WatsonxLLMclass 替换为之前设置的参数。

注意：

要为 API 调用提供上下文，您必须传递project_id或space_id.要获取您的项目或空间 ID，请打开您的项目或空间，转到 Manage 选项卡，然后单击 General。有关更多信息，请参阅：项目文档或 Deployment Space 文档。
根据预置服务实例的区域，请使用 watsonx.ai API 身份验证中列出的 URL 之一。

在此示例中，我们将使用project_id和达拉斯 URL。

您需要指定model_id这将用于推理。您可以在支持的聊天模型.

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,
)

API 参考：ChatWatsonx

或者，您可以使用 Cloud Pak for Data 凭证。有关详细信息，请参阅 watsonx.ai 软件设置。

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,
)

而不是model_id，您还可以将deployment_id之前部署的模型。

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,
)

对于某些要求，可以选择将 IBM 的APIClient对象复制到ChatWatsonx类。

from ibm_watsonx_ai import APIClient

api_client = APIClient(...)

chat = ChatWatsonx(
    model_id="ibm/granite-34b-code-instruct",
    watsonx_client=api_client,
)

调用

要获得完成，您可以使用字符串提示直接调用模型。

# Invocation

messages = [
    ("system", "You are a helpful assistant that translates English to French."),
    (
        "human",
        "I love you for listening to Rock.",
    ),
]

chat.invoke(messages)

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})

# Invocation multiple chat
from langchain_core.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])

API 参考：HumanMessage | SystemMessage 系统

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})

链接

创造ChatPromptTemplate对象，这些对象将负责创建一个随机问题。

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)])

API 参考：ChatPromptTemplate

提供 inputs 并运行链。

chain = prompt | chat
chain.invoke(
    {
        "input_language": "English",
        "output_language": "German",
        "input": "I love Python",
    }
)

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})

流式处理 Model 输出

您可以流式传输模型输出。

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="")

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

批处理 Model 输出

您可以对模型输出进行批处理。

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])

[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（）

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,
)

API 参考：ChatWatsonx

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])

ai_msg = llm_with_tools.invoke(
    "Which city is hotter today: LA or NY?",
)
ai_msg

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

请注意，AIMessage 有一个tool_calls属性。这包含在与模型提供程序无关的标准化 ToolCall 格式中。

ai_msg.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'}]

API 参考

有关所有ChatWatsonx功能和配置可参考 API 参考。

聊天模型概念指南
聊天模型操作指南

概述