이 노트북은 AI21 chat model을 시작하는 방법을 다룹니다. 서로 다른 chat model은 서로 다른 parameter를 지원한다는 점에 유의하세요. 선택한 model의 parameter에 대해 자세히 알아보려면 AI21 문서를 참조하세요. AI21의 모든 LangChain component를 확인하세요.

​
Integration 세부 정보

ClassPackageLocalSerializableJS supportDownloadsVersion
ChatAI21langchain-ai21❌beta✅PyPI - DownloadsPyPI - Version

​
Model 기능

Tool callingStructured outputJSON modeImage inputAudio inputVideo inputToken-level streamingNative asyncToken usageLogprobs
✅✅❌❌❌❌✅✅✅❌

​
Setup

​
Credentials

AI21 API key를 받아서 AI21_API_KEY environment variable을 설정해야 합니다: 
import os
from getpass import getpass

if "AI21_API_KEY" not in os.environ:
    os.environ["AI21_API_KEY"] = getpass()
model 호출의 자동 추적을 활성화하려면 LangSmith API key를 설정하세요: 
os.environ["LANGSMITH_TRACING"] = "true"
os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")

​
Installation

!pip install -qU langchain-ai21

​
Instantiation

이제 model object를 인스턴스화하고 chat completion을 생성할 수 있습니다: 
from langchain_ai21 import ChatAI21

llm = ChatAI21(model="jamba-instruct", temperature=0)

​
Invocation

messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg

​
Tool Calls / Function Calling

이 예제는 AI21 model에서 tool calling을 사용하는 방법을 보여줍니다: 
import os
from getpass import getpass

from langchain_ai21.chat_models import ChatAI21
from langchain.messages import HumanMessage, SystemMessage, ToolMessage
from langchain.tools import tool
from langchain_core.utils.function_calling import convert_to_openai_tool

if "AI21_API_KEY" not in os.environ:
    os.environ["AI21_API_KEY"] = getpass()


@tool
def get_weather(location: str, date: str) -> str:
    """“Provide the weather for the specified location on the given date.”"""
    if location == "New York" and date == "2024-12-05":
        return "25 celsius"
    elif location == "New York" and date == "2024-12-06":
        return "27 celsius"
    elif location == "London" and date == "2024-12-05":
        return "22 celsius"
    return "32 celsius"


llm = ChatAI21(model="jamba-1.5-mini")

llm_with_tools = llm.bind_tools([convert_to_openai_tool(get_weather)])

chat_messages = [
    SystemMessage(
        content="You are a helpful assistant. You can use the provided tools "
        "to assist with various tasks and provide accurate information"
    )
]

human_messages = [
    HumanMessage(
        content="What is the forecast for the weather in New York on December 5, 2024?"
    ),
    HumanMessage(content="And what about the 2024-12-06?"),
    HumanMessage(content="OK, thank you."),
    HumanMessage(content="What is the expected weather in London on December 5, 2024?"),
]


for human_message in human_messages:
    print(f"User: {human_message.content}")
    chat_messages.append(human_message)
    response = llm_with_tools.invoke(chat_messages)
    chat_messages.append(response)
    if response.tool_calls:
        tool_call = response.tool_calls[0]
        if tool_call["name"] == "get_weather":
            weather = get_weather.invoke(
                {
                    "location": tool_call["args"]["location"],
                    "date": tool_call["args"]["date"],
                }
            )
            chat_messages.append(
                ToolMessage(content=weather, tool_call_id=tool_call["id"])
            )
            llm_answer = llm_with_tools.invoke(chat_messages)
            print(f"Assistant: {llm_answer.content}")
    else:
        print(f"Assistant: {response.content}")

​
API reference

모든 ChatAI21 기능 및 구성에 대한 자세한 문서는 API reference를 참조하세요: python.langchain.com/api_reference/ai21/chat_models/langchain_ai21.chat_models.ChatAI21.html
Edit the source of this page on GitHub.
Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.
⌘I