ChatPipeshift

這將幫助您開始使用 Pipeshift 聊天模型。如需所有 ChatPipeshift 功能和配置的詳細文件，請前往 API 參考。

概觀

整合詳細資訊

類別	套件	本地	可序列化	JS 支援	套件下載	套件最新版本
ChatPipeshift	langchain-pipeshift	❌	-	❌

模型功能

工具呼叫	結構化輸出	JSON 模式	圖像輸入	音訊輸入	視訊輸入	Token 層級串流	原生非同步	Token 使用量	Logprobs
❌	❌	✅	✅	❌	❌	✅	✅	✅	-

設定

若要存取 Pipeshift 模型，您需要於 Pipeshift 上建立帳戶、取得 API 金鑰，並安裝 langchain-pipeshift 整合套件。

憑證

前往 Pipeshift 註冊 Pipeshift 並產生 API 金鑰。完成後，設定 PIPESHIFT_API_KEY 環境變數

import getpass
import os

if not os.getenv("PIPESHIFT_API_KEY"):
    os.environ["PIPESHIFT_API_KEY"] = getpass.getpass("Enter your Pipeshift API key: ")

如果您想要取得模型呼叫的自動追蹤，您也可以設定您的 LangSmith API 金鑰，取消註解下方內容

# os.environ["LANGSMITH_TRACING"] = "true"
# os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")

安裝

LangChain Pipeshift 整合位於 langchain-pipeshift 套件中

%pip install -qU langchain-pipeshift

Note: you may need to restart the kernel to use updated packages.

實例化

現在我們可以實例化我們的模型物件並產生聊天完成

from langchain_pipeshift import ChatPipeshift

llm = ChatPipeshift(
    model="meta-llama/Meta-Llama-3.1-8B-Instruct",
    temperature=0,
    max_tokens=512,
    # other params...
)

調用

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

AIMessage(content='Here is the translation:\n\nJe suis amoureux du programme. \n\nHowever, a more common translation would be:\n\nJ\'aime programmer.\n\nNote that "Je suis amoureux" typically implies romantic love, whereas "J\'aime" is a more casual way to express affection or enjoyment for an activity, in this case, programming.', additional_kwargs={}, response_metadata={}, id='run-5cad8e5c-d089-44a8-8dcd-22736cde7d7b-0')

print(ai_msg.content)

Here is the translation:

Je suis amoureux du programme. 

However, a more common translation would be:

J'aime programmer.

Note that "Je suis amoureux" typically implies romantic love, whereas "J'aime" is a more casual way to express affection or enjoyment for an activity, in this case, programming.

串鏈

我們可以像這樣使用提示範本串鏈我們的模型

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

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

API 參考：ChatPromptTemplate

AIMessage(content="Das ist schön! Du liebst Programmieren! (That's great! You love programming!)\n\nWould you like to know the German translation of a specific programming-related term or phrase, or would you like me to help you with something else?", additional_kwargs={}, response_metadata={}, id='run-8a4b7d56-23d9-43a7-8fb2-e05f556d94bd-0')

API 參考

如需所有 ChatPipeshift 功能和配置的詳細文件，請前往 API 參考：https://dashboard.pipeshift.com/docs

相關內容

• 聊天模型概念指南
• 聊天模型操作指南