OpaquePrompts

OpaquePrompts 是一項服務，使應用程式能夠利用語言模型的力量，而不會損害用戶隱私。 OpaquePrompts 專為可組合性和易於整合到現有應用程式和服務而設計，可透過簡單的 Python 程式庫以及 LangChain 使用。更重要的是，OpaquePrompts 利用機密運算的力量，確保即使是 OpaquePrompts 服務本身也無法存取其保護的資料。

此筆記本介紹如何使用 LangChain 與 OpaquePrompts 互動。

# install the opaqueprompts and langchain packages
%pip install --upgrade --quiet  opaqueprompts langchain

存取 OpaquePrompts API 需要 API 密鑰，您可以透過在OpaquePrompts 網站上建立帳戶來取得。建立帳戶後，您可以在API 密鑰頁面上找到您的 API 密鑰。

import os

# Set API keys

os.environ["OPAQUEPROMPTS_API_KEY"] = "<OPAQUEPROMPTS_API_KEY>"
os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>"

使用 OpaquePrompts LLM 包裝器 (Use OpaquePrompts LLM Wrapper)

將 OpaquePrompts 應用於您的應用程式可能就像使用 OpaquePrompts 類別包裝您的 LLM 一樣簡單，方法是用 llm=OpaquePrompts(base_llm=OpenAI()) 替換 llm=OpenAI()。

from langchain.chains import LLMChain
from langchain.globals import set_debug, set_verbose
from langchain.memory import ConversationBufferWindowMemory
from langchain_community.llms import OpaquePrompts
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

set_debug(True)
set_verbose(True)

prompt_template = """
As an AI assistant, you will answer questions according to given context.

Sensitive personal information in the question is masked for privacy.
For instance, if the original text says "Giana is good," it will be changed
to "PERSON_998 is good." 

Here's how to handle these changes:
* Consider these masked phrases just as placeholders, but still refer to
them in a relevant way when answering.
* It's possible that different masked terms might mean the same thing.
Stick with the given term and don't modify it.
* All masked terms follow the "TYPE_ID" pattern.
* Please don't invent new masked terms. For instance, if you see "PERSON_998,"
don't come up with "PERSON_997" or "PERSON_999" unless they're already in the question.

Conversation History: \`\`\`{history}\`\`\`
Context : \`\`\`During our recent meeting on February 23, 2023, at 10:30 AM,
John Doe provided me with his personal details. His email is johndoe@example.com
and his contact number is 650-456-7890. He lives in New York City, USA, and
belongs to the American nationality with Christian beliefs and a leaning towards
the Democratic party. He mentioned that he recently made a transaction using his
credit card 4111 1111 1111 1111 and transferred bitcoins to the wallet address
1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa. While discussing his European travels, he noted
down his IBAN as GB29 NWBK 6016 1331 9268 19. Additionally, he provided his website
as https://johndoeportfolio.com. John also discussed some of his US-specific details.
He said his bank account number is 1234567890123456 and his drivers license is Y12345678.
His ITIN is 987-65-4321, and he recently renewed his passport, the number for which is
123456789. He emphasized not to share his SSN, which is 123-45-6789. Furthermore, he
mentioned that he accesses his work files remotely through the IP 192.168.1.1 and has
a medical license number MED-123456. \`\`\`
Question: \`\`\`{question}\`\`\`

"""

chain = LLMChain(
    prompt=PromptTemplate.from_template(prompt_template),
    llm=OpaquePrompts(base_llm=OpenAI()),
    memory=ConversationBufferWindowMemory(k=2),
    verbose=True,
)


print(
    chain.run(
        {
            "question": """Write a message to remind John to do password reset for his website to stay secure."""
        },
        callbacks=[StdOutCallbackHandler()],
    )
)

從輸出中，您可以看到來自用戶輸入的以下上下文具有敏感數據。

# Context from user input

During our recent meeting on February 23, 2023, at 10:30 AM, John Doe provided me with his personal details. His email is johndoe@example.com and his contact number is 650-456-7890. He lives in New York City, USA, and belongs to the American nationality with Christian beliefs and a leaning towards the Democratic party. He mentioned that he recently made a transaction using his credit card 4111 1111 1111 1111 and transferred bitcoins to the wallet address 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa. While discussing his European travels, he noted down his IBAN as GB29 NWBK 6016 1331 9268 19. Additionally, he provided his website as https://johndoeportfolio.com. John also discussed some of his US-specific details. He said his bank account number is 1234567890123456 and his drivers license is Y12345678. His ITIN is 987-65-4321, and he recently renewed his passport, the number for which is 123456789. He emphasized not to share his SSN, which is 669-45-6789. Furthermore, he mentioned that he accesses his work files remotely through the IP 192.168.1.1 and has a medical license number MED-123456.

OpaquePrompts 將自動檢測敏感數據並將其替換為佔位符。

# Context after OpaquePrompts

During our recent meeting on DATE_TIME_3, at DATE_TIME_2, PERSON_3 provided me with his personal details. His email is EMAIL_ADDRESS_1 and his contact number is PHONE_NUMBER_1. He lives in LOCATION_3, LOCATION_2, and belongs to the NRP_3 nationality with NRP_2 beliefs and a leaning towards the Democratic party. He mentioned that he recently made a transaction using his credit card CREDIT_CARD_1 and transferred bitcoins to the wallet address CRYPTO_1. While discussing his NRP_1 travels, he noted down his IBAN as IBAN_CODE_1. Additionally, he provided his website as URL_1. PERSON_2 also discussed some of his LOCATION_1-specific details. He said his bank account number is US_BANK_NUMBER_1 and his drivers license is US_DRIVER_LICENSE_2. His ITIN is US_ITIN_1, and he recently renewed his passport, the number for which is DATE_TIME_1. He emphasized not to share his SSN, which is US_SSN_1. Furthermore, he mentioned that he accesses his work files remotely through the IP IP_ADDRESS_1 and has a medical license number MED-US_DRIVER_LICENSE_1.

佔位符用於 LLM 回應中。

# response returned by LLM

Hey PERSON_1, just wanted to remind you to do a password reset for your website URL_1 through your email EMAIL_ADDRESS_1. It's important to stay secure online, so don't forget to do it!

通過將佔位符替換為原始敏感數據來取消對回應的清理。

# desanitized LLM response from OpaquePrompts

Hey John, just wanted to remind you to do a password reset for your website https://johndoeportfolio.com through your email johndoe@example.com. It's important to stay secure online, so don't forget to do it!

在 LangChain 表達式中使用 OpaquePrompts (Use OpaquePrompts in LangChain expression)

如果直接替換不能提供您需要的靈活性，則還有一些可以與 LangChain 表達式一起使用的函數。

import langchain_community.utilities.opaqueprompts as op
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnablePassthrough

prompt = (PromptTemplate.from_template(prompt_template),)
llm = OpenAI()
pg_chain = (
    op.sanitize
    | RunnablePassthrough.assign(
        response=(lambda x: x["sanitized_input"]) | prompt | llm | StrOutputParser(),
    )
    | (lambda x: op.desanitize(x["response"], x["secure_context"]))
)

pg_chain.invoke(
    {
        "question": "Write a text message to remind John to do password reset for his website through his email to stay secure.",
        "history": "",
    }
)

API 參考：StrOutputParser | RunnablePassthrough

LLM 概念指南
LLM 操作指南

使用 OpaquePrompts LLM 包裝器 (Use OpaquePrompts LLM Wrapper)

在 LangChain 表達式中使用 OpaquePrompts (Use OpaquePrompts in LangChain expression)

相關​

此頁面是否有幫助？ (Was this page helpful?)

相關