LangChain Integration

pip install langchain-ambientmeta

from langchain_ambientmeta import PrivacyLLM
from langchain_openai import ChatOpenAI

# Wrap your LLM with privacy protection
safe_llm = PrivacyLLM(
    llm=ChatOpenAI(model="gpt-4"),
    api_key="am_live_xxx",
)

# Use normally — PII is automatically handled
response = safe_llm.invoke("Summarize John Smith's file at john@acme.com")
# OpenAI never sees the real PII

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_template("Answer this question: {query}")
chain = prompt | safe_llm

result = chain.invoke({"query": "What is John Smith's email?"})

from langchain.chains import create_retrieval_chain
from langchain.chains.combine_documents import create_stuff_documents_chain
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_template(
    "Answer the question based on context:\n{context}\n\nQuestion: {input}"
)
combine_chain = create_stuff_documents_chain(safe_llm, prompt)
rag_chain = create_retrieval_chain(your_retriever, combine_chain)

result = rag_chain.invoke({"input": "Find information about employee EMP-123456"})

safe_llm = PrivacyLLM(
    llm=ChatOpenAI(model="gpt-4"),
    api_key="am_live_xxx",
    entities=["PERSON", "EMAIL_ADDRESS", "SSN"],  # Optional: specific entities only
    auto_rehydrate=True,   # Automatically restore PII in responses (default: True)
)