AzureAIMemoryRetriever

LangChain retriever that queries Foundry Memory with multi-turn context.

This retriever is designed for close coupling with AzureAIMemoryChatMessageHistory. When bound to a history instance via history_ref, it provides incremental search capabilities with multi-turn conversation context. Use standalone mode only for one-off queries without conversation context.

This retriever queries Azure AI Foundry Memory, supporting both standalone retrieval and history-bound incremental search with previous_search_id.

Examples

Standalone retriever (one-off search without context):

from azure.identity import DefaultAzureCredential

retriever = AzureAIMemoryRetriever(
    project_endpoint="https://myproject.api.azureml.ms",
    credential=DefaultAzureCredential(),
    store_name="my_store",
    scope="user:123",
    k=5,
)
docs = retriever.invoke("What are my coffee preferences?")

With endpoint from environment variable:

retriever = AzureAIMemoryRetriever(
    store_name="my_store",
    scope="user:123",
    k=5,
)
docs = retriever.invoke("What are my preferences?")

History-bound retriever (recommended):

from langchain_core.chat_history import InMemoryChatMessageHistory
from langchain_azure_ai.chat_history import (
    AzureAIMemoryChatMessageHistory,
)

history = AzureAIMemoryChatMessageHistory(
    project_endpoint="https://myproject.api.azureml.ms",
    store_name="my_store",
    scope="user:123",
    base_history=InMemoryChatMessageHistory(),
)
retriever = history.get_retriever(k=5)
docs = retriever.invoke("Tell me more")