Getting Thread Message History in Azure AI Foundry with Python (furotmark.github.io)

This piece shows how to fetch thread message history from Azure AI Foundry using Python—an essential capability for debugging agents, surfacing conversation context, or implementing agent memory. You install azure-ai-projects, azure-ai-agents and azure-identity, then create an AIProjectClient with DefaultAzureCredential and your project endpoint. Obtain the thread_id either by persisting it when you create threads in code or by looking it up in the Foundry portal, then call agents_client.messages.list(thread_id=thread_id) to iterate the messages asynchronously. A key technical detail: the list method’s limit parameter controls only the per-request page size, not the total number of messages returned—so limit=3 will still traverse the whole history in 3-item batches. To genuinely restrict processing (and reduce API work), page through messages with messages.by_page() and break after you’ve processed the first N items or pages. Practical implications: use paging to control latency, cost, and memory, persist thread IDs for reliable lookup, and handle async iteration patterns in your app to avoid unexpected full-history scans.