Show HN: Agent File (.af) – A standard file format for serializing AI agents

github.com

5 points by wooders 5 days ago

Hi HN - We’re building Agent File (.af), which makes it possible to re-create the exact same agent (including memories, tools, message history, configs, etc.) across different machines.

A big difference between LLMs and agents is that agents have associated state: system prompts, editable memory (personality and user information), tool configurations (code and schemas), and LLM/embedding model settings. While you can run the same LLM as someone else by downloading the weights, there’s no “representation” of agents that allows you to re-create an instance of an agent across services.

Agent File (.af) is an open standard file format for serializing stateful agents. Originally designed for the Letta framework, .af is a human-readable representation of all the associated state of an agent to reproduce the exact behavior and memories.

To demonstrate .af, we also made a few example agents with download links to .af:

- MemGPT: An agent with memory management tools for infinite context, as described in the MemGPT paper Deep Research: A research agent with planning, search, and memory tools to enable writing deep research reports from iterative research

- Customer Support: A customer support agent that has dummy tools for handling order cancellations, looking up order status, and also memory

- Stateless Workflow: A stateless graph workflow agent (no memory and deterministic tool calling) that evaluates recruiting candidates and drafts emails

- Composio Tools: An example of an agent that uses a Composio tool to star a GitHub repository

pacjam 5 days ago

If you're interested in the full schema you can look at the Pydantic models here: https://github.com/letta-ai/letta/blob/main/letta/serialize_...

Agent File is intended to support "one thread" agents, ie agents that have an indefinite conversation/event history, even if the underlying in-context message history is limited. That's why there's a distinction between just "messages" and "in-context messages" (a subset of messages).