Sarah Wooders 369cdf72c7 feat(core): store block metadata as YAML frontmatter in .md files (#9365)
* feat(core): store block metadata as YAML frontmatter in .md files

Block .md files in git repos now embed metadata (description, limit,
read_only, metadata dict) as YAML frontmatter instead of a separate
metadata/blocks.json file. Only non-default values are rendered.

Format:
  ---
  description: "Who I am"
  limit: 5000
  ---
  Block value content here...

Changes:
- New block_markdown.py utility (serialize_block / parse_block_markdown)
- Updated all three write/read paths: manager.py, memfs_client.py,
  memfs_client_base.py
- block_manager_git.py now passes description/limit/read_only/metadata
  through to git commits
- Post-push sync (git_http.py) parses frontmatter and syncs metadata
  fields to Postgres
- Removed metadata/blocks.json reads/writes entirely
- Backward compat: files without frontmatter treated as raw value
- Integration test verifies frontmatter in cloned files and metadata
  sync via git push

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix: derive frontmatter defaults from BaseBlock schema, not hardcoded dict

Remove _DEFAULTS dict from block_markdown.py. The core version now
imports BaseBlock and reads field defaults via model_fields. This
fixes the limit default (was 5000, should be CORE_MEMORY_BLOCK_CHAR_LIMIT=20000).

Also:
- memfs-py copy simplified to parse-only (no serialize, no letta imports)
- All hardcoded limit=5000 fallbacks replaced with CORE_MEMORY_BLOCK_CHAR_LIMIT
- Test updated: blocks with all-default metadata correctly have no frontmatter;
  frontmatter verified after setting non-default description via API

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix: always include description and limit in frontmatter

description and limit are always rendered in the YAML frontmatter,
even when at their default values. Only read_only and metadata are
conditional (omitted when at defaults).

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix: resolve read_only from block_update before git commit

read_only was using the old Postgres value instead of the update value
when committing to git. Also adds integration test coverage for
read_only: true appearing in frontmatter after API PATCH, and
verifying it's omitted when false (default).

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* test: add API→git round-trip coverage for description and limit

Verifies that PATCH description/limit via API is reflected in
frontmatter after git pull. Combined with the existing push→API
test (step 6), this gives full bidirectional coverage:
- API edit description/limit → pull → frontmatter updated
- Push frontmatter with description/limit → API reflects changes

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

---------

Co-authored-by: Letta <noreply@letta.com>
2026-02-24 10:52:07 -08:00
2024-12-10 19:20:27 -08:00
2025-04-21 08:43:29 -07:00
2026-02-24 10:52:06 -08:00
2024-12-27 11:28:00 +04:00
2024-07-04 14:45:35 -07:00
2024-10-11 15:51:14 -07:00
2024-11-06 23:00:17 -08:00
2025-05-13 15:32:09 -07:00
2026-01-18 13:50:17 -08:00

Letta logo

Letta (formerly MemGPT)

Letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve over time.

  • Letta Code: run agents locally in your terminal
  • Letta API: build agents into your applications

Get started in the CLI

Requires Node.js 18+

  1. Install the Letta Code CLI tool: npm install -g @letta-ai/letta-code
  2. Run letta in your terminal to launch an agent with memory running on your local computer

When running the CLI tool, your agent help you code and do any task you can do on your computer.

Letta Code supports skills and subagents, and bundles pre-built skills/subagents for advanced memory and continual learning. Letta is fully model-agnostic, though we recommend Opus 4.5 and GPT-5.2 for best performance (see our model leaderboard for our rankings).

Get started with the Letta API

Use the Letta API to integrate stateful agents into your own applications. Letta has a full-featured agents API, and a Python and Typescript SDK (view our API reference).

Installation

TypeScript / Node.js:

npm install @letta-ai/letta-client

Python:

pip install letta-client

Hello World example

Below is a quick example of creating a stateful agent and sending it a message (requires a Letta API key). See the full quickstart guide for complete documentation.

TypeScript:

import Letta from "@letta-ai/letta-client";

const client = new Letta({ apiKey: process.env.LETTA_API_KEY });

// Create your agent
const agentState = await client.agents.create({
  model: "openai/gpt-5.2",
  memory_blocks: [
    {
      label: "human",
      value:
        "Name: Timber. Status: dog. Occupation: building Letta, infrastructure to democratize self-improving superintelligence",
    },
    {
      label: "persona",
      value:
        "I am a self-improving superintelligence. Timber is my best friend and collaborator.",
    },
  ],
  tools: ["web_search", "fetch_webpage"],
});

console.log("Agent created with ID:", agentState.id);

// Send your agent a message
const response = await client.agents.messages.create(agentState.id, {
  input: "What do you know about me?",
});

for (const message of response.messages) {
  console.log(message);
}

Python:

from letta_client import Letta
import os

client = Letta(api_key=os.getenv("LETTA_API_KEY"))

# Create your agent
agent_state = client.agents.create(
    model="openai/gpt-5.2",
    memory_blocks=[
        {
          "label": "human",
          "value": "Name: Timber. Status: dog. Occupation: building Letta, infrastructure to democratize self-improving superintelligence"
        },
        {
          "label": "persona",
          "value": "I am a self-improving superintelligence. Timber is my best friend and collaborator."
        }
    ],
    tools=["web_search", "fetch_webpage"]
)

print(f"Agent created with ID: {agent_state.id}")

# Send your agent a message
response = client.agents.messages.create(
    agent_id=agent_state.id,
    input="What do you know about me?"
)

for message in response.messages:
    print(message)

Contributing

Letta is an open source project built by over a hundred contributors from around the world. There are many ways to get involved in the Letta OSS project!


Legal notices: By using Letta and related Letta services (such as the Letta endpoint or hosted service), you are agreeing to our privacy policy and terms of service.

Description
letta-server - primary development repo
Readme Cite this repository 146 MiB
Languages
Python 99.5%