Sarah Wooders adab8cd9b5 feat: add MiniMax provider support (#9095)
* feat: add MiniMax provider support

Add MiniMax as a new LLM provider using their Anthropic-compatible API.

Key implementation details:
- Uses standard messages API (not beta) - MiniMax supports thinking blocks natively
- Base URL: https://api.minimax.io/anthropic
- Models: MiniMax-M2.1, MiniMax-M2.1-lightning, MiniMax-M2 (all 200K context, 128K output)
- Temperature clamped to valid range (0.0, 1.0]
- All M2.x models treated as reasoning models (support interleaved thinking)

Files added:
- letta/schemas/providers/minimax.py - MiniMax provider schema
- letta/llm_api/minimax_client.py - Client extending AnthropicClient
- tests/test_minimax_client.py - Unit tests (13 tests)
- tests/model_settings/minimax-m2.1.json - Integration test config

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

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

* chore: regenerate API spec with MiniMax provider

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

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

* chore: use MiniMax-M2.1-lightning for CI tests

Switch to the faster/cheaper lightning model variant for integration tests.

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

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

* chore: add MINIMAX_API_KEY to deploy-core command

Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>

* chore: regenerate web openapi spec with MiniMax provider

Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>

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

---------

Co-authored-by: Letta <noreply@letta.com>
Co-authored-by: letta-code <248085862+letta-code@users.noreply.github.com>
Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
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  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

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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

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