Agent Native

letta-configuration

Configure LLM models on Letta agents by setting model handles, temperature, and token limits, and set up providers on Letta servers using API keys…

by LettaOfficial publisherNot reviewed

Identity proven by GitHub's verified organisation badge (letta-ai)

Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode
License
MIT (permissive)
Pin
6785511pinned Oct 9, 2026
Context cost
about 1,200 tokenswhen the skill loads
GitHub stars
148on letta-ai/skills
Scripts
7 scripts

What it does

“Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.”
The author's description, from SKILL.md

Generated summary from the skill's own text

Configure LLM models on Letta agents by setting model handles, temperature, and token limits, and set up providers on Letta servers using API keys, environment variables, or custom endpoints. The skill covers agent-level model configuration and server-level provider setup for cloud and self-hosted deployments.

When to use it

  • Creating agents with specific model configurations and adjusting temperature or max tokens
  • Changing models on existing agents without losing memory or tools
  • Setting up BYOK providers or self-hosted deployments with environment variables
  • Configuring provider-specific features like OpenAI reasoning or Anthropic thinking

When not to

  • Deciding which model to choose for a task, seek model selection guidance elsewhere
  • Troubleshooting general agent behavior unrelated to model or provider configuration

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add letta-ai/skills --skill letta-configuration

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install letta-ai/skills letta-configuration@6785511e7d3913d9ec598435a77ae637cd45fc89

Installs the commit we checked (6785511).

Copy by hand

Download the folder at 6785511 and put it in .claude/skills/letta-configuration for Claude Code and in .agents/skills/letta-configuration for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at 6785511

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "letta-configuration" by Letta.

Source, pinned to commit 6785511e7d3913d9ec598435a77ae637cd45fc89:
https://github.com/letta-ai/skills/tree/6785511e7d3913d9ec598435a77ae637cd45fc89/letta/letta-configuration

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/letta-configuration/ for Claude Code and .agents/skills/letta-configuration/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/letta/letta-configuration

SKILL.md at the pin

---
name: letta-configuration
description: Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.
license: MIT
---

# Letta Configuration

Complete guide for configuring models on agents and providers on servers.

## When to Use This Skill

**Agent-level (model configuration):**
- Creating agents with specific model configurations
- Adjusting model settings (temperature, max tokens, context window)
- Configuring provider-specific features (OpenAI reasoning, Anthropic thinking)
- Changing models on existing agents

**Server-level (provider configuration):**
- Setting up BYOK (bring your own key) providers
- Configuring self-hosted deployments with environment variables
- Validating provider credentials
- Setting up custom OpenAI-compatible endpoints

**Not covered here:** Model selection advice (which model to choose) - see `agent-development` skill.

---

## Part 1: Model Configuration (Agent-Level)

### Model Handles

Models use a `provider/model-name` format:

| Provider | Handle Prefix | Example |
|----------|---------------|---------|
| OpenAI | `openai/` | `openai/gpt-4o`, `openai/gpt-4o-mini` |
| Anthropic | `anthropic/` | `anthropic/claude-sonnet-4-5-20250929` |
| Google AI | `google_ai/` | `google_ai/gemini-2.0-flash` |
| Azure OpenAI | `azure/` | `azure/gpt-4o` |
| AWS Bedrock | `bedrock/` | `bedrock/anthropic.claude-3-5-sonnet` |
| Groq | `groq/` | `groq/llama-3.3-70b-versatile` |
| Together | `together/` | `together/meta-llama/Llama-3-70b` |
| OpenRouter | `openrouter/` | `openrouter/anthropic/claude-3.5-sonnet` |
| Ollama (local) | `ollama/` | `ollama/llama3.2` |

### Basic Model Configuration

```python
from letta_client import Letta

client = Letta(api_key="your-api-key")

agent = client.agents.create(
    model="openai/gpt-4o",
    model_settings={
        "provider_type": "openai",  # Required - must match model provider
        "temperature": 0.7,
        "max_output_tokens": 4096,
    },
    context_window_limit=128000
)
```

### Common Settings

| Setting | Type | Description |
|---------|------|-------------|
| `provider_type` | string | **Required.** Must match model provider (`openai`, `anthropic`, `google_ai`, etc.) |
| `temperature` | float | Controls randomness (0.0-2.0). Lower = more deterministic. |
| `max_output_tokens` | int | Maximum tokens in the response. |

### Changing an Agent's Model

```python
client.agents.update(
    agent_id=agent.id,
    model="anthropic/claude-sonnet-4-5-20250929",
    model_settings={"provider_type": "anthropic", "temperature": 0.5},
    context_window_limit=64000
)
```

**Note:** Agents retain memory and tools when changing models.

### Provider-Specific Settings

For OpenAI reasoning models and Anthropic extended thinking, see `references/provider-settings.md`.

---

## Part 2: Provider Configuration (Server-Level)

### Quick Start

```bash
# Add provider via API
python scripts/setup_provider.py --type openai --api-key sk-...

# Generate .env for Docker
python scripts/generate_env.py --providers openai,anthropic,ollama

# Validate credentials
python scripts/validate_provider.py --provider-id provider-xxx
```

### Add BYOK Provider

```python
# Via REST API
curl -X POST http://localhost:8283/v1/providers \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My OpenAI",
    "provider_type": "openai",
    "api_key": "sk-your-key-here"
  }'
```

### Supported Provider Types

`openai`, `anthropic`, `azure`, `google_ai`, `google_vertex`, `ollama`, `groq`, `deepseek`, `xai`, `together`, `mistral`, `cerebras`, `bedrock`, `vllm`, `sglang`, `hugging_face`, `lmstudio_openai`

For detailed configuration of each provider, see:
- `references/common_providers.md` - OpenAI, Anthropic, Azure, Google
- `references/self_hosted_providers.md` - Ollama, vLLM, LM Studio
- `references/all_providers.md` - Complete reference
- `references/environment_variables.md` - Docker/self-hosted setup

---

## Anti-Hallucination Checklist

Before configuring:

- [ ] Model handle uses correct `provider/model-name` format
- [ ] `model_settings` includes required `provider_type` field
- [ ] `context_window_limit` is set at agent level, not in `model_settings`
- [ ] Provider-specific settings use correct nested structure
- [ ] For self-hosted: embedding model is specified
- [ ] Temperature is within valid range (0.0-2.0)

## Scripts

**Model configuration:**
- `scripts/basic_config.py` - Basic model configuration
- `scripts/basic_config.ts` - TypeScript equivalent
- `scripts/change_model.py` - Changing models on existing agents
- `scripts/provider_specific.py` - OpenAI reasoning, Anthropic thinking

**Provider configuration:**
- `scripts/setup_provider.py` - Add providers via REST API
- `scripts/validate_provider.py` - Check provider credentials
- `scripts/generate_env.py` - Generate .env for Docker

From letta-ai/skills at 6785511, shown as plain text under its license: MIT (permissive). The license text is in letta/letta-configuration/LICENSE.

View SKILL.md on GitHub at 6785511

Files

15 files, 59 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at 6785511
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