letta-configuration

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.

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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

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

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

# 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

# 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