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letta-configuration

letta-configuration

github.com/letta-aiAgent workflows152151 installsUpdated 4w ago
Repository

About letta-configuration

A skill for configuring models on Letta agents and language-model providers on servers. It covers model settings, provider credentials, self-hosted setups, and validation scripts.

Key features

  1. 01Configure agent model handles and settings
  2. 02Change models while retaining agent memory and tools
  3. 03Set up BYOK and self-hosted providers
  4. 04Validate provider credentials
  5. 05Generate Docker environment files

Use cases

  1. 01Create an agent with provider-specific settings
  2. 02Change an existing agent’s model
  3. 03Configure credentials for a server provider
  4. 04Prepare environment variables for Docker deployment

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/letta-ai/skills --skill letta-configuration

After installing, type/letta-configurationin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
references/
all_providers.md
common_providers.md
custom-endpoints.md
environment_variables.md
provider-settings.md
self_hosted_providers.md
scripts/
basic_config.py
basic_config.ts
change_model.py
generate_env.py
provider_specific.py
setup_provider.py
validate_provider.py

Details

From the project README

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:

ProviderHandle PrefixExample
OpenAIopenai/openai/gpt-4o, openai/gpt-4o-mini
Anthropicanthropic/anthropic/claude-sonnet-4-5-20250929
Google AIgoogle_ai/google_ai/gemini-2.0-flash
Azure OpenAIazure/azure/gpt-4o
AWS Bedrockbedrock/bedrock/anthropic.claude-3-5-sonnet
Groqgroq/groq/llama-3.3-70b-versatile
Togethertogether/together/meta-llama/Llama-3-70b
OpenRouteropenrouter/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
SettingTypeDescription
provider_typestringRequired. Must match model provider (openai, anthropic, google_ai, etc.)
temperaturefloatControls randomness (0.0-2.0). Lower = more deterministic.
max_output_tokensintMaximum 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

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