Agent skill
letta-configuration
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.
Install this agent skill to your Project
npx add-skill https://github.com/letta-ai/skills/tree/main/letta/letta-configuration
SKILL.md
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
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, Googlereferences/self_hosted_providers.md- Ollama, vLLM, LM Studioreferences/all_providers.md- Complete referencereferences/environment_variables.md- Docker/self-hosted setup
Anti-Hallucination Checklist
Before configuring:
- Model handle uses correct
provider/model-nameformat -
model_settingsincludes requiredprovider_typefield -
context_window_limitis set at agent level, not inmodel_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 configurationscripts/basic_config.ts- TypeScript equivalentscripts/change_model.py- Changing models on existing agentsscripts/provider_specific.py- OpenAI reasoning, Anthropic thinking
Provider configuration:
scripts/setup_provider.py- Add providers via REST APIscripts/validate_provider.py- Check provider credentialsscripts/generate_env.py- Generate .env for Docker
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