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…
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- 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.”
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-configurationInstalls 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@6785511e7d3913d9ec598435a77ae637cd45fc89Installs 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.
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 6785511Files
- SKILL.md5.0 KB · 04e3c3eccfaf
- LICENSE1.1 KB · cffc4dad09f3
- references/
- all_providers.md6.5 KB · 6b47bf90bae5
- common_providers.md4.8 KB · f8dbcf734c30
- custom-endpoints.md3.7 KB · 42c7a6595129
- environment_variables.md7.7 KB · 160ae94c086c
- provider-settings.md3.6 KB · 405c4a7cc748
- self_hosted_providers.md5.7 KB · 40dc459bceac
- scripts/
- basic_config.py1.5 KB · 764adfac2c88
- basic_config.ts1.7 KB · 2596a48fa7c9
- change_model.py2.0 KB · 09d6e6b6c0c1
- generate_env.py4.6 KB · ae9037a2466f
- provider_specific.py3.6 KB · a482ea097313
- setup_provider.py3.9 KB · 00475e53ce13
- validate_provider.py3.9 KB · 7716a1cefec0
15 files, 59 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
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