adding-models · diff
git:20260822.1f4d3e3 to git:20260904.5d21ac4
24 added, 8 removed. Audit A to A.
---
name: adding-models
description: Guide for adding new LLM models to Letta Code. Use when the user wants to add support for a new model, needs to know valid model handles, or wants to update model-specific compatibility behavior. Covers runtime catalog sources, CI test matrices, and handle validation.
---
# Adding Models
This skill guides you through adding a new LLM model to Letta Code.
## Quick Reference
**Key files**:
- `src/agent/remote-model-catalog.ts` - Runtime catalog loading and projection
- `src/agent/model-catalog.ts` - Model lookup and compatibility aliases
- `.github/workflows/ci.yml` - CI test matrix (optional)
- `src/tools/manager.ts` - Toolset detection logic (rarely needed)
## Workflow
### Step 1: Find Valid Model Handles
- Query the hosted catalog to see preset IDs and handles:
+ First identify the agent source. These inputs are deliberately different:
+ | Agent source | Rows shown | Labels, presets, and capabilities |
+ |---|---|---|
+ | Cloud hosted | `GET /v1/models/catalog` only | `GET /v1/models/catalog` |
+ | Cloud organization BYOK | BYOK rows from `GET /v1/models` | Match to catalog metadata using provider metadata and model name; retain the BYOK handle for selection |
+ | Local | pi-ai inventory | pi-ai metadata |
+ | Custom App Server | Server runtime inventory | Server runtime metadata |
+
+ In Cloud mode, never use base/hosted rows from `GET /v1/models` to filter,
+ supplement, delay, or provide a fallback for the hosted catalog. This once made
+ GPT-4o appear in a selector even though the Cloud catalog deliberately omitted
+ it. `GET /v1/models` remains necessary for organization-specific BYOK rows.
+
+ Query the Cloud hosted catalog to see hosted preset IDs, handles, and
+ capabilities:
+
```bash
curl -s https://api.letta.com/v1/models/catalog | jq '.models[] | [.id, .handle]'
```
- To inspect the models currently available from an API backend, query its model inventory:
+ To inspect organization BYOK rows from a Cloud backend, query its model
+ inventory and filter by `provider_category`:
```bash
- curl -s https://api.letta.com/v1/models/ | jq '.[] | .handle'
+ curl -s https://api.letta.com/v1/models/ \
+ | jq '.[] | select(.provider_category == "byok") | [.handle, .provider_type]'
```
- Or filter the inventory by provider:
- ```bash
- curl -s https://api.letta.com/v1/models/ | jq '.[] | select(.handle | startswith("google_ai/")) | .handle'
- ```
+ Do not use this response as a second hosted catalog.
Common provider prefixes:
- `anthropic/` - Claude models
- `openai/` - GPT models
- `google_ai/` - Gemini models
- `google_vertex/` - Vertex AI
- `openrouter/` - Various providers
### Step 2: Update the Owning Catalog
Letta Code does not bundle a model catalog:
- - API and hosted presets come from the server's `GET /v1/models/catalog` response.
+ - Cloud hosted rows and presets come from the server's
+ `GET /v1/models/catalog` response.
+ - Cloud `GET /v1/models` contributes only organization BYOK rows to selectors.
- Local model inventory comes from pi-ai and the active provider runtimes.
Add the model at the source that owns it. A hosted preset belongs in the server catalog. A local provider model belongs in pi-ai or that provider's discovery runtime.
Only change this repository when the model needs Letta Code-specific compatibility behavior, such as preserving an established CLI alias or recognizing a new provider for toolset selection. Keep that logic narrow and derive the handle and metadata from the runtime catalog rather than copying model definitions here.
### Step 3: Test the Model
Test with headless mode:
```bash
bun run src/index.ts --new --model <model-id> -p "hi, what model are you?"
```
Example:
```bash
bun run src/index.ts --new --model gemini-3-flash -p "hi, what model are you?"
```
### Step 4: Add to CI Test Matrix (Optional)
To include the model in automated testing, add it to `.github/workflows/ci.yml`:
```yaml
# Find the headless job matrix around line 122
model: [gpt-5-minimal, gpt-4.1, sonnet-4.5, gemini-pro, your-new-model, glm-4.6, haiku]
```
## Toolset Detection
Models are automatically assigned toolsets based on provider:
- `openai/*` → `codex` toolset
- `google_ai/*` or `google_vertex/*` → `gemini` toolset
- Others → `default` toolset
This is handled by `isGeminiModel()` and `isOpenAIModel()` in `src/tools/manager.ts`. You typically don't need to modify this unless adding a new provider.
## Common Issues
**"Handle not found" error**: The model handle is incorrect. Run the validation script to see valid handles.
**Model works but wrong toolset**: Check `src/tools/manager.ts` to ensure the provider prefix is recognized.