# Architecture: LLM Backends

> How Cortex selects and talks to AI models.
> Last updated: 2026-06-18

---

## Providers

Cortex supports two model types, each dispatched differently:

| Type | Auth | Use |
|---|---|---|
| `local_openai` | API key per host in model registry | Open WebUI, Ollama, OpenRouter, LiteLLM, any OpenAI-compatible endpoint |
| `anthropic_api` | API key in model registry (Anthropic cloud provider) | Claude models via Anthropic SDK |

The Gemini API (`gemini_api`) is a third type used exclusively by the orchestrator engine —
it is not dispatched through `llm_client.py` and is not available for chat/distill roles.

---

## Backend Selection

### Default: Role-Based Routing (Auto)

All routing goes through the user's model registry. When a request arrives, `complete()` in
`llm_client.py` resolves the model for the given role:

```
slot specified  →  resolve that exact slot (primary / backup_1 / backup_2)
no slot         →  get_model_for_role(username, role)
no registry entry  →  RuntimeError: "No model configured for role '...'"
```

Roles: `chat`, `orchestrator`, `distill`, `janitor`, `coder`, `research` (extensible via
`DEFINED_ROLES` in `.env`).

There is no implicit fallback to a built-in model. If no model is configured for a role,
the request fails with a clear error directing the user to `/settings/models`.

### Explicit Slot Selection

The **Role** toggle in the Context & Memory panel cycles through configured role slots:
**Primary → Backup 1 → auto**. Each slot resolves the configured model for that position.

When a model is explicitly configured (via slot or registry entry), errors surface
immediately — no silent fallback to another backend.

---

## Model Registry Schema

Per-user configuration stored in `home/{user}/model_registry.json`.

Managed at **Settings → Models** (`/settings/models`).

```json
{
  "version": 2,

  "providers": {
    "anthropic": {
      "credentials": [
        {"id": "key1", "label": "My Anthropic Key", "type": "api_key", "api_key": "sk-ant-..."}
      ]
    },
    "google": {
      "accounts": [
        {"id": "a1b2", "label": "One Sky IT", "api_key": "AIza..."}
      ]
    }
  },

  "hosts": [
    {
      "id": "abc123",
      "label": "OpenRouter",
      "api_url": "https://openrouter.ai/api/v1",
      "api_key": "sk-or-...",
      "host_type": "openai"
    },
    {
      "id": "def456",
      "label": "Gaming Laptop",
      "api_url": "http://192.168.x.x:3000",
      "api_key": "",
      "host_type": "openwebui"
    }
  ],

  "models": [
    {
      "id": "m1",
      "type": "local_openai",
      "label": "Claude Sonnet 4.6 (OpenRouter)",
      "model_name": "anthropic/claude-sonnet-4-6",
      "host_id": "abc123",
      "context_k": 200,
      "tags": ["chat", "persona"]
    },
    {
      "id": "m2",
      "type": "anthropic_api",
      "label": "Claude Sonnet 4.6 (Direct)",
      "model_name": "claude-sonnet-4-6",
      "provider": "anthropic",
      "credential_id": "key1",
      "context_k": 200,
      "tags": ["chat"]
    },
    {
      "id": "m3",
      "type": "local_openai",
      "label": "Gemma 4 E4B",
      "model_name": "gemma4:e4b",
      "provider": "local",
      "host_id": "def456",
      "context_k": 72,
      "max_rounds": 5,
      "tools": true,
      "tags": ["fast", "local"]
    }
  ],

  "roles": {
    "chat":         {"primary": "m1", "backup_1": "m2"},
    "orchestrator": {"primary": "m2"},
    "distill":      {"primary": "m1"}
  }
}
```

### Optional model fields

| Field | Type | Default | Meaning |
|---|---|---|---|
| `context_k` | int | 32 | Context window in thousands of tokens. Used for compaction budget (75% of window). |
| `max_rounds` | int \| null | null | Per-model tool loop cap. `null` = use global `orchestrator_max_rounds`. Effective limit = `min(per_model, global)`. |
| `tools` | bool | true | Whether this model supports tool calling. `false` = skip tool loop entirely; model gets a plain chat request. |

### host_type (local hosts)

| `host_type` | Chat endpoint | Models endpoint | Use for |
|---|---|---|---|
| `openwebui` (default) | `POST {url}/api/chat/completions` | `GET {url}/api/models` | Open WebUI, Ollama |
| `openai` | `POST {url}/chat/completions` | `GET {url}/models` | OpenRouter, LiteLLM, Anthropic-compat |

Set `api_url` to the base path before `/chat/completions`:
- OpenRouter: `https://openrouter.ai/api/v1`

---

## Local/OpenAI-Compatible Backend (`_local()`)

HTTP POST to an OpenAI-compatible endpoint. Model config is resolved via the model registry.

```python
# host_type "openwebui":  POST {api_url}/api/chat/completions
# host_type "openai":     POST {api_url}/chat/completions
```

System prompt is sent as the first `{"role": "system", "content": "..."}` message.
Image attachments are injected into the last user message as `image_url` content blocks.
Token usage is recorded when returned by the endpoint.

Streaming variant: `_local_streaming()` — SSE line-by-line, yields tokens via `token_sink`.

Timeout: `TIMEOUT_LOCAL=300` seconds (`.env`) — local models may need to load from disk.

---

## Anthropic API Backend (`_anthropic_api()`)

Direct call to the Anthropic Messages API via the `anthropic` Python SDK.

System prompt passed as top-level `system` field. Messages stripped to `role`/`content` only.
Token usage is always recorded from `resp.usage`.

Streaming variant: `_anthropic_api_streaming()` — uses `client.messages.stream()`, yields
tokens via `token_sink`.

API key comes from the model registry: `providers.anthropic.credentials[n].api_key`.

Timeout: governed by httpx defaults and the Anthropic SDK's own connection handling.

---

## Gemini API (Orchestrator only)

Used by `orchestrator_engine.py` for the ReAct tool loop. Not dispatched through
`llm_client.py` and not available for chat, distill, or other roles.

API key resolution order:
1. `api_key` embedded in the resolved orchestrator model config (V2 registry with `account_id`)
2. `get_user_gemini_key(user)` — reads from `auth.json` (legacy, kept for compat)
3. `GEMINI_API_KEY` in `.env` (server default)

---

## Distillation

Memory distillation uses `role="distill"`. Configure via Model Registry → Role Assignments.
Any `local_openai` or `anthropic_api` model can be assigned to the distill role.

---

## Code locations

| File | Responsibility |
|---|---|
| `cortex/llm_client.py` | `complete()` — routing, dispatch, fallback |
| `cortex/model_registry.py` | Per-user registry CRUD and resolution (V2) |
| `cortex/routers/local_llm.py` | Settings UI routes + `/api/models/role` AJAX |
| `cortex/routers/chat.py` | `_backend_label()`, `fallback_used` flag |
| `cortex/routers/orchestrator.py` | Engine selection, Gemini API key resolution |
| `cortex/config.py` | `ROLE_*` env defaults, `DEFINED_ROLES`, `TIMEOUT_LOCAL` |