# OpenClaw

In this guide you will use an inference endpoint from Rafay's Token Factory as a custom model provider within a self hosted [OpenClaw](https://openclaw.ai/) instance.

## Assumptions

This exercise assumes the following requirements are already in place.

- An active Token Factory model deployment (If using vLLM and your model requires it, be sure your deployment is using the following extra engine arguments, "--enable-auto-tool-choice --tool-call-parser hermes")
- A customer tenant org with access to a user with an end user role
- An [OpenClaw installation](https://docs.openclaw.ai/install)

## 1. Retrieve Model API Details

In this section, you will retrieve the Token Factory Model API details. These details will be used to configure an OpenClaw custom model provider in a later step.

- Log into the Developer Hub console as a tenant end user
- Navigate to **GenAI -> Model APIs**
- Click on the model card for the model you will be using with OpenClaw
- Click **Get an API Key**
- Enter a name for the key
- Click **Create**

- Copy the key provided and store in a safe location as it cannot be retrieved again
- Copy the model name and endpoint and save for later use

## 2. Configure OpenClaw

In this section, you will configure a "custom model provider" from the OpenClaw Control UI. This will allow the OpenClaw instance to use the models in the Rafay Token Factory.

- Log into the OpenClaw Control UI
- Navigate to **AI & Agents -> Models**
- Click **Add Entry** under "Model Providers -> Custom entries"
- Enter a name for the custom entry
- Select **openai-completions** for the Model Provider API Adapter
- Enter the previously stored API key from Token Factory for the Model Provider API Key
- Select **token** for the Model Provider Auth Mode
- Enter the Endpoint from Token Factory for the Model Provider Base URL. Be sure to remove "/chat/completions" from the end of the URL.
- Click **+Add** on Model Provider Model List
- Select **openai-completions** for the Api
- Enter the model name for the Id
- Enter **256** for the Max Tokens
- Enter the model name for the name
- Click **Save**
- Click **Update**

You can configure/verify your custom model within the **openclaw.json** configuration file.

The following content should be added to the file. Be sure to use your environment specific values.

```
  "models": {
    "providers": {
      "ACME": {
        "baseUrl": "https://openclaw.paas.demo.gorafay.net/v1",
        "apiKey": "<YOUR_API_KEY>",
        "auth": "token",
        "api": "openai-completions",
        "injectNumCtxForOpenAICompat": true,
        "models": [\
          {\
            "id": "openclaw",\
            "name": "openclaw",\
            "api": "openai-completions",\
            "reasoning": false,\
            "input": [\
              "text"\
            ],\
            "cost": {\
              "input": 0,\
              "output": 0,\
              "cacheRead": 0,\
              "cacheWrite": 0\
            },\
            "contextWindow": 200000,\
            "maxTokens": 256\
          }\
        ]
      }
    }
  }
```

## 3. Use OpenClaw with Token Factory

In this section, you will initiate a chat session from the OpenClaw Control UI.

- Log into the OpenClaw Control UI
- Navigate to **Chat**
- Ensure your custom model provider is selected in the top dropdown menu
- Enter a message into the chat and press enter

You will receive a response from the Token Factory inference endpoint.

## 4. Verify Token Usage

In this section, you will verify token usage from OpenClaw within Token Factory.

- Log into the Developer Hub console as a tenant end user
- Navigate to **GenAI -> Token Usage**
- Select the **Token Usage** tab

You will see the token usage from the previously sent chat message.