> ## Documentation Index
> Fetch the complete documentation index at: https://docs.phala.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Other Tools

> Connect coding assistants and chat apps to Private AI with your Phala API key.

For tools that support an OpenAI-compatible provider, use:

| Setting | Value |
| - | - |
| Provider type | OpenAI compatible |
| Base URL | `https://inference.phala.com/v1` |
| API key | Your Phala API key |
| Model | `z-ai/glm-5.3`, or another chat model from [`/v1/models`](https://inference.phala.com/v1/models) |

Create a key under **Private AI → API Keys** in the Phala dashboard. For the shell examples below, set `PHALA_AI_API_KEY` in your local environment.

Every model on this endpoint runs in a TEE. These clients do not verify attestation locally; use [Private AI Proxy](https://docs.phala.com/phala-cloud/confidential-ai/agents/private-ai-proxy.md#local-api) when you need a verified channel on your machine.

## Continue

Add a model to your local `~/.continue/config.yaml` using Continue's [OpenAI-compatible configuration](https://docs.continue.dev/customize/model-providers/top-level/openai). Keep any other models already in the file:

```yaml theme={"system"}
name: Phala
version: 0.0.1
schema: v1
models:
  - name: Phala GLM 5.3
    provider: openai
    model: z-ai/glm-5.3
    apiBase: https://inference.phala.com/v1
    apiKey: YOUR_PHALA_API_KEY
```

## Zed

Add this provider under `language_models` in your settings file using Zed's [OpenAI-compatible endpoint configuration](https://zed.dev/docs/ai/use-api-access#openai-compatible). Enter your Phala API key through **Settings → AI → LLM Providers**:

```json theme={"system"}
{
  "language_models": {
    "openai_compatible": {
      "phala": {
        "api_url": "https://inference.phala.com/v1",
        "available_models": [
          {
            "name": "z-ai/glm-5.3",
            "max_tokens": 1048576
          }
        ]
      }
    }
  }
}
```

## GitHub Copilot (VS Code BYOK)

Run **Chat: Manage Language Models**, choose **Add Models → Custom Endpoint**, name the group `Phala`, enter your Phala API key, and select **Chat Completions**. In the generated `chatLanguageModels.json`, keep the API-key input reference created by VS Code and configure the model as below. See the [Custom Endpoint documentation](https://code.visualstudio.com/docs/agent-customization/language-models#_add-a-custom-endpoint-model). This example uses the model's context window from the catalog and reserves 65,536 tokens for output, within the model's 1,048,576-token output maximum:

```json theme={"system"}
[
  {
    "name": "Phala",
    "vendor": "customendpoint",
    "apiKey": "${input:phalaApiKey}",
    "models": [
      {
        "id": "z-ai/glm-5.3",
        "name": "Phala GLM 5.3",
        "url": "https://inference.phala.com/v1/chat/completions",
        "toolCalling": true,
        "contextWindow": 1048576,
        "maxOutputTokens": 65536
      }
    ]
  }
]
```

Select the model in chat. For Copilot Business or Enterprise, your administrator can disable this with the *Bring Your Own Language Model Key in VS Code* policy.

## Aider

Use Aider's [OpenAI-compatible endpoint](https://aider.chat/docs/llms/openai-compat.html) support. The `openai/` prefix tells Aider which API format to use:

```bash theme={"system"}
export OPENAI_API_BASE="https://inference.phala.com/v1"
export OPENAI_API_KEY="$PHALA_AI_API_KEY"
aider --model openai/z-ai/glm-5.3
```

## Goose

Save the following as `phala.json` in Goose's [`custom_providers` directory](https://goose-docs.ai/docs/getting-started/providers/#configure-custom-provider): `~/.config/goose/custom_providers/` on macOS/Linux, or `%APPDATA%\Block\goose\config\custom_providers\` on Windows. If you set `GOOSE_PATH_ROOT`, use `<GOOSE_PATH_ROOT>/config/custom_providers/` instead. Create the directory if needed:

```json theme={"system"}
{
  "name": "phala",
  "engine": "openai",
  "display_name": "Phala",
  "description": "OpenAI-compatible confidential inference from Phala.",
  "api_key_env": "PHALA_AI_API_KEY",
  "base_url": "https://inference.phala.com/v1",
  "dynamic_models": true,
  "models": [],
  "supports_streaming": true,
  "model_doc_link": "https://docs.phala.com/phala-cloud/confidential-ai/confidential-model/confidential-ai-api",
  "setup_steps": [
    "Sign in to the Phala dashboard",
    "Open Private AI, then API Keys, and create an API key",
    "Copy the key and paste it above"
  ]
}
```

With `PHALA_AI_API_KEY` set, run `goose configure`, choose **Configure Providers → Phala**, and select `z-ai/glm-5.3`. Dynamic discovery also lists the non-chat `jaredpalmer/kev-4b` decision model; choose a chat model.

## AnythingLLM

In **Settings → AI Providers → LLM**, select **Generic OpenAI** and enter these [provider settings](https://docs.anythingllm.com/setup/llm-configuration/cloud/openai-generic), then select **Save changes**. Use the model's `context_length` from the catalog when choosing another model:

```text theme={"system"}
Base URL: https://inference.phala.com/v1
API Key: Your Phala API key
Selected Model: z-ai/glm-5.3
Model context window: 1048576
```

## Cherry Studio

Open **Settings → Model Services → + Add Provider** and add a [custom provider](https://docs.cherryai.com.cn/docs/en-us/pre-basic/providers/zi-ding-yi-fu-wu-shang) with the values below. Enter the base URL in the OpenAI-compatible endpoint/API address row. Select **Add**, then **Get model list** and add `z-ai/glm-5.3`:

```text theme={"system"}
Provider Name: Phala
API Key: Your Phala API key
Base URL: https://inference.phala.com/v1
```

## LobeHub

Open **App Settings → AI Providers** and create a [custom AI provider](https://lobehub.com/changelog/2025-01-22-new-ai-provider) with the values below. Enable the provider and fetch or add `z-ai/glm-5.3` in its model list, then select it in your Agent settings:

```text theme={"system"}
Provider ID: phala
Provider Name: Phala
Request Format: openai
Proxy URL: https://inference.phala.com/v1
API Key: Your Phala API key
```

## Jan

In [Jan Desktop](https://docs.jan.ai/desktop/remote-models/custom-endpoint), open **Settings → Model Providers → Add Provider**, choose **OpenAI-compatible**, and set **Provider name** to `Phala`, **Base URL** to `https://inference.phala.com/v1`, and **API key** to your Phala key. Select **Create**, then select `z-ai/glm-5.3` from the model list. For tool use, edit the model and enable **Tools** under **Capabilities**.

For [Jan Agent CLI](https://docs.jan.ai/agent/providers), save a provider and start Jan with it:

```bash theme={"system"}
jan config set --provider phala \
  --api-key "$PHALA_AI_API_KEY" \
  --base-url https://inference.phala.com/v1 \
  --model z-ai/glm-5.3
jan --provider phala --model z-ai/glm-5.3
```


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