Providers & Models

PizzaPi is built on the pi coding agent, which supports 20+ AI providers out of the box. You can authenticate with a paid subscription via OAuth, set API keys, or add custom providers like Ollama or LM Studio for local models.

Supported Providers

Subscription Providers (OAuth)

These providers use OAuth — authenticate with /login inside a session:

Provider	Subscription
Anthropic	Claude Pro / Max
OpenAI	ChatGPT Plus / Pro (Codex)
GitHub Copilot	Copilot subscription
Google Gemini CLI	Free with Google account
Google Antigravity	Free with Google account

API Key Providers

Set an environment variable or store the key in the auth file:

Provider	Environment Variable
Anthropic	`ANTHROPIC_API_KEY`
OpenAI	`OPENAI_API_KEY`
Google Gemini	`GEMINI_API_KEY`
Azure OpenAI	`AZURE_OPENAI_API_KEY`
Google Vertex AI	Uses Application Default Credentials
Amazon Bedrock	`AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY`
Mistral	`MISTRAL_API_KEY`
Groq	`GROQ_API_KEY`
Cerebras	`CEREBRAS_API_KEY`
xAI	`XAI_API_KEY`
OpenRouter	`OPENROUTER_API_KEY`
Vercel AI Gateway	`AI_GATEWAY_API_KEY`
Hugging Face	`HF_TOKEN`
Kimi For Coding	`KIMI_API_KEY`
MiniMax	`MINIMAX_API_KEY`

Authentication

Using `/login` (Subscriptions)

Inside a PizzaPi session, type /login in the chat input. You’ll be prompted to select a provider and complete the OAuth flow in your browser. Tokens are stored in ~/.pi/agent/auth.json and auto-refresh when they expire.

Use /logout to clear stored credentials.

Using API Keys

Set the provider’s environment variable before starting PizzaPi:

export ANTHROPIC_API_KEY=sk-ant-...

Or store it in the auth file at ~/.pi/agent/auth.json:

{
  "anthropic": { "type": "api_key", "key": "sk-ant-..." },
  "openai": { "type": "api_key", "key": "sk-..." }
}

The auth file is created with 0600 permissions (user read/write only). Auth file credentials take priority over environment variables.

Key Resolution

The key field in auth.json supports three formats:

Format	Example	Description
Shell command	`"!security find-generic-password -ws 'anthropic'"`	Executes command, uses stdout
Environment variable	`"MY_ANTHROPIC_KEY"`	Reads the named env var
Literal value	`"sk-ant-..."`	Used directly

Shell commands are useful for pulling keys from password managers:

{
  "anthropic": { "type": "api_key", "key": "!op read 'op://vault/item/credential'" }
}

Credential Priority

When multiple sources provide credentials for the same provider:

CLI --api-key flag (highest priority)
auth.json entry (API key or OAuth token)
Environment variable
Custom provider keys from models.json

Switching Models

In the Web UI

Use the /model command in the chat input to open the model selector. This shows all available models across your authenticated providers.

You can also cycle through a subset of models using the /cycle_model command, or change reasoning effort with /effort.

Setting Defaults

Set your preferred default model in ~/.pi/agent/settings.json:

{
  "defaultProvider": "anthropic",
  "defaultModel": "claude-sonnet-4-20250514",
  "defaultThinkingLevel": "medium"
}

Scoped Model Cycling

Limit which models appear when cycling:

{
  "enabledModels": ["claude-*", "gpt-4o", "gemini-2*"]
}

Custom Models

Add local or custom models (Ollama, vLLM, LM Studio, proxies) via ~/.pi/agent/models.json. The file reloads each time you open /model — edit it mid-session without restarting.

Minimal Example (Ollama)

{
  "providers": {
    "ollama": {
      "baseUrl": "http://localhost:11434/v1",
      "api": "openai-completions",
      "apiKey": "ollama",
      "models": [
        { "id": "llama3.1:8b" },
        { "id": "qwen2.5-coder:7b" }
      ]
    }
  }
}

Full Model Configuration

{
  "providers": {
    "ollama": {
      "baseUrl": "http://localhost:11434/v1",
      "api": "openai-completions",
      "apiKey": "ollama",
      "models": [
        {
          "id": "llama3.1:8b",
          "name": "Llama 3.1 8B (Local)",
          "reasoning": false,
          "input": ["text"],
          "contextWindow": 128000,
          "maxTokens": 32000,
          "cost": { "input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0 }
        }
      ]
    }
  }
}

Supported API Types

API	Use For
`openai-completions`	Most compatible — Ollama, vLLM, LM Studio, OpenRouter
`openai-responses`	OpenAI Responses API
`anthropic-messages`	Anthropic Messages API
`google-generative-ai`	Google Generative AI

Provider Configuration Fields

Field	Description
`baseUrl`	API endpoint URL
`api`	API type (see above)
`apiKey`	API key (supports shell command, env var, or literal)
`headers`	Custom headers (same resolution as apiKey)
`authHeader`	Set `true` to add `Authorization: Bearer <apiKey>`
`models`	Array of model definitions
`modelOverrides`	Per-model overrides for built-in models

Model Fields

Field	Required	Default	Description
`id`	Yes	—	Model identifier passed to the API
`name`	No	`id`	Human-readable label
`api`	No	provider’s	Override API type for this model
`reasoning`	No	`false`	Supports extended thinking
`input`	No	`["text"]`	Input types: `["text"]` or `["text", "image"]`
`contextWindow`	No	`128000`	Context window (tokens)
`maxTokens`	No	`16384`	Max output tokens
`cost`	No	all zeros	Per-million-token costs

OpenAI Compatibility

For servers with partial OpenAI compatibility, use the compat field at the provider or model level:

{
  "providers": {
    "local-llm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "compat": {
        "supportsDeveloperRole": false,
        "supportsReasoningEffort": false
      },
      "models": [{ "id": "my-model" }]
    }
  }
}

This commonly applies to Ollama, vLLM, SGLang, and similar servers that don’t understand the developer role or reasoning_effort parameter.

Cloud Provider Setup

Azure OpenAI

export AZURE_OPENAI_API_KEY=...
export AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com
# Optional
export AZURE_OPENAI_API_VERSION=2024-02-01
export AZURE_OPENAI_DEPLOYMENT_NAME_MAP=gpt-4=my-gpt4,gpt-4o=my-gpt4o

Amazon Bedrock

# Option 1: AWS Profile
export AWS_PROFILE=your-profile

# Option 2: IAM Keys
export AWS_ACCESS_KEY_ID=AKIA...
export AWS_SECRET_ACCESS_KEY=...

# Optional region (defaults to us-east-1)
export AWS_REGION=us-west-2

Google Vertex AI

gcloud auth application-default login
export GOOGLE_CLOUD_PROJECT=your-project
export GOOGLE_CLOUD_LOCATION=us-central1

Overriding Built-in Providers

Route a built-in provider through a proxy without redefining its models:

{
  "providers": {
    "anthropic": {
      "baseUrl": "https://my-proxy.example.com/v1"
    }
  }
}

All built-in Anthropic models remain available — only the endpoint changes.