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feat(metamodels): Add support for Muse Spark 1.1 via the Meta Models API (#10432)

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This commit is contained in:
Ben Godfrey
2026-07-14 17:55:42 +01:00
committed by GitHub
parent c1eebf034d
commit f47cebf855
4 changed files with 339 additions and 157 deletions
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crates/goose-providers/src/declarative.rs
+1
View File
@@ -27,6 +27,7 @@ pub(crate) mod declarative_providers {
inception,
llama_swap,
lmstudio,
meta,
minimax,
mistral,
moonshot,
crates/goose-providers/src/declarative/definitions/meta.json
+30
View File
@@ -0,0 +1,30 @@
{
"name": "meta",
"engine": "openai",
"display_name": "Meta",
"description": "Meta's Model API, home of the Muse Spark models",
"api_key_env": "META_MODEL_API_KEY",
"base_url": "https://api.meta.ai/v1",
"catalog_provider_id": "meta",
"dynamic_models": true,
"models": [
{
"name": "muse-spark-1.1",
"context_limit": 1000000,
"max_tokens": 32000,
"input_token_cost": 0.00000125,
"output_token_cost": 0.00000425,
"currency": "USD",
"reasoning": true
}
],
"preserves_thinking": true,
"supports_streaming": true,
"model_doc_link": "https://dev.meta.ai/docs",
"setup_steps": [
"Sign in to https://dev.meta.ai",
"Navigate to API Keys in your account settings",
"Create a new API key",
"Copy the key and paste it above"
]
}
crates/goose-providers/src/openai.rs
+126 -9
View File
@@ -18,9 +18,11 @@ use crate::openai_compatible::{
handle_response_openai_compat, handle_status, stream_openai_compat, stream_responses_compat,
};
use crate::request_log::{start_log, LoggerHandleExt};
use crate::thinking::ThinkingEffort;
use anyhow::Result;
use async_trait::async_trait;
use reqwest::StatusCode;
use serde_json::json;
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
@@ -347,7 +349,33 @@ impl OpenAiProvider {
const PROVIDERS_NEEDING_STANDARD_CHAT_PARAMS: &[&str] = &["nearai"];
fn sanitize_request_for_compat(&self, mut payload: serde_json::Value) -> serde_json::Value {
/// Providers whose reasoning models accept an OpenAI-style
/// `reasoning_effort` field on chat-completions requests but aren't
/// matched by [`is_openai_responses_model`] (which only recognises
/// OpenAI's own `o*`/`gpt-5*` model names). These need the unified
/// [`ThinkingEffort`] mapped onto the request explicitly.
const PROVIDERS_NEEDING_REASONING_EFFORT_MAPPING: &[&str] = &["meta"];
/// Maps the unified thinking effort onto Meta's Muse Spark
/// `reasoning_effort` levels: `low`, `medium`, `high`, `xhigh`.
///
/// Muse Spark always reasons and has no supported "disable reasoning"
/// level, so `Off` is clamped to `low` (the lightest level Meta
/// supports) rather than sent as-is or omitted.
fn meta_reasoning_effort(effort: ThinkingEffort) -> &'static str {
match effort {
ThinkingEffort::Off | ThinkingEffort::Low => "low",
ThinkingEffort::Medium => "medium",
ThinkingEffort::High => "high",
ThinkingEffort::Max => "xhigh",
}
}
fn sanitize_request_for_compat(
&self,
mut payload: serde_json::Value,
model_config: &ModelConfig,
) -> serde_json::Value {
if let Some(obj) = payload.as_object_mut() {
if Self::PROVIDERS_NEEDING_MAX_TOKENS_REMAP.contains(&self.name.as_str()) {
if let Some(value) = obj.remove("max_completion_tokens") {
@@ -373,6 +401,20 @@ impl OpenAiProvider {
}
}
}
if Self::PROVIDERS_NEEDING_REASONING_EFFORT_MAPPING.contains(&self.name.as_str()) {
match model_config.thinking_effort() {
Some(effort) => {
obj.insert(
"reasoning_effort".to_string(),
json!(Self::meta_reasoning_effort(effort)),
);
}
None => {
obj.remove("reasoning_effort");
}
}
}
}
payload
@@ -672,7 +714,7 @@ impl Provider for OpenAiProvider {
preserve_thinking_context: self.preserve_thinking_context,
},
)?;
let payload = self.sanitize_request_for_compat(payload);
let payload = self.sanitize_request_for_compat(payload, model_config);
let mut log = start_log(model_config, &payload)?;
let response = self
@@ -876,7 +918,8 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result = provider
.sanitize_request_for_compat(payload, &ModelConfig::new("mistral-medium-latest"));
let obj = result.as_object().unwrap();
assert!(!obj.contains_key("max_completion_tokens"));
@@ -893,7 +936,8 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result = provider
.sanitize_request_for_compat(payload, &ModelConfig::new("mistral-medium-latest"));
let obj = result.as_object().unwrap();
assert!(!obj.contains_key("max_completion_tokens"));
@@ -909,7 +953,7 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result = provider.sanitize_request_for_compat(payload, &ModelConfig::new("o3"));
let obj = result.as_object().unwrap();
assert!(obj.contains_key("max_completion_tokens"));
@@ -925,7 +969,8 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result =
provider.sanitize_request_for_compat(payload, &ModelConfig::new("future-model"));
let obj = result.as_object().unwrap();
assert!(obj.contains_key("max_completion_tokens"));
@@ -940,7 +985,10 @@ mod tests {
"messages": []
});
let result = provider.sanitize_request_for_compat(payload.clone());
let result = provider.sanitize_request_for_compat(
payload.clone(),
&ModelConfig::new("llama-3.3-70b-versatile"),
);
assert_eq!(result, payload);
}
@@ -963,7 +1011,8 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result = provider
.sanitize_request_for_compat(payload, &ModelConfig::new("Qwen/Qwen3.6-35B-A3B-FP8"));
let obj = result.as_object().unwrap();
assert!(!obj.contains_key("reasoning_effort"));
@@ -983,7 +1032,8 @@ mod tests {
"max_completion_tokens": 16384
});
let result = provider.sanitize_request_for_compat(payload);
let result =
provider.sanitize_request_for_compat(payload, &ModelConfig::new("openai/gpt-5"));
let obj = result.as_object().unwrap();
assert_eq!(obj.get("reasoning_effort"), Some(&json!("medium")));
@@ -991,6 +1041,73 @@ mod tests {
assert_eq!(obj.get("max_tokens").unwrap(), &json!(16384));
}
#[test]
fn sanitize_meta_applies_reasoning_effort_from_thinking_effort() {
let provider = make_provider("meta");
let payload = json!({
"model": "muse-spark-1.1",
"messages": []
});
let model_config =
ModelConfig::new("muse-spark-1.1").with_thinking_effort(ThinkingEffort::High);
let result = provider.sanitize_request_for_compat(payload, &model_config);
let obj = result.as_object().unwrap();
assert_eq!(obj.get("reasoning_effort"), Some(&json!("high")));
}
#[test]
fn sanitize_meta_maps_max_thinking_effort_to_xhigh() {
let provider = make_provider("meta");
let payload = json!({
"model": "muse-spark-1.1",
"messages": []
});
let model_config =
ModelConfig::new("muse-spark-1.1").with_thinking_effort(ThinkingEffort::Max);
let result = provider.sanitize_request_for_compat(payload, &model_config);
let obj = result.as_object().unwrap();
assert_eq!(obj.get("reasoning_effort"), Some(&json!("xhigh")));
}
#[test]
fn sanitize_meta_clamps_off_thinking_effort_to_low() {
// Muse Spark always reasons and has no "disable reasoning" level,
// so an explicit `Off` must be clamped to the lightest supported
// level rather than omitted or sent as-is.
let provider = make_provider("meta");
let payload = json!({
"model": "muse-spark-1.1",
"messages": [],
"reasoning_effort": "high"
});
let model_config =
ModelConfig::new("muse-spark-1.1").with_thinking_effort(ThinkingEffort::Off);
let result = provider.sanitize_request_for_compat(payload, &model_config);
let obj = result.as_object().unwrap();
assert_eq!(obj.get("reasoning_effort"), Some(&json!("low")));
}
#[test]
fn sanitize_meta_omits_reasoning_effort_when_unset() {
let provider = make_provider("meta");
let payload = json!({
"model": "muse-spark-1.1",
"messages": []
});
let model_config = ModelConfig::new("muse-spark-1.1");
let result = provider.sanitize_request_for_compat(payload, &model_config);
let obj = result.as_object().unwrap();
assert!(!obj.contains_key("reasoning_effort"));
}
#[test]
fn nearai_uses_chat_completions_for_openai_reasoning_models() {
let provider = make_provider("nearai");
documentation/docs/getting-started/providers.md
+182 -148
View File
@@ -41,6 +41,7 @@ goose is compatible with a wide range of LLM providers, allowing you to choose a
| [iFlytek Astron MaaS](https://maas.xfyun.cn/) | iFlytek Astron MaaS (讯飞星辰) hosting Spark X2, DeepSeek, GLM, Kimi, MiniMax, Qwen, and Astron coding models via an OpenAI-compatible API. Set `ASTRON_BASE_URL` to switch between the Token Plan and Coding Plan endpoints. | `ASTRON_API_KEY`, `ASTRON_BASE_URL` (optional) |
| [LiteLLM](https://docs.litellm.ai/docs/) | LiteLLM proxy supporting multiple models with automatic prompt caching and unified API access. | `LITELLM_HOST`, `LITELLM_BASE_PATH` (optional), `LITELLM_API_KEY` (optional), `LITELLM_CUSTOM_HEADERS` (optional), `LITELLM_TIMEOUT` (optional) |
| [LM Studio](https://lmstudio.ai/) | Run local models with LM Studio's OpenAI-compatible server. **Because this provider runs locally, you must first [download a model](#local-llms).** | None required. Connects to local server at `localhost:1234` by default. |
| [Meta](https://dev.meta.ai/) | Meta's Model API, home of the Muse Spark models. | `META_MODEL_API_KEY` |
| [Mistral AI](https://mistral.ai/) | Provides access to Mistral models including general-purpose models, specialized coding models (Codestral), and multimodal models (Pixtral). | `MISTRAL_API_KEY` |
| [NEAR AI Cloud](https://cloud.near.ai/) | TEE-backed private inference through an OpenAI-compatible API with dynamic model discovery. | `NEARAI_API_KEY` |
| [Novita AI](https://novita.ai/) | 90+ open-source models with OpenAI-compatible API and competitive pricing. Supports Kimi K2.5, DeepSeek, GLM, MiniMax, Qwen, and more. | `NOVITA_API_KEY` |
@@ -91,11 +92,11 @@ To configure your chosen provider, see available options, or select a model, vis
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**First-time users:**
On the welcome screen the first time you open goose, you have these options:
<OnboardingProviderSetup />
<Tabs groupId="setup">
<TabItem value="apikey" label="Quick Setup" default>
1. Choose `Quick Setup with API Key`.
@@ -111,34 +112,34 @@ To configure your chosen provider, see available options, or select a model, vis
4. When you return to goose Desktop, you're ready to begin your first session.
</TabItem>
<TabItem value="tetrate" label="Agent Router">
We recommend new users start with Agent Router by Tetrate. Tetrate provides access to multiple AI models with built-in rate limiting and automatic failover.
We recommend new users start with Agent Router by Tetrate. Tetrate provides access to multiple AI models with built-in rate limiting and automatic failover.
:::info Free Credits Offer
You'll receive $10 in free credits the first time you automatically authenticate with Tetrate through goose. This offer is available to both new and existing Tetrate users.
:::
1. Choose `Agent Router by Tetrate`.
1. Choose `Agent Router by Tetrate`.
2. goose will open a browser window for you to authenticate with Tetrate, or create a new account if you don't have one already.
3. When you return to goose Desktop, you're ready to begin your first session.
</TabItem>
<TabItem value="openrouter" label="OpenRouter">
1. Choose `Automatic setup with OpenRouter`.
1. Choose `Automatic setup with OpenRouter`.
2. goose will open a browser window for you to authenticate with OpenRouter, or create a new account if you don't have one already.
3. When you return to the goose Desktop, you're ready to begin your first session.
</TabItem>
<TabItem value="others" label="Other Providers">
1. If you have a specific provider you want to use with goose, and an API key from that provider, choose `Other Providers`.
2. Find the provider of your choice and click its `Configure` button. If you don't see your provider in the list, click `Add Custom Provider` at the bottom of the window to [configure a custom provider](#configure-custom-provider).
1. If you have a specific provider you want to use with goose, and an API key from that provider, choose `Other Providers`.
2. Find the provider of your choice and click its `Configure` button. If you don't see your provider in the list, click `Add Custom Provider` at the bottom of the window to [configure a custom provider](#configure-custom-provider).
3. Depending on your provider, you'll need to input your API Key, API Host, or other optional [parameters](#available-providers). Click the `Submit` button to authenticate and begin your first session.
:::info Ollama Model Detection
For Ollama users, all locally installed models display automatically in the model selection dropdown.
:::
</TabItem>
</Tabs>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar
2. Click the `Settings` button on the sidebar
3. Click the `Models` tab
@@ -166,7 +167,7 @@ To configure your chosen provider, see available options, or select a model, vis
4. Click `Reset Provider and Model` to clear your current settings and return to the welcome screen
</TabItem>
<TabItem value="cli" label="goose CLI">
1. In your terminal, run the following command:
1. In your terminal, run the following command:
```sh
goose configure
@@ -175,59 +176,59 @@ To configure your chosen provider, see available options, or select a model, vis
2. Select `Configure Providers` from the menu and press `Enter`.
```
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
// highlight-start
│ ● Configure Providers (Change provider or update credentials)
// highlight-end
│ ○ Custom Providers
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
│ ○ Custom Providers
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
```
3. Choose a model provider and press `Enter`. Use the arrow keys (↑/↓) to move through the options, or start typing to filter the list.
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◆ Which model provider should we use?
│ ○ Amazon Bedrock
│ ○ Amazon SageMaker TGI
│ ○ Amazon Bedrock
│ ○ Amazon SageMaker TGI
// highlight-start
│ ● Anthropic (Claude and other models from Anthropic)
// highlight-end
│ ○ Azure OpenAI
│ ○ Azure OpenAI
│ ○ Claude Code CLI
│ ○ ...
└
└
```
4. Enter your API key (and any other configuration details) when prompted.
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◇ Which model provider should we use?
│ Anthropic
│ Anthropic
│
◆ Provider Anthropic requires ANTHROPIC_API_KEY, please enter a value
// highlight-start
│ ▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪
// highlight-end
└
└
```
If you're just changing models, skip any prompts to update the provider configuration.
5. Enter your desired `ANTHROPIC_HOST` or press `Enter` to use the default.
5. Enter your desired `ANTHROPIC_HOST` or press `Enter` to use the default.
```
◆ Provider Anthropic requires ANTHROPIC_HOST, please enter a value
@@ -239,7 +240,7 @@ To configure your chosen provider, see available options, or select a model, vis
- Select the model from a list
- Search for the model by name
- Enter the model name directly
```
│
◇ Model fetch complete
@@ -252,7 +253,7 @@ To configure your chosen provider, see available options, or select a model, vis
◒ Checking your configuration...
└ Configuration saved successfully
```
This change takes effect the next time you start a session.
:::note
@@ -385,7 +386,7 @@ Custom providers must use OpenAI, Anthropic, or Ollama compatible API formats. T
4. Click `Configure providers`
5. Click `Add Custom Provider` at the bottom of the window
6. Fill in the provider details:
- **Provider Type**:
- **Provider Type**:
- `OpenAI Compatible` (most common)
- `Anthropic Compatible`
- `Ollama Compatible`
@@ -404,7 +405,7 @@ Custom providers must use OpenAI, Anthropic, or Ollama compatible API formats. T
</TabItem>
<TabItem value="cli" label="goose CLI">
1. In your terminal, run the following command:
1. In your terminal, run the following command:
```sh
goose configure
@@ -413,38 +414,38 @@ Custom providers must use OpenAI, Anthropic, or Ollama compatible API formats. T
2. Select `Custom Providers`. Use the arrow keys (↑/↓) to move through the options.
```sh
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
│ ○ Configure Providers
// highlight-start
│ ● Custom Providers (Add custom provider with compatible API)
// highlight-end
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
```
3. Select `Add A Custom Provider`
```sh
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Custom Providers
│ Custom Providers
│
◆ What would you like to do?
// highlight-start
│ ● Add A Custom Provider (Add a new OpenAI/Anthropic/Ollama compatible Provider)
// highlight-end
│ ○ Remove Custom Provider
└
└
```
4. Follow the prompts to enter the provider details:
- **API Type**:
- **API Type**:
- `OpenAI Compatible` (most common)
- `Anthropic Compatible`
- `Ollama Compatible`
@@ -523,8 +524,8 @@ Custom providers must use OpenAI, Anthropic, or Ollama compatible API formats. T
</TabItem>
<TabItem value="cli" label="goose CLI">
1. In your terminal, run the following command:
1. In your terminal, run the following command:
```sh
goose configure
@@ -533,40 +534,40 @@ Custom providers must use OpenAI, Anthropic, or Ollama compatible API formats. T
2. Select `Configure Providers` from the menu and press `Enter`.
```sh
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
// highlight-start
│ ● Configure Providers (Change provider or update credentials)
// highlight-end
│ ○ Custom Providers
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
│ ○ Custom Providers
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
```
3. Select the custom provider you want to update and press `Enter`. Use the arrow keys (↑/↓) to move through the options, or start typing to filter the list.
```sh
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◆ Which model provider should we use?
│ ○ Amazon Bedrock
│ ○ Amazon SageMaker TGI
│ ○ Amazon Bedrock
│ ○ Amazon SageMaker TGI
│ ○ Anthropic
│ ○ Azure OpenAI
│ ○ Claude Code CLI
│ ○ Azure OpenAI
│ ○ Claude Code CLI
// highlight-start
│ ● Corporate API (Custom Corporate API provider)
// highlight-end
│ ○ Cursor Agent
│ ○ Cursor Agent
│ ○ ...
└
└
```
4. Follow the prompts to update the fields.
@@ -598,8 +599,8 @@ Your changes are available in your next goose session.
</TabItem>
<TabItem value="cli" label="goose CLI">
1. In your terminal, run the following command:
1. In your terminal, run the following command:
```sh
goose configure
@@ -608,34 +609,34 @@ Your changes are available in your next goose session.
2. Select `Custom Providers`. Use the arrow keys (↑/↓) to move through the options.
```sh
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
│ ○ Configure Providers
// highlight-start
│ ● Custom Providers (Add custom provider with compatible API)
// highlight-end
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
│ ○ Add Extension
│ ○ Toggle Extensions
│ ○ Remove Extension
│ ○ goose Settings
└
```
3. Select `Remove Custom Provider`.
```sh
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Custom Providers
│ Custom Providers
│
◆ What would you like to do?
│ ○ Add A Custom Provider
│ ○ Add A Custom Provider
// highlight-start
│ ● Remove Custom Provider (Remove an existing custom provider)
// highlight-end
└
└
```
4. Select the custom provider you want to remove.
@@ -658,7 +659,7 @@ Your changes are available in your next goose session.
## Using goose for Free
goose is a free and open source AI agent that you can start using right away, but not all supported [LLM Providers][providers] provide a free tier.
goose is a free and open source AI agent that you can start using right away, but not all supported [LLM Providers][providers] provide a free tier.
Below, we outline a couple of free options and how to get started with them.
@@ -672,7 +673,7 @@ Groq provides free access to open source (open weight) models with high-speed in
Groq offers several open source models that support tool calling, including:
- **moonshotai/kimi-k2-instruct-0905** - Mixture-of-Experts model with 1 trillion parameters, optimized for agentic intelligence and tool use
- **qwen/qwen3-32b** - 32.8 billion parameter model with advanced reasoning and multilingual capabilities
- **qwen/qwen3-32b** - 32.8 billion parameter model with advanced reasoning and multilingual capabilities
- **llama-3.3-70b-versatile** - Meta's Llama 3.3 model for versatile applications
- **llama-3.1-8b-instant** - Meta's Llama 3.1 model for fast inference
@@ -682,7 +683,7 @@ To set up Groq with goose, follow these steps:
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar.
2. Click the `Settings` button on the sidebar.
@@ -694,7 +695,7 @@ To set up Groq with goose, follow these steps:
</TabItem>
<TabItem value="cli" label="goose CLI">
1. Run:
1. Run:
```sh
goose configure
```
@@ -723,7 +724,7 @@ To set up EmpirioLabs with goose, follow these steps:
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar.
2. Click the `Settings` button on the sidebar.
@@ -735,7 +736,7 @@ To set up EmpirioLabs with goose, follow these steps:
</TabItem>
<TabItem value="cli" label="goose CLI">
1. Run:
1. Run:
```sh
goose configure
```
@@ -762,7 +763,7 @@ To set up FuturMix with goose, follow these steps:
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar.
2. Click the `Settings` button on the sidebar.
@@ -774,7 +775,7 @@ To set up FuturMix with goose, follow these steps:
</TabItem>
<TabItem value="cli" label="goose CLI">
1. Run:
1. Run:
```sh
goose configure
```
@@ -801,7 +802,7 @@ To set up Novita AI with goose, follow these steps:
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar.
2. Click the `Settings` button on the sidebar.
@@ -813,7 +814,7 @@ To set up Novita AI with goose, follow these steps:
</TabItem>
<TabItem value="cli" label="goose CLI">
1. Run:
1. Run:
```sh
goose configure
```
@@ -868,7 +869,7 @@ To set up Google Gemini with goose, follow these steps:
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
**To update your LLM provider and API key:**
**To update your LLM provider and API key:**
1. Click the <PanelLeft className="inline" size={16} /> button in the top-left to open the sidebar.
2. Click the `Settings` button on the sidebar.
@@ -879,7 +880,7 @@ To set up Google Gemini with goose, follow these steps:
</TabItem>
<TabItem value="cli" label="goose CLI">
1. Run:
1. Run:
```sh
goose configure
```
@@ -899,7 +900,7 @@ To set up Google Gemini with goose, follow these steps:
│
◇ Provider Google Gemini requires GOOGLE_API_KEY, please enter a value
│▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪
│
│
◇ Enter a model from that provider:
│ gemini-2.0-flash-exp
│
@@ -1022,14 +1023,14 @@ Here are some local providers we support:
</TabItem>
<TabItem value="deepseek" label="DeepSeek-R1">
The native `DeepSeek-r1` model doesn't support tool calling, however, we have a [custom model](https://ollama.com/michaelneale/deepseek-r1-goose) you can use with goose.
The native `DeepSeek-r1` model doesn't support tool calling, however, we have a [custom model](https://ollama.com/michaelneale/deepseek-r1-goose) you can use with goose.
:::warning
Note that this is a 70B model size and requires a powerful device to run smoothly.
:::
1. [Download Ollama](https://ollama.com/download).
1. [Download Ollama](https://ollama.com/download).
2. In a terminal window, run the following command to install the custom DeepSeek-r1 model:
```sh
@@ -1045,44 +1046,44 @@ Here are some local providers we support:
4. Choose to `Configure Providers`
```
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
│ ● Configure Providers (Change provider or update credentials)
│ ○ Toggle Extensions
│ ○ Add Extension
└
│ ○ Toggle Extensions
│ ○ Add Extension
└
```
5. Choose `Ollama` as the model provider
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◆ Which model provider should we use?
│ ○ Anthropic
│ ○ Databricks
│ ○ Google Gemini
│ ○ Groq
│ ○ Anthropic
│ ○ Databricks
│ ○ Google Gemini
│ ○ Groq
│ ● Ollama (Local open source models)
│ ○ OpenAI
│ ○ OpenRouter
└
│ ○ OpenAI
│ ○ OpenRouter
└
```
6. Enter the host where your model is running
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│ Ollama
│
◆ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://localhost:11434
@@ -1092,17 +1093,17 @@ Here are some local providers we support:
7. Enter the installed model from above
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│ Ollama
│
◇ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://localhost:11434
│
│ http://localhost:11434
│
◇ Enter a model from that provider:
│ michaelneale/deepseek-r1-goose
│
@@ -1112,7 +1113,7 @@ Here are some local providers we support:
```
</TabItem>
<TabItem value="others" label="Other Models" default>
1. [Download Ollama](https://ollama.com/download).
1. [Download Ollama](https://ollama.com/download).
2. In a terminal, run any [model supporting tool-calling](https://ollama.com/search?c=tools)
Example:
@@ -1130,32 +1131,32 @@ Here are some local providers we support:
4. Choose to `Configure Providers`
```
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
│ ● Configure Providers (Change provider or update credentials)
│ ○ Toggle Extensions
│ ○ Add Extension
└
│ ○ Toggle Extensions
│ ○ Add Extension
└
```
5. Choose `Ollama` as the model provider
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◆ Which model provider should we use?
│ ○ Anthropic
│ ○ Databricks
│ ○ Google Gemini
│ ○ Groq
│ ○ Anthropic
│ ○ Databricks
│ ○ Google Gemini
│ ○ Groq
│ ● Ollama (Local open source models)
│ ○ OpenAI
│ ○ OpenRouter
└
│ ○ OpenAI
│ ○ OpenRouter
└
```
6. Enter the host where your model is running
@@ -1168,13 +1169,13 @@ Here are some local providers we support:
:::
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│ Ollama
│
◆ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://localhost:11434
@@ -1185,13 +1186,13 @@ Here are some local providers we support:
7. Enter the model you have running
```
┌ goose-configure
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│ Ollama
│
◇ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://localhost:11434
@@ -1207,7 +1208,7 @@ Here are some local providers we support:
:::tip Context Length
If you notice that goose is having trouble using extensions or is ignoring [.goosehints](/docs/guides/context-engineering/using-goosehints), it is likely that the model's default context length of 4096 tokens is too low. Set the `OLLAMA_CONTEXT_LENGTH` environment variable to a [higher value](https://github.com/ollama/ollama/blob/main/docs/faq.mdx#how-can-i-specify-the-context-window-size).
:::
</TabItem>
</Tabs>
</TabItem>
@@ -1320,7 +1321,7 @@ Here are some local providers we support:
docker model pull hf.co/unsloth/gemma-3n-e4b-it-gguf:q6_k
```
4. Configure goose to use Docker Model Runner, using the OpenAI API compatible endpoint:
4. Configure goose to use Docker Model Runner, using the OpenAI API compatible endpoint:
```sh
goose configure
@@ -1329,16 +1330,16 @@ Here are some local providers we support:
5. Choose to `Configure Providers`
```
┌ goose-configure
┌ goose-configure
│
◆ What would you like to configure?
│ ● Configure Providers (Change provider or update credentials)
│ ○ Toggle Extensions
│ ○ Add Extension
└
│ ○ Toggle Extensions
│ ○ Add Extension
└
```
6. Choose `OpenAI` as the model provider:
6. Choose `OpenAI` as the model provider:
```
┌ goose-configure
@@ -1354,7 +1355,7 @@ Here are some local providers we support:
│ ○ OpenRouter
```
7. Configure Docker Model Runner endpoint as the `OPENAI_HOST`:
7. Configure Docker Model Runner endpoint as the `OPENAI_HOST`:
```
┌ goose-configure
@@ -1370,10 +1371,10 @@ Here are some local providers we support:
└
```
The default value for the host-side port Docker Model Runner is 12434, so the `OPENAI_HOST` value could be:
`http://localhost:12434`.
The default value for the host-side port Docker Model Runner is 12434, so the `OPENAI_HOST` value could be:
`http://localhost:12434`.
8. Configure the base path:
8. Configure the base path:
```
◆ Provider OpenAI requires OPENAI_BASE_PATH, please enter a value
@@ -1390,7 +1391,7 @@ Here are some local providers we support:
◇ Enter a model from that provider:
│ gpt-4o
│
◒ Checking your configuration...
◒ Checking your configuration...
└ Configuration saved successfully
```
</TabItem>
@@ -1455,6 +1456,39 @@ Beyond single-model setups, goose supports [multi-model configurations](/docs/gu
- **Planning Mode** - Use a dedicated planner model to create detailed project breakdowns before execution
- **Subagents** - Delegate scoped tasks to isolated sessions to keep your primary workflow focused and efficient
## Meta Muse Spark Reasoning Effort
Meta's Muse Spark models support a configurable reasoning effort that maps to Meta's `reasoning_effort` request parameter:
- **Low** - Faster responses, lighter reasoning
- **Medium** - Balanced reasoning depth and latency
- **High** - Deeper reasoning, higher latency
- **Max** - Sent as `xhigh`, the deepest reasoning level Meta supports
<Tabs groupId="interface">
<TabItem value="ui" label="goose Desktop" default>
When selecting a Muse Spark model, a "Thinking Effort" dropdown appears automatically. Select your preference and the setting persists across sessions.
</TabItem>
<TabItem value="cli" label="goose CLI">
When you run `goose configure` and select a Muse Spark model, you'll be prompted to choose a thinking effort:
```
◆ Select thinking effort:
│ ● Off - No extended thinking
│ ○ Low - Better latency, lighter reasoning
│ ○ Medium - Moderate thinking
│ ○ High - Deep reasoning
│ ○ Max - No constraints on thinking depth
```
You can also set this globally with the `GOOSE_THINKING_EFFORT` environment variable (`off`, `low`, `medium`, `high`, or `max`).
</TabItem>
</Tabs>
:::note
Muse Spark always reasons and has no way to disable it, so choosing `off` is clamped to `low` (the lightest level Meta supports) rather than omitting the `reasoning_effort` parameter.
:::
## Gemini 3 Thinking Levels
Gemini 3 models support configurable thinking levels to balance response latency and reasoning depth:
@@ -1469,12 +1503,12 @@ When thinking is enabled, you can view the model's reasoning process. See [Viewi
<TabItem value="ui" label="goose Desktop" default>
When selecting a Gemini 3 model, a "Thinking Level" dropdown appears automatically. Select your preference and the setting persists across sessions.
</TabItem>
<TabItem value="cli" label="goose CLI">
**Interactive configuration:**
When you run `goose configure` and select a Gemini 3 model, you'll be prompted to choose a thinking level:
```
◆ Select thinking level for Gemini 3:
│ ● Low - Better latency, lighter reasoning
@@ -1505,16 +1539,16 @@ Some models expose their internal reasoning or "chain of thought" as part of the
<TabItem value="ui" label="goose Desktop" default>
Reasoning output appears automatically in a collapsible **"Show reasoning"** toggle above the model's response. Click it to expand and view the model's thought process.
</TabItem>
<TabItem value="cli" label="goose CLI">
Reasoning output is **hidden by default** in the CLI. To display it, set the `GOOSE_CLI_SHOW_THINKING` environment variable:
```bash
export GOOSE_CLI_SHOW_THINKING=1
```
When enabled, reasoning appears under a "Thinking:" header in dimmed text before the model's main response.
:::note
This requires stdout to be a terminal (reasoning output won't appear when piping output to a file or another command).
:::