Docs

OpenAI-compatible API documentation

Copy one setup prompt into your existing coding agent, or use the API reference and manual client configurations below.

Install with one prompt

Copy this prompt into the coding agent or AI editor you already use. It will identify the client, ask for your API key, add Yolo-Auto without removing existing providers, and verify the connection.

Configure the coding agent or AI code editor I am currently using to use Yolo-Auto as a model provider. Perform the setup for me instead of only describing it.

Provider details:
- Name: Yolo-Auto
- API protocol: OpenAI-compatible Chat Completions
- Base URL: https://yolo-auto.com/v1
- Default model: qwen3.8-27b
- Context window: 131072
- API key environment variable: YOLO_AUTO_API_KEY

Instructions:
- Identify the current coding agent or editor, its installed version, and its local user-level configuration before making changes.
- Ask me for my Yolo-Auto API key now if I have not provided it. Prefer a hidden credential prompt when available.
- Treat the API key as a secret. Never print the full key, place it in command history or logs, or store it in a repository.
- Use the agent's native custom OpenAI-compatible provider support when available. Preserve all existing providers and unrelated settings.
- Store the key in the agent's secure credential store or a user-level environment/config file that is excluded from version control.
- Add Yolo-Auto and make qwen3.8-27b available. Do not remove another provider or change my existing default model unless I ask.
- If this agent cannot use an OpenAI-compatible provider directly, use the smallest supported local compatibility bridge. Explain why it is needed and ask before installing a dependency.
- Validate the resulting configuration, then make an authenticated GET request to https://yolo-auto.com/v1/models or use the agent's safest equivalent connection check. Keep the key redacted.
- Finish by reporting the exact files or settings changed and the one command or action I should use to start coding with Yolo-Auto.

Base URL

https://yolo-auto.com/v1

Authentication

Authorization: Bearer yolo_...

Model IDs

"qwen3.8-27b"

Desktop app

Download the desktop app, grab other platform builds, or browse the source on GitHub.

Download for Windows Download for Mac Other releases GitHub

Mac download is the Apple Silicon DMG. Intel Mac and Linux builds are available under Other releases.

Yolo-Auto Desktop v0.1.7
Windows download: https://github.com/yolo-auto-org/yolo-auto-desktop/releases/download/v0.1.7/YOLO-Auto-Desktop-Setup-0.1.7-x64.exe
Mac download: https://github.com/yolo-auto-org/yolo-auto-desktop/releases/download/v0.1.7/YOLO-Auto-Desktop-0.1.7-arm64.dmg
Other releases: https://github.com/yolo-auto-org/yolo-auto-desktop/releases
GitHub: https://github.com/yolo-auto-org/yolo-auto-desktop
HTTPS clone: git clone https://github.com/yolo-auto-org/yolo-auto-desktop
SSH clone: git clone git@github.com:yolo-auto-org/yolo-auto-desktop.git

OpenAI-Compatible API Endpoints

Use base URL https://yolo-auto.com/v1 and send Authorization: Bearer yolo_YOUR_KEY. Yolo-Auto implements a focused OpenAI-compatible surface rather than every OpenAI API route.

GET /v1/modelsList the public model IDs available to compatible clients.

POST /v1/chat/completionsSend messages and create a normal or streaming chat completion.

GET /v1/usageRead request, token, and quota metadata for the authenticated API key.

Use the request examples below to verify the endpoint, API key, model ID, JSON body, and streaming behavior before configuring a third-party client.

Request format and vision

Qwen3.8-27B accepts text and image input through OpenAI-compatible multimodal messages. Chat completion request bodies may contain up to 20 MB of JSON.

Use a public or signed image URL when possible. Base64 data URLs are supported, but their encoding increases the request size and counts toward the total JSON limit.

Capacity and retries

Paid plans have fixed monthly prices with no per-token overage fees. Fair use, bounded queues, and shared-capacity availability apply.

Build clients for transient capacity responses. Requests can wait, time out, or return a retryable error during busy periods. Your subscription price does not change.

Plan workload guide

Agent counts are typical-fit estimates and vary with request size, duration, and workload pattern.

Plan	Typical agent fit	Context
Builder	Roughly 3-4	128K
Pro	Roughly 5-6	256K

Agent estimates are workload guidance, not guaranteed simultaneous capacity.

Client guidance

Keep parallel agent work moderate and adapt when requests queue or return HTTP 429.
Cancel abandoned requests and streams promptly.
Honor Retry-After on HTTP 429 responses and retry with jitter.
Do not submit duplicate work while the original request is waiting.

Manual provider references

Use the client-specific sections below if you want to inspect or apply the configuration yourself.

Pi

Configure Pi models.json.

Use this provider block in your Pi model configuration.

{
  "providers": {
    "Yolo-Auto": {
      "baseUrl": "https://yolo-auto.com/v1",
      "api": "openai-completions",
      "apiKey": "YOUR_yolo_API_KEY_HERE",
      "compat": {
        "supportsDeveloperRole": false,
        "supportsStore": false,
        "supportsReasoningEffort": true,
        "thinkingFormat": "qwen-chat-template"
      },
      "models": [
        {
          "id": "qwen3.8-27b",
          "name": "qwen3.8-27b",
          "reasoning": true,
          "input": [
            "text",
            "image"
          ],
          "contextWindow": 131072,
          "cost": {
            "input": 0,
            "output": 0,
            "cacheRead": 0,
            "cacheWrite": 0
          }
        }
      ]
    }
  }
}

Prompt for your current agent

Paste this into your current coding agent and let it make the Pi config changes.

Configure this machine's Pi agent to use Yolo-Auto.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Preserve all existing Pi providers, models, auth, comments/format as much as possible.
- Update or create ~/.pi/agent/models.json and merge in this provider block under providers.Yolo-Auto:
{
  "providers": {
    "Yolo-Auto": {
      "baseUrl": "https://yolo-auto.com/v1",
      "api": "openai-completions",
      "apiKey": "PASTE_YOUR_YOLO_AUTO_API_KEY_HERE",
      "compat": {
        "supportsDeveloperRole": false,
        "supportsStore": false,
        "supportsReasoningEffort": true,
        "thinkingFormat": "qwen-chat-template"
      },
      "models": [
        {
          "id": "qwen3.8-27b",
          "name": "qwen3.8-27b",
          "reasoning": true,
          "input": [
            "text",
            "image"
          ],
          "contextWindow": 131072,
          "cost": {
            "input": 0,
            "output": 0,
            "cacheRead": 0,
            "cacheWrite": 0
          }
        }
      ]
    }
  }
}
- If Pi has a default model/provider setting, set the default model to qwen3.8-27b for Yolo-Auto only when that setting exists and can be changed safely.
- Validate the JSON after editing.
- Report the exact files changed and a one-command way for me to test it.

OpenClaw

Configure an OpenClaw agent models.json.

OpenClaw stores agent config under ~/.openclaw/agents/. For the agent you run, update agents/<agent-name>/models.json.

{
  "providers": {
    "yolo-auto": {
      "baseUrl": "https://yolo-auto.com/v1",
      "apiKey": "ENTER_YOUR_yolo_KEY_HERE",
      "api": "openai-completions",
      "models": [
        {
          "id": "qwen3.8-27b",
          "name": "Qwen 3.8 27B",
          "contextWindow": 128000,
          "reasoning": true,
          "input": [
            "text",
            "image"
          ]
        }
      ]
    }
  }
}

Prompt for your current agent

Paste this into your current coding agent and let it update the selected OpenClaw agent.

Configure my existing OpenClaw agent to use Yolo-Auto.

Requirements:
- Ask me which OpenClaw agent name to configure if it is not obvious from ~/.openclaw/agents/.
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Preserve all existing providers and unrelated settings.
- Update or create ~/.openclaw/agents/<agent-name>/models.json and merge in this provider block under providers.yolo-auto:
{
  "providers": {
    "yolo-auto": {
      "baseUrl": "https://yolo-auto.com/v1",
      "apiKey": "PASTE_YOUR_YOLO_AUTO_API_KEY_HERE",
      "api": "openai-completions",
      "models": [
        {
          "id": "qwen3.8-27b",
          "name": "Qwen 3.8 27B",
          "contextWindow": 128000,
          "reasoning": true,
          "input": [
            "text",
            "image"
          ]
        }
      ]
    }
  }
}
- Keep the model id qwen3.8-27b and contextWindow 128000.
- Validate the JSON after editing.
- Report the exact files changed and how I should restart/test OpenClaw.

Hermes Agent

Set Hermes custom endpoint values.

Follow Hermes Agent's custom endpoint setup and use these values.

Provider: custom
Base URL: https://yolo-auto.com/v1
API key: YOUR_yolo_API_KEY_HERE
Default model: qwen3.8-27b
API mode: chat_completions
Context length: 131072

Prompt for your current agent

Paste this into your current coding agent and let it configure Hermes.

Configure Hermes Agent to use Yolo-Auto as its custom OpenAI-compatible endpoint.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Preserve existing Hermes config except the main model provider/base/model values needed below.
- Set these values:
Provider: custom
Base URL: https://yolo-auto.com/v1
API key: PASTE_YOUR_YOLO_AUTO_API_KEY_HERE
Default model: qwen3.8-27b
API mode: chat_completions
Context length: 131072
- Prefer Hermes' CLI when available:
  hermes config set model.provider custom
  hermes config set model.base_url https://yolo-auto.com/v1
  hermes config set model.default qwen3.8-27b
  hermes config set model.context_length 131072
  hermes config set model.api_mode chat_completions
- Also set OPENAI_API_KEY and OPENAI_BASE_URL in the Hermes .env location for this OS/HERMES_HOME if Hermes uses it.
- Validate by showing the sanitized effective provider/base/model settings, with the API key redacted.
- Report the exact files/commands changed and how I should restart/test Hermes.

OpenCode

Add a Yolo-Auto OpenAI-compatible provider.

Add this provider to opencode.json. Keep your real key in YOLO_AUTO_API_KEY.

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "yolo-auto": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Yolo-Auto",
      "options": {
        "baseURL": "https://yolo-auto.com/v1",
        "apiKey": "{env:YOLO_AUTO_API_KEY}"
      },
      "models": {
        "qwen3.8-27b": {
          "name": "Qwen3.8 27B",
          "limit": {
            "context": 131072,
            "output": 32768
          },
          "attachment": true,
          "modalities": {
            "input": [
              "text",
              "image"
            ],
            "output": [
              "text"
            ]
          }
        }
      }
    }
  }
}

Prompt for your current agent

Paste this into your current coding agent and let it configure OpenCode.

Configure OpenCode to use Yolo-Auto.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Preserve existing OpenCode providers and unrelated settings.
- Update or create the appropriate opencode.json for this workspace/user.
- Add or merge this provider under provider.yolo-auto:
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "yolo-auto": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Yolo-Auto",
      "options": {
        "baseURL": "https://yolo-auto.com/v1",
        "apiKey": "{env:YOLO_AUTO_API_KEY}"
      },
      "models": {
        "qwen3.8-27b": {
          "name": "Qwen3.8 27B",
          "limit": {
            "context": 131072,
            "output": 32768
          },
          "attachment": true,
          "modalities": {
            "input": [
              "text",
              "image"
            ],
            "output": [
              "text"
            ]
          }
        }
      }
    }
  }
}
- Store the real key in YOLO_AUTO_API_KEY or OpenCode's normal credential store; do not hardcode the secret into a committed repo file unless I explicitly ask.
- Configure/select model qwen3.8-27b.
- Validate the JSON after editing.
- Report the exact files changed and how I should run/test OpenCode.

Aider

Use Aider with an OpenAI-compatible base URL.

Aider uses an OpenAI-compatible base URL and the openai/ model prefix.

export AIDER_OPENAI_API_BASE="https://yolo-auto.com/v1"
export AIDER_OPENAI_API_KEY="YOUR_yolo_API_KEY_HERE"
export AIDER_MODEL="openai/qwen3.8-27b"

# Or run one-off: aider --openai-api-base "https://yolo-auto.com/v1" --openai-api-key "YOUR_yolo_API_KEY_HERE" --model openai/qwen3.8-27b

Prompt for your current agent

Paste this into your current coding agent and let it configure Aider.

Configure Aider to use Yolo-Auto through its OpenAI-compatible settings.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Prefer project-local config/env files only if they are gitignored; otherwise tell me what shell exports to add.
- Set these values:
export AIDER_OPENAI_API_BASE="https://yolo-auto.com/v1"
export AIDER_OPENAI_API_KEY="PASTE_YOUR_YOLO_AUTO_API_KEY_HERE"
export AIDER_MODEL="openai/qwen3.8-27b"

# Or run one-off: aider --openai-api-base "https://yolo-auto.com/v1" --openai-api-key "PASTE_YOUR_YOLO_AUTO_API_KEY_HERE" --model openai/qwen3.8-27b
- Use model openai/qwen3.8-27b.
- Do not commit or expose the API key.
- Report the exact files changed and a one-command test using aider.

Cline

Use the OpenAI Compatible provider in VS Code.

In Cline settings, choose OpenAI Compatible, then enter these values.

API Provider: OpenAI Compatible
Base URL: https://yolo-auto.com/v1
API Key: YOUR_yolo_API_KEY_HERE
Model ID: qwen3.8-27b
Context window: 131072
Supports images: false

Prompt for your current agent

Paste this into your current coding agent and let it configure Cline or give exact UI steps.

Configure Cline to use Yolo-Auto via the OpenAI Compatible provider.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- If Cline settings can be safely edited as JSON on this machine, update them; otherwise give me exact UI steps.
- Use these values:
API Provider: OpenAI Compatible
Base URL: https://yolo-auto.com/v1
API Key: PASTE_YOUR_YOLO_AUTO_API_KEY_HERE
Model ID: qwen3.8-27b
Context window: 131072
Supports images: false
- Preserve unrelated Cline/VS Code settings.
- Report the exact files changed or the exact UI fields I need to set.

Roo Code

Use Roo Code's OpenAI Compatible provider.

In Roo Code settings, choose OpenAI Compatible, then enter these values.

API Provider: OpenAI Compatible
Base URL: https://yolo-auto.com/v1
API Key: YOUR_yolo_API_KEY_HERE
Model ID: qwen3.8-27b
Context window: 131072
Note: Roo Code requires OpenAI-compatible native tool calling from the selected model.

Prompt for your current agent

Paste this into your current coding agent and let it configure Roo Code or give exact UI steps.

Configure Roo Code to use Yolo-Auto via the OpenAI Compatible provider.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- If Roo Code settings can be safely edited as JSON on this machine, update them; otherwise give me exact UI steps.
- Use these values:
API Provider: OpenAI Compatible
Base URL: https://yolo-auto.com/v1
API Key: PASTE_YOUR_YOLO_AUTO_API_KEY_HERE
Model ID: qwen3.8-27b
Context window: 131072
Note: Roo Code requires OpenAI-compatible native tool calling from the selected model.
- Preserve unrelated Roo Code/VS Code settings.
- Warn me if the selected model/tool-calling compatibility cannot be verified locally.
- Report the exact files changed or the exact UI fields I need to set.

Continue

Add a Yolo-Auto model to Continue config.

Add this model entry to Continue's config YAML.

name: Yolo-Auto
version: 0.0.1
schema: v1

models:
  - name: Yolo-Auto Qwen3.8 27B
    provider: openai
    model: qwen3.8-27b
    apiBase: https://yolo-auto.com/v1
    apiKey: YOUR_yolo_API_KEY_HERE
    useResponsesApi: false

Prompt for your current agent

Paste this into your current coding agent and let it configure Continue.

Configure Continue to use Yolo-Auto as an OpenAI-compatible model provider.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Locate Continue's config YAML/JSON for this install and preserve unrelated models/settings.
- Add or merge this model entry:
name: Yolo-Auto
version: 0.0.1
schema: v1

models:
  - name: Yolo-Auto Qwen3.8 27B
    provider: openai
    model: qwen3.8-27b
    apiBase: https://yolo-auto.com/v1
    apiKey: PASTE_YOUR_YOLO_AUTO_API_KEY_HERE
    useResponsesApi: false
- Keep useResponsesApi: false so Continue uses chat completions.
- Do not commit or expose the API key.
- Validate the config syntax and report how I should restart/test Continue.

Claude Code

Bridge through LiteLLM's Anthropic-compatible endpoint.

Claude Code expects Anthropic Messages API. Use LiteLLM as a local bridge to Yolo-Auto's OpenAI-compatible endpoint.

1. Save this as `litellm-yolo-auto.yaml`

model_list:
  - model_name: qwen3.8-27b
    litellm_params:
      model: openai/qwen3.8-27b
      api_key: os.environ/YOLO_AUTO_API_KEY
      api_base: https://yolo-auto.com/v1

litellm_settings:
  master_key: os.environ/LITELLM_MASTER_KEY

2. Start the bridge and launch Claude Code

# Install LiteLLM proxy support
uv tool install 'litellm[proxy]'

# Set secrets locally. Use your real yolo_ key and generate your own proxy key.
export YOLO_AUTO_API_KEY="YOUR_yolo_API_KEY_HERE"
export LITELLM_MASTER_KEY="sk-local-proxy-key-change-me"

# Start the Anthropic-compatible bridge. Save the YAML above as litellm-yolo-auto.yaml first.
litellm --config ./litellm-yolo-auto.yaml --host 127.0.0.1 --port 4000

# In another shell, point Claude Code at LiteLLM's Anthropic Messages API bridge.
export ANTHROPIC_BASE_URL="http://127.0.0.1:4000"
export ANTHROPIC_AUTH_TOKEN="$LITELLM_MASTER_KEY"
export CLAUDE_CODE_ENABLE_GATEWAY_MODEL_DISCOVERY=1
claude --model qwen3.8-27b

Prompt for your current agent

Paste this into your current coding agent and let it set up the LiteLLM bridge.

Configure Claude Code to use Yolo-Auto through a local LiteLLM bridge.

Context:
- Claude Code expects an Anthropic Messages API endpoint.
- Yolo-Auto is OpenAI-compatible, so LiteLLM should bridge Claude Code -> LiteLLM /v1/messages -> Yolo-Auto /v1/chat/completions.

Requirements:
- Ask me for my Yolo-Auto API key if I have not provided it, and do not print the full key back to me.
- Install LiteLLM proxy support only if needed and after confirming the package manager/uv availability.
- Create or update a local litellm-yolo-auto.yaml with:
model_list:
  - model_name: qwen3.8-27b
    litellm_params:
      model: openai/qwen3.8-27b
      api_key: os.environ/YOLO_AUTO_API_KEY
      api_base: https://yolo-auto.com/v1

litellm_settings:
  master_key: os.environ/LITELLM_MASTER_KEY
- Set local environment variables without committing secrets:
  YOLO_AUTO_API_KEY=<my yolo_ key>
  LITELLM_MASTER_KEY=<a generated local proxy key>
  ANTHROPIC_BASE_URL=http://127.0.0.1:4000
  ANTHROPIC_AUTH_TOKEN=$LITELLM_MASTER_KEY
  CLAUDE_CODE_ENABLE_GATEWAY_MODEL_DISCOVERY=1
- Show me the command to start LiteLLM and the command to launch Claude Code with qwen3.8-27b.
- Report the exact files changed and keep all secrets redacted.

Request examples

List models

curl https://yolo-auto.com/v1/models \
  -H "Authorization: Bearer yolo_YOUR_KEY"

Chat completion

Streaming is recommended for long-context or long-output requests. When the upstream starts the response promptly, streaming reduces the risk of hitting the proxied read deadline before inference finishes.

curl https://yolo-auto.com/v1/chat/completions \
  -H "Authorization: Bearer yolo_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.8-27b",
    "messages": [
      { "role": "user", "content": "Hello from Yolo-Auto" }
    ],
    "stream": true
  }'

Vision chat completion

curl https://yolo-auto.com/v1/chat/completions \
  -H "Authorization: Bearer yolo_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.8-27b",
    "messages": [{
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": { "url": "https://example.com/image.png" }
        },
        { "type": "text", "text": "Describe this image." }
      ]
    }],
    "stream": true
  }'

Usage

curl https://yolo-auto.com/v1/usage \
  -H "Authorization: Bearer yolo_YOUR_KEY"

OpenAI SDK

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.YOLO_AUTO_API_KEY,
  baseURL: "https://yolo-auto.com/v1"
});

const response = await client.chat.completions.create({
  model: "qwen3.8-27b",
  messages: [{ role: "user", content: "Hello" }]
});

console.log(response.choices[0]?.message?.content);

OpenAI-compatible API documentation

Install with one prompt

Base URL

Authentication

Model IDs

Desktop app

OpenAI-Compatible API Endpoints

Request format and vision

Capacity and retries

Plan workload guide

Client guidance

Manual provider references

Pi

Prompt for your current agent

OpenClaw

Prompt for your current agent

Hermes Agent

Prompt for your current agent

OpenCode

Prompt for your current agent

Aider

Prompt for your current agent

Cline

Prompt for your current agent

Roo Code

Prompt for your current agent

Continue

Prompt for your current agent

Claude Code

1. Save this as litellm-yolo-auto.yaml

2. Start the bridge and launch Claude Code

Prompt for your current agent

Request examples

List models

Chat completion

Vision chat completion

Usage

OpenAI SDK

1. Save this as `litellm-yolo-auto.yaml`