---
title: "v0"
url: "/docs/providers/v0"
canonical_url: "https://docs.litellm.ai/docs/providers/v0"
type: "docs"
last_updated: "2026-10-09"
related:
  - "/docs/providers/triton-inference-server"
  - "/docs/providers/valkey_vector_stores"
---
# v0

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


## Overview

| Property | Details |
|-------|-------|
| Description | v0 provides AI models optimized for code generation, particularly for creating Next.js applications, React components, and modern web development. |
| Provider Route on LiteLLM | `v0/` |
| Link to Provider Doc | [v0 API Documentation ↗](https://v0.dev/docs/v0-model-api) |
| Base URL | `https://api.v0.dev/v1` |
| Supported Operations | [`/chat/completions`](/docs/providers/v0#usage---litellm-python-sdk) |

<br />
<br />

https://v0.dev/docs/v0-model-api

**We support ALL v0 models, just set `v0/` as a prefix when sending completion requests**

## Available Models

| Model | Description | Context Window | Max Output |
|-------|-------------|----------------|------------|
| `v0/v0-1.5-lg` | Large model for advanced code generation and reasoning | 512,000 tokens | 512,000 tokens |
| `v0/v0-1.5-md` | Medium model for everyday code generation tasks | 128,000 tokens | 128,000 tokens |
| `v0/v0-1.0-md` | Legacy medium model | 128,000 tokens | 128,000 tokens |

## Required Variables

```python showLineNumbers title="Environment Variables"
os.environ["V0_API_KEY"] = ""  # your v0 API key from v0.dev
```

Note: v0 API access requires a Premium or Team plan. Visit [v0.dev/chat/settings/billing](https://v0.dev/chat/settings/billing) to upgrade.

## Usage - LiteLLM Python SDK

### Non-streaming

```python showLineNumbers title="v0 Non-streaming Completion"
import os
import litellm
from litellm import completion

os.environ["V0_API_KEY"] = ""  # your v0 API key

messages = [{"content": "Create a React button component with hover effects", "role": "user"}]

# v0 call
response = completion(
    model="v0/v0-1.5-md", 
    messages=messages
)

print(response)
```

### Streaming

```python showLineNumbers title="v0 Streaming Completion"
import os
import litellm
from litellm import completion

os.environ["V0_API_KEY"] = ""  # your v0 API key

messages = [{"content": "Create a React button component with hover effects", "role": "user"}]

# v0 call with streaming
response = completion(
    model="v0/v0-1.5-md", 
    messages=messages,
    stream=True
)

for chunk in response:
    print(chunk)
```

### Vision/Multimodal Support

All v0 models support vision inputs, allowing you to send images along with text:

```python showLineNumbers title="v0 Vision/Multimodal"
import os
import litellm
from litellm import completion

os.environ["V0_API_KEY"] = ""  # your v0 API key

messages = [{
    "role": "user",
    "content": [
        {
            "type": "text",
            "text": "Recreate this UI design in React"
        },
        {
            "type": "image_url",
            "image_url": {
                "url": "https://example.com/ui-design.png"
            }
        }
    ]
}]

response = completion(
    model="v0/v0-1.5-lg",
    messages=messages
)

print(response)
```

### Function Calling

v0 supports function calling for structured outputs:

```python showLineNumbers title="v0 Function Calling"
import os
import litellm
from litellm import completion

os.environ["V0_API_KEY"] = ""  # your v0 API key

tools = [
    {
        "type": "function",
        "function": {
            "name": "create_component",
            "description": "Create a React component",
            "parameters": {
                "type": "object",
                "properties": {
                    "component_name": {
                        "type": "string",
                        "description": "The name of the component"
                    },
                    "props": {
                        "type": "array",
                        "items": {"type": "string"},
                        "description": "List of component props"
                    }
                },
                "required": ["component_name"]
            }
        }
    }
]

response = completion(
    model="v0/v0-1.5-md",
    messages=[{"role": "user", "content": "Create a Button component with onClick and disabled props"}],
    tools=tools,
    tool_choice="auto"
)

print(response)
```

## Usage - LiteLLM Proxy

Add the following to your LiteLLM Proxy configuration file:

```yaml showLineNumbers title="config.yaml"
model_list:
  - model_name: v0-large
    litellm_params:
      model: v0/v0-1.5-lg
      api_key: os.environ/V0_API_KEY

  - model_name: v0-medium
    litellm_params:
      model: v0/v0-1.5-md
      api_key: os.environ/V0_API_KEY

  - model_name: v0-legacy
    litellm_params:
      model: v0/v0-1.0-md
      api_key: os.environ/V0_API_KEY
```

Start your LiteLLM Proxy server:

```bash showLineNumbers title="Start LiteLLM Proxy"
litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000
```

**OpenAI SDK**

```python showLineNumbers title="v0 via Proxy - Non-streaming"
from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="your-proxy-api-key"       # Your proxy API key
)

# Non-streaming response
response = client.chat.completions.create(
    model="v0-medium",
    messages=[{"role": "user", "content": "Create a React card component"}]
)

print(response.choices[0].message.content)
```

```python showLineNumbers title="v0 via Proxy - Streaming"
from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="your-proxy-api-key"       # Your proxy API key
)

# Streaming response
response = client.chat.completions.create(
    model="v0-medium",
    messages=[{"role": "user", "content": "Create a React card component"}],
    stream=True
)

for chunk in response:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")
```

**LiteLLM SDK**

```python showLineNumbers title="v0 via Proxy - LiteLLM SDK"
import litellm

# Configure LiteLLM to use your proxy
response = litellm.completion(
    model="litellm_proxy/v0-medium",
    messages=[{"role": "user", "content": "Create a React card component"}],
    api_base="http://localhost:4000",
    api_key="your-proxy-api-key"
)

print(response.choices[0].message.content)
```

```python showLineNumbers title="v0 via Proxy - LiteLLM SDK Streaming"
import litellm

# Configure LiteLLM to use your proxy with streaming
response = litellm.completion(
    model="litellm_proxy/v0-medium",
    messages=[{"role": "user", "content": "Create a React card component"}],
    api_base="http://localhost:4000",
    api_key="your-proxy-api-key",
    stream=True
)

for chunk in response:
    if hasattr(chunk.choices[0], 'delta') and chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")
```

**cURL**

```bash showLineNumbers title="v0 via Proxy - cURL"
curl http://localhost:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-proxy-api-key" \
  -d '{
    "model": "v0-medium",
    "messages": [{"role": "user", "content": "Create a React card component"}]
  }'
```

```bash showLineNumbers title="v0 via Proxy - cURL Streaming"
curl http://localhost:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-proxy-api-key" \
  -d '{
    "model": "v0-medium",
    "messages": [{"role": "user", "content": "Create a React card component"}],
    "stream": true
  }'
```

For more detailed information on using the LiteLLM Proxy, see the [LiteLLM Proxy documentation](../providers/litellm_proxy).

## Supported OpenAI Parameters

v0 supports the following OpenAI-compatible parameters:

| Parameter | Type | Description |
|-----------|------|-------------|
| `messages` | array | **Required**. Array of message objects with 'role' and 'content' |
| `model` | string | **Required**. Model ID (v0-1.5-lg, v0-1.5-md, v0-1.0-md) |
| `stream` | boolean | Optional. Enable streaming responses |
| `tools` | array | Optional. List of available tools/functions |
| `tool_choice` | string/object | Optional. Control tool/function calling |

Note: v0 has a limited set of supported parameters compared to the full OpenAI API. Parameters like `temperature`, `max_tokens`, `top_p`, etc. are not supported.

## Advanced Usage

### Custom API Base

If you're using a custom v0 deployment:

```python showLineNumbers title="Custom API Base"
import litellm

response = litellm.completion(
    model="v0/v0-1.5-md",
    messages=[{"role": "user", "content": "Hello"}],
    api_base="https://your-custom-v0-endpoint.com/v1",
    api_key="your-api-key"
)
```

## Pricing

v0 models require a Premium or Team subscription. Visit [v0.dev/chat/settings/billing](https://v0.dev/chat/settings/billing) for current pricing information.

## Additional Resources

- [v0 Official Documentation](https://v0.dev/docs)
- [v0 Model API Reference](https://v0.dev/docs/v0-model-api)

## Related pages

- [Triton Inference Server](https://docs.litellm.ai/docs/providers/triton-inference-server.md)
- [Valkey - Vector Store](https://docs.litellm.ai/docs/providers/valkey_vector_stores.md)