v0

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 ↗
Base URL	`https://api.v0.dev/v1`
Supported Operations	`/chat/completions`

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

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 to upgrade.

Usage - LiteLLM Python SDK

Non-streaming

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

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:

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:

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:

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:

Start LiteLLM Proxy
litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000

OpenAI SDK
LiteLLM SDK
cURL

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)

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="")

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)

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="")

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"}]
  }'

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.

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:

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 for current pricing information.

Overview​

Available Models​

Required Variables​

Usage - LiteLLM Python SDK​

Non-streaming​

Streaming​

Vision/Multimodal Support​

Function Calling​

Usage - LiteLLM Proxy​

Supported OpenAI Parameters​

Advanced Usage​

Custom API Base​

Pricing​

Additional Resources​