Veo 4 API: Python Wrapper for Google DeepMind's AI Video Generator

The most comprehensive Python wrapper for the Veo 4 API (developed by Google DeepMind), delivered via muapi.ai. Generate native 4K AI videos up to 30 seconds with integrated audio, character consistency, and advanced camera controls — Google's most powerful video generation model.

Join subreddit Veo4 for discussion

🌊 Also explore these top AI video models:

• Seedance 2.0 API — ByteDance's cinematic 2K video model with character sheets & omni-reference
• HappyHorse 1.0 API — Alibaba's #1 ranked model (1392 Elo I2V) with native 1080p & integrated audio

Related Projects

• Veo 4 on MuAPI — Model landing page for the wrapper's video and audio workflows.
• Veo 4 text-to-video playground — Try Veo 4 directly in the browser.
• MiniMax-H3-API — Python SDK for MiniMax H3 text-to-video, image-to-video, and first/last-frame video generation.
• Wan-3.0-API — Python SDK and MCP server for Wan 3.0-compatible text-to-video, image-to-video, and multimodal reference workflows.
• veo4-video-generator — Ready-made Next.js SaaS built on Veo 4
• veo3.1-comfyui — Run Veo 3.1 inside ComfyUI
• awesome-ai-video-models — compare AI video models by API, price & speed

🚀 Why Use Veo 4 API?

Veo 4 is Google DeepMind's latest state-of-the-art AI video generation model, featuring a 3x larger Transformer architecture than Veo 3, native 4K output, and advanced character anchoring technology.

• Native 4K Output: Every pixel generated from scratch — not upscaled.
• Up to 30 Seconds: Longer clips than any previous Veo model.
• Integrated Audio: Jointly generates synchronized dialogue, ambient sound, and music in one pass (building on Veo 3's audio breakthrough).
• Character Consistency: Advanced anchoring technology keeps faces, clothing, and features consistent across all frames and camera angles.
• Advanced Camera Controls: Pan, zoom, orbit, tracking shots — precise cinematic control.
• Developer-First: Simple Python SDK via MuAPI infrastructure.

🌟 Key Features of Veo 4 API

• ✅ Veo 4 Text-to-Video (T2V): Transform descriptive prompts into stunning native 4K video clips up to 30 seconds.
• ✅ Veo 4 Image-to-Video (I2V): Animate static images with precise motion and camera control using images_list.
• ✅ Integrated Audio-Video Generation: Jointly generate synchronized audio and video in one pass — include sound cues in your prompt.
• ✅ Character Consistency: character_video() anchors on reference photos to keep identity consistent across scenes.
• ✅ Advanced Camera Controls: Specify camera_control for cinematic movements — pan, zoom, orbit, tracking shots.
• ✅ Video Extension: Extend existing Veo 4 clips up to 30 seconds total.
• ✅ Video Edit: Edit existing videos using natural language prompts.
• ✅ File Upload: Upload local images and videos directly via upload_file().
• ✅ Flexible Aspect Ratios: Optimized for 16:9, 9:16 (TikTok/Reels), and 1:1.
• ✅ Quality Tiers: 1080p and 4k (native) output.

🛠 Installation

Via Pip (Recommended)

pip install veo-4-api

From Source

git clone https://github.com/Anil-matcha/Veo-4-API.git
cd Veo-4-API
pip install -r requirements.txt

Configuration

Create a .env file in the root directory and add your MuAPI API key:

MUAPI_API_KEY=your_muapi_api_key_here

🤖 Veo 4 MCP Server

Use Veo 4 as an MCP (Model Context Protocol) server, allowing AI assistants like Claude Desktop or Cursor to directly invoke Veo 4 generation tools.

Running the MCP Server

1. Ensure MUAPI_API_KEY is set in your environment.
2. Run the server:

   python3 mcp_server.py
   

3. To test with the MCP Inspector:

   npx -y @modelcontextprotocol/inspector python3 mcp_server.py
   

💻 Quick Start with Veo 4 API (Python)

from veo4_api import Veo4API

# Initialize the Veo 4 client
api = Veo4API()

# Generate Video from Text (T2V)
print("Generating AI Video using Veo 4...")
submission = api.text_to_video(
    prompt="A cinematic tracking shot through a lush rainforest, sunlight filtering through the canopy, birds calling",
    aspect_ratio="16:9",
    duration=8,
    quality="4k",
    camera_control="tracking shot"
)

# Wait for completion
result = api.wait_for_completion(submission['request_id'])
print(f"Success! View your Veo 4 video here: {result['outputs'][0]}")

🎵 Audio-Video Generation

Veo 4 jointly generates synchronized video and audio in a single pass — include sound cues in your prompt for best results.

from veo4_api import Veo4API

api = Veo4API()

# Text-to-video with audio
submission = api.text_to_video_with_audio(
    prompt="A street musician playing violin in Paris, rain on cobblestones, distant traffic, melancholic melody",
    aspect_ratio="16:9",
    duration=15,
    quality="4k"
)
result = api.wait_for_completion(submission['request_id'])
print(f"Video with audio: {result['outputs'][0]}")

# Image-to-video with audio
submission = api.image_to_video_with_audio(
    prompt="@image1 comes alive — waves crashing, seagulls calling, ocean breeze rustling palm trees",
    images_list=["https://example.com/beach.jpg"],
    duration=10,
)
result = api.wait_for_completion(submission['request_id'])
print(f"Animated with audio: {result['outputs'][0]}")

Tip: Include explicit sound cues (e.g. "thunder rumbling", "crowd cheering", "piano melody") for richer, more accurate audio generation.

🎭 Character Consistency

Veo 4's character anchoring keeps faces and identity consistent across all frames.

from veo4_api import Veo4API

api = Veo4API()

# Anchor on a reference photo
submission = api.character_video(
    prompt="@image1 walks confidently through a neon-lit Tokyo street at night",
    character_images=["https://example.com/person.jpg"],
    aspect_ratio="16:9",
    duration=8,
    quality="4k",
    with_audio=True,
)
result = api.wait_for_completion(submission['request_id'])
print(f"Character video: {result['outputs'][0]}")

🎬 Camera Controls

Specify cinematic camera movements with the camera_control parameter.

# Zoom in dramatically
submission = api.text_to_video(
    prompt="A lone lighthouse on a rocky cliff at dusk, storm approaching",
    aspect_ratio="16:9",
    duration=10,
    quality="4k",
    camera_control="slow zoom in"
)

# Orbit around a subject
submission = api.text_to_video(
    prompt="A marble statue in a sunlit museum courtyard",
    aspect_ratio="16:9",
    duration=8,
    camera_control="orbit"
)

📡 API Endpoints & Reference

1. Veo 4 Text-to-Video (T2V)

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-t2v

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-t2v" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "A majestic eagle soaring over snow-capped mountains at sunrise",
      "aspect_ratio": "16:9",
      "duration": 8,
      "quality": "4k",
      "camera_control": "pan right"
  }'

2. Veo 4 Image-to-Video (I2V)

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-i2v

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-i2v" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "@image1 — the clouds drift slowly, light shifts from golden to dusk",
      "images_list": ["https://example.com/landscape.jpg"],
      "aspect_ratio": "16:9",
      "duration": 8,
      "quality": "4k"
  }'

3. Veo 4 T2V with Audio

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-t2v-audio

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-t2v-audio" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "A busy Tokyo street at night, neon signs, rain, jazz music drifting from a bar",
      "aspect_ratio": "16:9",
      "duration": 15,
      "quality": "4k"
  }'

4. Veo 4 I2V with Audio

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-i2v-audio

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-i2v-audio" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "@image1 — waves begin to crash, seagulls cry in the distance, wind howling",
      "images_list": ["https://example.com/ocean.jpg"],
      "aspect_ratio": "16:9",
      "duration": 10,
      "quality": "4k"
  }'

5. Veo 4 Character Video

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-character

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-character" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "@image1 walks confidently through a neon-lit Tokyo street",
      "images_list": ["https://example.com/person.jpg"],
      "aspect_ratio": "16:9",
      "duration": 8,
      "quality": "4k"
  }'

6. Video Extension

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-extend

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-extend" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "request_id": "your-completed-request-id",
      "prompt": "The eagle lands on a mountain peak, surveying the valley below",
      "duration": 10,
      "quality": "4k"
  }'

7. Video Edit

Endpoint: POST https://api.muapi.ai/api/v1/veo-4-video-edit

curl --location --request POST "https://api.muapi.ai/api/v1/veo-4-video-edit" \
  --header "Content-Type: application/json" \
  --header "x-api-key: YOUR_API_KEY" \
  --data-raw '{
      "prompt": "Change the weather to a dramatic thunderstorm",
      "video_urls": ["https://example.com/video.mp4"],
      "aspect_ratio": "16:9",
      "quality": "4k"
  }'

📖 API Method Reference

🔗 Official Resources

• API Provider: MuAPI.ai

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Keywords: Veo 4 API, Google Veo 4, Google DeepMind Video, AI Video Generator, Text-to-Video AI, Image-to-Video API, Veo 4 Python SDK, Google Video AI, Audio Video Generation, 4K AI Video, Character Consistency AI, Camera Control Video, MuAPI, Video Generation API, Native 4K Video, AI Video Creation, Veo 4 API Documentation, Veo 4 I2V, Veo 4 T2V, Python Video API.