Metadata-Version: 2.4
Name: veo-3-1
Version: 1772075.106.941
Summary: High-quality integration for https://supermaker.ai/video/veo-3-1/
Home-page: https://supermaker.ai/video/veo-3-1/
Author: SuperMaker
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python
Dynamic: summary

# veo-3-1: Automated Interaction Library

The `veo-3-1` library provides a streamlined interface for demonstrating and integrating with the capabilities showcased at https://supermaker.ai/video/veo-3-1/. It automates common tasks and simplifies interaction with the platform.

## Installation

Install `veo-3-1` using pip:
bash
pip install veo-3-1

## Basic Usage Examples

Here are a few examples demonstrating how to use the `veo-3-1` library:

**1. Generating a Video Summary:**

This example demonstrates how to automatically generate a concise summary of a video using the `veo-3-1` library.  Assume the video is identified by a unique ID.
python
from veo_3_1 import VeoClient

client = VeoClient()  # Replace with necessary authentication if required

video_id = "unique_video_123"
summary = client.generate_video_summary(video_id)

if summary:
    print("Video Summary:")
    print(summary)
else:
    print("Failed to generate video summary.")

**2. Extracting Key Moments from a Video:**

This example showcases how to extract key moments or highlights from a video based on predefined criteria (e.g., scenes with high activity).
python
from veo_3_1 import VeoClient

client = VeoClient()  # Replace with necessary authentication if required

video_id = "another_unique_video_456"
key_moments = client.extract_key_moments(video_id, threshold=0.7) # threshold is optional, defaults to 0.5

if key_moments:
    print("Key Moments (timestamps):")
    for timestamp in key_moments:
        print(timestamp)
else:
    print("Failed to extract key moments.")

**3. Applying a Visual Style Transfer:**

This example demonstrates applying a specific visual style (e.g., a painting style) to a video.  This requires a defined style ID.
python
from veo_3_1 import VeoClient

client = VeoClient()  # Replace with necessary authentication if required

video_id = "yet_another_video_789"
style_id = "impressionist_style_1" # This needs to be a valid style ID
new_video_url = client.apply_visual_style(video_id, style_id)

if new_video_url:
    print("Video with style applied available at:")
    print(new_video_url)
else:
    print("Failed to apply visual style.")

**4. Generating a Transcript:**

This example demonstrates automatic transcript generation from a video.
python
from veo_3_1 import VeoClient

client = VeoClient()  # Replace with necessary authentication if required

video_id = "transcript_video_abc"
transcript = client.generate_transcript(video_id)

if transcript:
    print("Video Transcript:")
    print(transcript)
else:
    print("Failed to generate transcript.")

**5. Checking Video Processing Status:**

This example shows how to check the status of a video processing job initiated by one of the other functions.
python
from veo_3_1 import VeoClient

client = VeoClient()  # Replace with necessary authentication if required

video_id = "processing_video_xyz"
status = client.get_processing_status(video_id)

if status:
    print(f"Video Processing Status: {status}")
else:
    print("Failed to retrieve processing status.")

## Feature List

*   **Video Summarization:** Automatically generate concise summaries of video content.
*   **Key Moment Extraction:** Identify and extract key moments or highlights from videos.
*   **Visual Style Transfer:** Apply visual styles to videos, changing their aesthetic appearance.
*   **Automatic Transcription:** Generate text transcripts from video audio.
*   **Processing Status Monitoring:** Track the status of video processing jobs.
*   **Simplified API:** Easy-to-use functions for interacting with the underlying platform.
*   **Error Handling:** Provides informative error messages for debugging.

## License

MIT License

This project is a gateway to the veo-3-1 ecosystem. For advanced features and full capabilities, please visit: https://supermaker.ai/video/veo-3-1/
