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Tarash

AI media toolkit
Generate video, image, and audio with a unified interface — plus tools to process and enhance them

Python 3.12+ License: MIT

Documentation  ·  Quick Start  ·  Providers  ·  Blog


What is Tarash?

Every AI media provider ships its own SDK with its own parameter names, response shapes, and error formats. Tarash is a Python toolkit that unifies all of this — generation across providers, plus processing tools to enhance the output.

Tarash Gateway is the first package: a unified SDK for video, image, and audio generation across 10+ providers and 100+ models. Write one integration, swap providers by changing config.


Quick Example

from tarash_gateway import VideoGenerationConfig, VideoGenerationRequest, generate_video

config = VideoGenerationConfig(
    model="fal-ai/veo3.1/fast",
    provider="fal",
    api_key="YOUR_FAL_KEY",
)

request = VideoGenerationRequest(
    prompt="Sunset over mountains, cinematic",
    aspect_ratio="16:9",
    duration_seconds=5,
)

response = generate_video(config, request)
print(response.video)  # URL to generated video

Switch to any other provider — same request, same response:

config = VideoGenerationConfig(
    model="gen4_turbo", provider="runway", api_key="YOUR_RUNWAY_KEY",
)
response = generate_video(config, request)

See tarash-gateway for image, audio, async, and fallback examples.


Packages

Package Description
tarash-gateway Unified SDK for AI video, image, and audio generation Stable
tarash-tools Media processing utilities (silence removal, scene detection, and more) Coming soon

Supported Providers

Provider Video Image Audio
Fal.ai
OpenAI
Google
Runway
Replicate
XAI
Stability AI
ElevenLabs
Cartesia
Sarvam
Hume

Full model list at tarash.vertexcover.io/providers


Highlights

  • One interface for video, image, and audio — stop rewriting integrations for every provider
  • Swap providers by changing config — your request code, response handling, and error logic stay identical
  • Automatic fallback chains — if a provider goes down, the next one picks up seamlessly
  • Sync and async — every function has both generate_* and generate_*_async variants
  • Production-ready — type-safe Pydantic v2 models, structured logging, and rich error context

Installation

pip install tarash-gateway[fal]

Install only the provider extras you need:

pip install tarash-gateway[openai]       # OpenAI / Azure
pip install tarash-gateway[runway]       # Runway
pip install tarash-gateway[elevenlabs]   # ElevenLabs TTS
pip install tarash-gateway[fal,runway]   # Multiple providers
pip install tarash-gateway[all]          # Everything

Requires Python 3.12+ — see the installation guide for details.


Contributing

Tarash is open source and contributions are welcome.

Development setup

Requirements: Python 3.12+, uv

git clone https://github.com/vertexcover-io/tarash.git
cd tarash
uv sync
# Unit tests (no API keys needed)
uv run pytest packages/tarash-gateway/tests/unit/

# End-to-end tests (requires API keys)
uv run pytest packages/tarash-gateway/tests/e2e/ --e2e

License

MIT — see LICENSE for details.

About

One-stop AI media toolkit — generate, caption & analyze video, image & audio across 15+ providers

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