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What is Sieve?

Sieve is a platform built to help discover, design, and run AI features at scale. AI development is moving away from being predominantly about training & finetuning, and more towards how people combine models together to make specific use cases work. Our platform is the best development experience built around this growing trend.

Some features include:

  • Pre-built, production-ready apps and models you can use in a single click or API call
  • Build complex apps that use many models in a few lines of code
  • Instant no-code interfaces for every app on Sieve, with zero extra configuration
  • Reliable, horizontally scaling infrastructure based on traffic
  • Powerful distributed primitives like queues and async jobs to parallelize data processing

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Getting Started

Every account comes with $20 of credit to get you started:

pip install sievedata
  • Login with your API key

If running on a terminal:

sieve login

If terminal interaction isn’t possible, set the SIEVE_API_KEY as an environment variable:

export SIEVE_API_KEY=YOUR_SIEVE_API_KEY

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Building a simple AI translation app

Let’s build a simple translation function on Sieve. We’ll take in an input file (video or audio) + the target language and return the translated transcript.

For simplicity, our app will only support English as the source language.
1

To start off, let's make a new directory and file

mkdir simple_translation && cd simple_translation

And copy the following code into simple_translation/main.py:

import sieve

@sieve.function(name="simple_translation")
def simple_translation(file: sieve.File, target_language: str = "spa") -> str:
    """
    :param file: File to translate
    :param target_language: Language code to translate to. Defaults to "spa" for Spanish.
    """

    transcribe = sieve.function.get("sieve/speech_transcriber")
    translate = sieve.function.get("sieve/seamless_text2text")

    transcript = transcribe.run(file)
    translated_segments = []
    for segment in transcript:
        translate_job = translate.push(
            segment["text"],
            source_language="eng",
            target_language=target_language
        )
        translated_segments.append(translate_job)

    translated_transcript = ""
    for translated_seg in translated_segments:
        translated_transcript += translated_seg.result()

    return translated_transcript
2

Deploy to Sieve

Make sure you are in the correct directory! Sieve zips up your current directory to run in the cloud.
sieve deploy

Your build should only take a few seconds, after which you’ll see a link to your newly deployed function on the Sieve dashboard.

3

Run a job

Navigate to your function on the Sieve dashboard and upload a sample file to test out your app.

You can also call your function via API call or the Python client.

Make sure to replace <your-org-name> with your org name and <your-api-key> with your API key.
curl -X POST \
  --url https://mango.sievedata.com/v2/push \
  -H 'X-API-Key: <your-api-key>' \
  -H 'Content-Type: application/json' \
  --data '{
    "function": "<org-name>/simple_translation"
    "inputs": {
      "file": {"url": "https://storage.googleapis.com/mango-public-models/output1.mp4"},
      "target_language": "spa"
    }
  }'

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What just happened?

That was easy! We just built a simple AI translation app in a few lines of code. Let’s walk through it.

At its core, we used 2 Sieve functions to build this app:

Sieve makes it easy to use any public Sieve functions in the cloud, synchronously or asynchronously.

# Running transcription syncronously
transcribe = sieve.function.get("sieve/speech_transcriber")
transcript = transcribe.run(file)

We wrote all of our logic for translating a file in a single function and defined a custom Sieve function with the @sieve.function decorator.

Deploying our function with sieve deploy lets us run this function via API and lets us visualize our inputs & outputs via the Sieve dashboard!

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What’s next?

All you need to get started with Sieve is an account. From there, you can decide what you’d like to do next.

Run AI apps with API

Run a production ready app on Sieve

Complex Applications

Build complex apps like video dubbing

Custom Functions

Deploy your own functions

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Support

If you need any assistance or have any questions, feel free to join our Discord community. Looking forward to see what you build!

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