Turn audio files into formatted markdown for your blog or note taking app.. A simple structured language lets you add headings, bulleted lists, and numbered lists.

Useful for developers and plugin authors building audio integrations into their apps.


Steamship Packages are cloud-hosted AI libraries you can use from any programming environment.

Packages manage their own data & infrastructure in the cloud. Each instance gets its own private scope.


Download a Jupyter Demo

> npx try-steamship audio-markdown

From Python

from steamship import Steamship

# See GitHub README for Config requirements
instance = Steamship.use("audio-markdown", config={})

# See GitHub README for available methods
resp = instance.invoke('method', arg1=val1, arg2=val2)
Pulled from the GitHub repository.
# Steamship Audio Markdown Package 

This project contains a Steamship Package that transcribes audio, generating Markdown output. The generated
Markdown will be formatted based on cues within the transcribed audio itself.

Web demo:

## Usage

import time

from steamship import Steamship
from steamship.base import TaskState

instance = Steamship.use("audio-markdown", "my-workspace-name")

url = ""
transcribe_task = instance.invoke("transcribe_url", url=url)
task_id = transcribe_task["task_id"]
status = transcribe_task["status"]

# Wait for completion
retries = 0
while retries <= 100 and status != TaskState.succeeded:
    response = instance.invoke("get_markdown", task_id=task_id)
    status = response["status"]
    if status == TaskState.failed:
        print(f"[FAILED] {response['status_message']")

    print(f"[Try {retries}] Transcription {status}.")
    if status == TaskState.succeeded:
    retries += 1

# Get Markdown
markdown = response["markdown"]

## Developing

Development instructions are located in [](

## Deploying

Deployment instructions are located in [](

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