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Podcast my Paper

We provide a module to perform document processing and text-to-speech to enable listening to any document in podcast style. The functionality can be accessed through the podcast API or by running the script scripts/

API access

The podcast API is available through the podcast module. An end-to-end workflow looks like this (modified from the test module):

from biochatter.podcast import Podcaster
from biochatter.vectorstore import DocumentReader

# Load document
reader = DocumentReader()
document = reader.load_document("test/dcn.pdf")

# Initialise podcaster
podcaster = Podcaster(document)

# Generate podcast (LLM task)

# Employ text-to-speech to generate audio file (optional)
podcaster.podcast_to_file("test/test.mp3", model="tts-1-hd", voice="alloy")

If you do not want audio output, you can simply access the generated text though the function podcaster.podcast_to_text().

This example uses the paid OpenAI text-to-speech API to generate the audio file. The default of the podcast_to_file function is to use the free Google text-to-speech API. When using OpenAI, due to the input length limit of 4096 characters, the podcast is split into multiple parts indicated by integer suffixes.

Command line access

To generate a podcast from a single document more quickly, you can use the scripts/ script. It accepts two arguments, the path to the document and the path to the desired output file. If the output file ends in .mp3, the OpenAI text-to-speech API will be used to generate an audio file. Otherwise, the script will generate a text file and skip the text-to-speech step. If using the OpenAI text-to-speech API, multiple files will be generated with integer suffixes. If you installed BioChatter with poetry, you can run the script like this (from the root directory of the repository):

poetry run python scripts/ test/dcn.pdf test/test.mp3