Summarizer

Summarizes long texts recursively with OpenAI API. This summarizer can be configured to output in a specified style (see --genre) and language (see --language), and can be hinted with the topic (see --topic). Any additional information can be provided in --context.

To prevent information losses from intermediate summaries, the model is instructed to take notes of the text chunks. This way details and facts are preserved while the notes are more compact than the original text. The final summary then combines all the notes into a coherent text.

Currently the summarizer only accept inputs as json verbose transcripts from Whisper API (you may be interested whisper-youtube-transcriber). In the future I plan to make it summarize plain texts as well.

Usage

python summarizer.py [-h] [-i INPUT] [-o OUTPUT] [-d DIR] [-m MODEL] [-n NUM_CHOICES] [-g GENRE] [-t TOPIC]
                     [-l LANGUAGE] [-c CONTEXT] [-v] [--checkpoint CHECKPOINT] [--load] [--rewrite]

Summarizes long texts recursively with OpenAI API.

options:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Path to the input file
  -o OUTPUT, --output OUTPUT
                        Path to the output file
  -d DIR, --dir DIR     Path to the output directory. Use with -i if -o is not specified.
  -m MODEL, --model MODEL
                        Model to use. Default: gpt-3.5-turbo. Options: gpt-4, gpt-3.5-turbo-16k, gpt-3.5-turbo,
                        gpt-4-0613, gpt-4-0314, gpt-3.5-turbo-16k-0613, gpt-3.5-turbo-0613, gpt-3.5-turbo-0301
  -n NUM_CHOICES        Number of times the final text will be generated. The longest complete text will be chosen.
                        Default: 1
  -g GENRE, --genre GENRE
                        Genre or style of the text. Default: post. Examples: post, (detailed) textbook, essay, novel,
                        scientific paper, script, etc.
  -t TOPIC, --topic TOPIC
                        Topic of the text. Default: [not specified]
  -l LANGUAGE, --language LANGUAGE
                        Language of the text. Default: English
  -c CONTEXT, --context CONTEXT
                        Something the model should keep in mind. Optional
  -v, --verbose         Print the log to stdout. Default: False
  --checkpoint CHECKPOINT
                        Path to the checkpoint file. Default: summarizer.pkl
  --load                Load the checkpoint file. Default: False
  --rewrite             Rewrite the the final text from the checkpoint. Default: False

Output Directory

The summarizer now supports an optional argument -d to specify the output directory for the summary file. If this argument is provided, the summary file will be saved in the specified directory with the same name as the input file and a .md extension. If this argument is not provided, the output argument is required to specify the output file path.

To use this argument, simply add -d followed by the path to the output directory when running the script. For example:

python summarizer.py -i input.json -d output/

This will save the final summary in output/input.md.

Rewriting Final Summary

Since the intermediate summaries are notes and only the last summary is a coherent text, the genre or style is only applied to that last stage. The final summary can be rewritten with the same notes from intermediate summaries. The options -n and --genre can be modified in this mode:

python summarizer.py -o OUTPUT [-n NUM_CHOICES] [-g GENRE] [--checkpoint CHECKPOINT] --rewrite

Continuing from Checkpoint

In case of unexpected crashes, the summarization process can be continued from a checkpoint:

python summarizer.py -o OUTPUT [--checkpoint CHECKPOINT] --load

Logs

Logs are stored in the logs/ folder. They are useful for debugging and looking at intermediate summaries.