summawise
Summarize information from files, links, and vectorized data using OpenAI's powerful models. Explore data further and generate code/information using an interactive prompt for deep dives into content. The beta API features that are built in make it superior to a standard LLM in the context of code generation relative to existing context/codebases.
Installation
For the sake of convenience (and to be added to your $PATH), the program is available via PyPI:
pip install --upgrade summawise
Notes
This tool uses OpenAI API features which are currently in beta.
Resources:
Information
The following inputs are supported:
- YouTube video URLs. (Transcript is extracted and used as text)
- Local files. (Any type of content, file will be uploaded byte for byte)
- Local directories. (Includes files in nested directories)
- Other URLs, depending on the response content. (Text content, PDF files, and HTML are all supported)
Support for a wider variety of input may be added in the future.
Potential improvements:
- Archive support (Both URLs and local files - automatically extract/upload contents of
.zip/.tar.gzfiles) - Extract natural language from certain types of content. (Ex: html/pdf)
1 maintainer
Metadata
1 maintainer
Release files for summawise 0.5.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| summawise-0.5.5.tar.gz | 42.9 kB | Without provenance | Details for summawise-0.5.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| summawise-0.5.5-py3-none-any.whl | Python 3 | none | any | Details for summawise-0.5.5-py3-none-any.whl |
Total release size: 92.0 kB
Release files / summawise-0.5.5.tar.gz
| Download URL | summawise-0.5.5.tar.gz |
|---|---|
| Size | 42.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fd245e3ef3dfeb6ea1ea3f2bbfe111e487bc760db41c01e525fa38f578f4fe2e
|
|
BLAKE2b-256 checksum How to use checksums |
a22953d81741cb5a4f655be1206b886eb17f9d98244c594221b12508c9aef937
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.4
|
Release files / summawise-0.5.5-py3-none-any.whl
| Download URL | summawise-0.5.5-py3-none-any.whl |
|---|---|
| Size | 49.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c101992def00ea280da829195d1bd2cd4edade626d27f9b59337ce7e4d23c459
|
|
BLAKE2b-256 checksum How to use checksums |
af58dfbf41d5f5b234b1d91b345a32a4855164afcdf8bfbbe175ac48f9169b0c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.4
|
Security for summawise 0.5.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
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