semvec/pypi-packages huggingface dataset:
openai-whisper-api-cli 0.1.1
Simple CLI wrapper for OpenAI Speech-to-Text API
Requires Python: >=3.10
Keywords: openai, whisper, speech-to-text, transcription, cli

# openai-whisper-api-cli

Simple Python CLI wrapper for OpenAI Speech-to-Text.

## Features
- Transcribe local audio/video files with OpenAI Speech-to-Text
- API key from `--api-key` or `OPENAI_API_KEY`
- Print result to stdout (default)
- Optionally write result to a file
- Supports multiple response formats

## Install (Recommended)

```bash
python3 -m pip install --user pipx
python3 -m pipx ensurepath
pipx install openai-whisper-api-cli
```

Verify:

```bash
owhisper --version
```

Upgrade:

```bash
pipx upgrade openai-whisper-api-cli
```

## Install From Source

```bash
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
```

## Authentication

Set env var:

```bash
export OPENAI_API_KEY="sk-..."
```

Or pass key directly:

```bash
owhisper transcribe ./audio.mp3 --api-key "sk-..."
```

`--api-key` takes precedence over `OPENAI_API_KEY`.

## Usage

Print transcription to stdout:

```bash
owhisper transcribe ./audio.mp3
```

Write transcription to file:

```bash
owhisper transcribe ./audio.mp3 --output-file ./transcript.txt
```

Use custom model and response format:

```bash
owhisper transcribe ./audio.mp3 \
  --model gpt-4o-transcribe \
  --response-format json \
  --language en
```

### Supported models
- `gpt-4o-transcribe`
- `gpt-4o-mini-transcribe`
- `gpt-4o-transcribe-diarize`
- `whisper-1`

Model list source:
- https://developers.openai.com/api/docs/guides/speech-to-text/

## CI and Publishing

GitHub Actions workflows:
- `.github/workflows/ci.yml`: runs tests on push/PR
- `.github/workflows/publish.yml`: builds and publishes to PyPI on tag push (`v*`)

### PyPI trusted publishing setup
1. Create your project on PyPI: `openai-whisper-api-cli`.
2. In PyPI project settings, add a Trusted Publisher:
   - Owner: your GitHub org/user
   - Repository: `openai-whisper-api-cli`
   - Workflow: `publish.yml`
   - Environment: `pypi`
3. In GitHub repo settings, ensure environment `pypi` exists (optional protection rules).

### Release

```bash
python -m pytest
python -m build
python -m twine check dist/*
git tag v0.1.0
git push origin v0.1.0
```

Pushing the tag triggers automated publish.

## Local manual publish (optional)

```bash
python -m build
python -m twine upload dist/*
```

## License

MIT (see `LICENSE`).
cognite-toolkit 0.7.120
Official Cognite Data Fusion tool for project templates and configuration deployment
Requires Python: >=3.10

# Cognite Data Fusion Toolkit

[![release](https://img.shields.io/github/actions/workflow/status/cognitedata/toolkit/release.yaml?style=for-the-badge)](https://github.com/cognitedata/toolkit/actions/workflows/release.yaml)
[![Github](https://shields.io/badge/github-cognite/toolkit-green?logo=github&style=for-the-badge)](https://github.com/cognitedata/toolkit)
[![PyPI](https://img.shields.io/pypi/v/cognite-toolkit?style=for-the-badge)](https://pypi.org/project/cognite-toolkit/)
[![Downloads](https://img.shields.io/pypi/dm/cognite-toolkit?style=for-the-badge)](https://pypistats.org/packages/cognite-toolkit)
[![GitHub](https://img.shields.io/github/license/cognitedata/toolkit?style=for-the-badge)](https://github.com/cognitedata/toolkit/blob/master/LICENSE)
[![Docker Pulls](https://img.shields.io/docker/pulls/cognite/toolkit?style=for-the-badge)](https://hub.docker.com/r/cognite/toolkit)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json&style=for-the-badge)](https://github.com/astral-sh/ruff)
[![mypy](https://img.shields.io/badge/mypy-checked-000000.svg?style=for-the-badge&color=blue)](http://mypy-lang.org)

The CDF Toolkit is a command-line interface (`cdf`) used for configuring and administrating
Cognite Data Fusion (CDF) projects. It ships with modularised `templates` that helps you
configure Cognite Data Fusion according to best practices.

It supports three different modes of operation:

1. As an **interactive command-line tool** used alongside the Cognite Data Fusion web application to retrieve and
   push configuration of the different Cognite Data Fusion services like data sets, data models, transformations,
   and more. This mode also supports configuration of new Cognite Data Fusion projects to quickly get started.
2. As tool to support the **project life-cycle by scripting and automating** configuration and management of Cognite Data
   Fusion projects where CDF configurations are kept as yaml-files that can be checked into version
   control. This mode also supports DevOps workflows with development, staging, and production projects.
3. As a **tool to deploy official Cognite project templates** to your Cognite Data Fusion project. The tool comes
   bundled with templates useful for getting started with Cognite Data Fusion, as well as for specific use cases
   delivered by Cognite or its partners. You can also create your own templates and share them.

## Usage

Install the Toolkit by running:

```bash
pip install cognite-toolkit
```

Then run `cdf --help` to get started with the interactive command-line tool.

## For more information

More details about the tool can be found at
[docs.cognite.com](https://docs.cognite.com/cdf/deploy/cdf_toolkit/).

You can find an overview of the modules and packages in the
[module and package documentation](https://docs.cognite.com/cdf/deploy/cdf_toolkit/references/resource_library).

See [./CONTRIBUTING.md](./CONTRIBUTING.md) for information about how to contribute to the `cdf-tk` tool or
templates.