CLI & library that extracts YouTube captions and returns an OpenAI-generated summary
Project description
youtube-ai-resume
Generate concise AI summaries of YouTube videos from the command line.
It works in two steps:
- Downloads the video caption (subtitles) with
pytubefix. - Sends the caption to the OpenAI API and returns a summary in the language you choose.
Features
- Zero-setup CLI →
youtube-ai-resume <video_url> - Summaries in any language (default
en_US) - Works with models like
gpt-4.1-mini(configurable) - Rich-formatted output with colours
- Usable as a library (
import youtube_ai_resume)
Installation
# Python ≥ 3.9
pip install youtube-ai-resume
Or, from source for development:
git clone https://github.com/fberbert/youtube-ai-resume.git
cd youtube-ai-resume
pip install -e ".[dev]" # editable + dev tools
Quick start
Command Line Usage
export OPENAI_API_KEY="sk-..."
youtube-ai-resume https://www.youtube.com/watch?v=Ht2QW5PV-eY
Sample output:
Summary:
The speaker, Dashish, an engineer on OpenAI’s product team, discusses advancements in AI agents that integrate improved models with powerful tools to
enhance user experience. Key points include:
- **Symbiotic Improvement**: Better tools enable more capable AI agents, which in turn can utilize more powerful tools, creating a continuous cycle of
enhancement.
- **Agent Capabilities**: The AI agent can access various personal tools and data sources, such as Gmail and Google Calendar, through connectors to perform
complex tasks.
- **Use Case - Booking a Tennis Tournament Itinerary**:
- The agent is tasked with planning a detailed itinerary for a tennis tournament in Palm Springs, focusing on semi-final dates.
- It checks the tournament schedule, the user’s calendar availability, flight options, hotel bookings, match attendance, and dining plans.
- The agent uses a visual browser and personal data access to gather and coordinate all necessary information.
- **User Experience**: The agent automates the research and planning process, handling logistical details like travel time and meeting schedules, then
notifies the user with a comprehensive plan to review.
- **Benefit**: This automation frees users from mundane tasks, allowing them to focus on the core activities they care about.
Overall, the presentation highlights how integrating AI models with personal data and external tools can create intelligent agents that manage complex,
personalized planning tasks efficiently.
Library usage
from youtube_ai_resume import caption, summarizer
txt = caption.fetch_caption("Ht2QW5PV-eY")
summary = summarizer.summarize(
transcript=txt,
api_key="sk-…",
model="gpt-4.1-mini",
out_lang="en_US"
)
print(summary)
Configuration
Voice narration (Text-to-Speech) [Optional]
You can optionally have the summary narrated aloud using Google Cloud Text-to-Speech (TTS).
Optional Requirements (only if you want voice narration)
- A service account key (JSON) with permission to use TTS
- The dependencies
google-cloud-texttospeechandplaysound(already included in requirements.txt)
Optional Setup
- Create a project in Google Cloud and enable the Text-to-Speech API.
- Generate and download a service account credentials file (JSON).
- Set the
GOOGLE_APPLICATION_CREDENTIALSenvironment variable to the path of your credentials file:
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/service-account.json"
The default path is ~/.config/youtube-ai-resume/.google-credentials.json. You can customize this path in your config file.
{
"google_credentials": "~/.config/youtube-ai-resume/.google-credentials.json"
}
Usage
- To hear the summary narration, add the
--voiceoption to the command:
youtube-ai-resume --voice 'https://www.youtube.com/watch?v=Ht2QW5PV-eY'
- To enable narration by default, add to your config.json:
{
"voice_enabled": true
}
You can customize voice, language, and speed in config.json (see code examples).
You can set the OpenAI API key as an environment variable or in a config file.
Environment variable:
OPENAI_API_KEY="sk-..."
Config file at ~/.config/youtube-ai-resume/config.json (auto-created on first run) lets you change the default model.
{
"model": "gpt-4.1-mini",
"out_lang": "en"
}
Development
Contributions are welcome!
Fork ➜ branch ➜ PR.
ruff check . and pytest must pass.
Describe your change clearly.
License
Released under the MIT License – see LICENSE.
Author
Fabio Berbert fberbert@gmail.com
I am open for job opportunities and collaborations.
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