websum
Summarise a web page or a YouTube video, with whichever model you want behind it.
PyPI · changelog · contributing
Summarising a page is a few lines of LangChain right up until you want the same call to also take a YouTube link, chunk a transcript that will not fit in a context window, run against a local Ollama on a laptop with no network, and then move to OpenAI without any of the calling code changing. That is the part this packages.
One object, Summarizer, takes a URL and works out whether it is a page or a video.
The model behind it is a constructor argument, so swapping Ollama for OpenAI, or for
something you wrote yourself, is a single line.
from websum import Summarizer, OllamaBackend s = Summarizer(backend=OllamaBackend(model="llama3:instruct")) print(s.summarize("https://www.youtube.com/watch?v=4pOpQwiUVXc"))
- Pages and YouTube through the same call.
summarize(url)detects which it has.summarize_webandsummarize_youtubeare there when you already know. - The backend is a Protocol, not a base class to inherit. Anything with a
.build()returning a LangChain chat model satisfies it. - Local by default. Ollama is a first-class backend, so nothing has to leave the machine, and no key is required to try it.
- Long inputs are chunked, so a two-hour transcript does not have to fit anywhere in one piece.
- A CLI, a library and a Gradio UI over the same code, and a
py.typedmarker so the API type-checks downstream.
Install
pip install 'websum[ollama]' # library + CLI, local models pip install 'websum[openai]' # OpenAI backend pip install 'websum[ui,ollama]' # with the Gradio web UI pip install 'websum[all]' # everything
Using uv:
Python 3.10 to 3.13. The base install carries no model client at all, which is why
the backend is an extra: installing websum alone should not drag in an SDK you are
not going to call.
Use
As a library
from websum import Summarizer, OllamaBackend s = Summarizer(backend=OllamaBackend(model="llama3:instruct")) print(s.summarize("https://cobanov.dev/haftalik-bulten/hafta-13")) print(s.summarize("https://www.youtube.com/watch?v=4pOpQwiUVXc")) print(s.translate("Hello world", target_language="Turkish"))
Swap the backend without touching anything else:
from websum import Summarizer, OpenAIBackend s = Summarizer(backend=OpenAIBackend(model="gpt-4o-mini"))
From the shell
websum summarize https://example.com
websum summarize https://example.com --backend openai --model gpt-4o-mini
websum translate "Hello world" --target-language Turkish
websum ui --port 7860websum --help has the full reference.
In a browser
The API
| Object | Purpose |
|---|---|
Summarizer |
The high-level API. summarize(url), summarize_web(url), summarize_youtube(url), translate(text) |
SummarizerConfig |
Chunking and language settings |
OllamaBackend, OpenAIBackend |
The built-in backends. Frozen dataclasses with .build() |
LLMBackend (Protocol) |
Implement this to plug in anything else |
BackendRegistry |
Maps string names to backend classes, which is how the CLI resolves --backend |
Every public name is re-exported from the top-level websum package and listed in
__all__.
Writing a backend
LLMBackend is a Protocol, so there is nothing to subclass and nothing to
register. A class with a build() method already satisfies it:
from dataclasses import dataclass from websum import LLMBackend, Summarizer @dataclass class MyBackend: def build(self): from langchain_anthropic import ChatAnthropic return ChatAnthropic(model="claude-sonnet-5") assert isinstance(MyBackend(), LLMBackend) # runtime Protocol check s = Summarizer(backend=MyBackend())
The import lives inside build() on purpose: a backend that is never constructed
should not cost an import of an SDK that may not be installed.
Docker
docker build -t websum . docker run -p 7860:7860 websum # when ollama is running on the host docker run --network host -p 7860:7860 websum
The image starts websum ui by default.
Development
git clone https://github.com/cobanov/websum cd websum uv sync --all-extras uv run pre-commit install uv run pytest uv run ruff check . uv run mypy src/websum
CI runs the 19 tests on 3.10, 3.11, 3.12 and 3.13, with ruff, ruff format --check
and mypy on top. pytest-randomly shuffles the order every run, so a test that
only passes because another one ran first fails here rather than later.
CONTRIBUTING.md has the full guide.
Upgrading from 0.1.x
The 0.1.x scripts under app/ are gone. Everything moved into the websum package
behind a typed, importable API.
| Before | After |
|---|---|
python app/summarizer.py -u URL |
websum summarize URL |
python app/webui.py |
websum ui |
from summarizer import setup_summarization_chain |
from websum import Summarizer |
Hardcoded ChatOllama |
OllamaBackend, OpenAIBackend, or your own LLMBackend |
pip install -r requirements.txt |
pip install 'websum[ollama]' |
Licence
MIT. See LICENSE.