This release is a pre-release and may not be stable for production use.
ovos-skill-wikipedia
Wikipedia skill for OpenVoiceOS. Adds a voice interface on top of ovos-wikipedia-plugin, which handles all Wikipedia search and retrieval.
Supports two answer modes:
- Explicit intent — handles utterances that target Wikipedia directly (e.g. "search Wikipedia for X", "what does Wikipedia say about X"). These always go to this skill.
- Common Query — handles general knowledge questions (e.g. "what is X", "tell me about X") via the OVOS Common Query pipeline. The pipeline asks all registered knowledge skills and picks the best answer — Wikipedia competes alongside Wolfram Alpha, WordNet, and others.
In other words: if you mention Wikipedia by name, this skill answers directly. If you just ask a general question, it enters the competition and wins only if it has the most confident answer.
Installation
pip install ovos-skill-wikipedia
Explicit intent utterances
These always route to this skill because they name Wikipedia explicitly:
- "Search Wikipedia for Ada Lovelace"
- "What does Wikipedia say about beans?"
- "Look up the Pembroke Welsh Corgi on Wikipedia"
- "Wiki chocolate"
- "Check wiki for Elon Musk"
Common Query utterances
These go through the pipeline — Wikipedia answers if it wins:
- "What is a black hole?"
- "Tell me about the Roman Empire"
- "Who was Marie Curie?"
Common Query pipeline
When the Common Query pipeline plugin is active, this skill competes against other knowledge skills (e.g. Wolfram Alpha, WordNet) to answer general questions. The pipeline selects the response with the highest confidence score.
Sub-plugins
All sub-plugins are optional. Configure them via ~/.config/mycroft/skills/ovos-skill-wikipedia.openvoiceos/settings.json:
{
"extractive_qa": "ovos-bm25-solver",
"reranker": "ovos-bm25-reranker",
"keyword_extractor": "ovos-rake-keywords"
}
Reranker (reranker)
Wikipedia searches often return multiple candidate pages for ambiguous topics — a search for "Mercury" might return the planet, the element, and the god. Without a reranker, results are ordered only by fuzzy title/summary match.
A reranker re-scores all candidate pages against the original query using a cross-encoder model, promoting the most contextually relevant page to the top. This is the single biggest quality improvement for voice use because a wrong page pick means a completely irrelevant spoken answer.
{ "reranker": "ovos-bm25-reranker" }
For better accuracy at the cost of more CPU, use a neural cross-encoder like
ovos-flashrank-reranker-plugin.
Extractive QA (extractive_qa)
By default the skill speaks the full introductory summary of the best Wikipedia article, which can be several sentences long. An extractive QA plugin reads that summary and extracts the single passage most likely to directly answer the user's question.
Without extractive QA — "Tell me about Ada Lovelace":
"Ada Lovelace was an English mathematician and writer, chiefly known for her work on Charles Babbage's proposed mechanical general-purpose computer, the Analytical Engine. She was the first to recognise that the machine had applications beyond pure calculation..."
With extractive QA — same query:
"Ada Lovelace was the first to recognise that the machine had applications beyond pure calculation."
Much more natural for a voice interface.
{ "extractive_qa": "ovos-bm25-solver" }
For better precision, use a reading-comprehension model like
ovos-roberta-qa-plugin.
Keyword Extractor (keyword_extractor)
When the initial Wikipedia search returns no results — common with conversational phrasing like "tell me more about that thing on the moon" — the keyword extractor pulls the most salient terms from the query and retries the search with a cleaner keyword.
Without it, over-specific or colloquial queries silently return nothing. With it, the skill gracefully recovers and finds the right page in most cases.
{ "keyword_extractor": "ovos-rake-keywords" }
License
Apache 2.0 — see LICENSE.
1 maintainer
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