829b811a91
Bug 1923364 - cleanup extensions, r=nanj Bug 1923364 - Adding tabs to lint, r=nanj Bug 1923364 - Ignore tabs linting, r=nanj Bug 1923364 - Restructure and combine rust components, r=nanj Bug 1923364 - Replace rst with MyST markdown, r=nanj Bug 1923364 - PR review fixes, r=nanj Differential Revision: https://phabricator.services.mozilla.com/D224949
70 lines
2.1 KiB
Markdown
70 lines
2.1 KiB
Markdown
---
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myst:
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enable_extensions: ["colon_fence"]
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---
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# Relevancy
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The `relevancy` component tracks the user's interests locally, without sharing any data over the network. The component currently supports building an interest vector based on the URLs they visit.
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## Setting up the store
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To use the `RelevancyStore` in either Kotlin or Swift, you need to import the relevant classes and data types from the `MozillaAppServices` library.
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:::{tab-set-code}
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:sync-group: language
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```kotlin
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import mozilla.appservices.relevancy.RelevancyStore
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import mozilla.appservices.relevancy.InterestVector
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val store = RelevancyStore(dbPath)
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```
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```swift
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import MozillaAppServices
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let store = RelevancyStore(dbPath: "path/to/database")
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```
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:::
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To work with the RelevancyStore, you need to create an instance using a database path where the user’s interest data will be stored:
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:::{tab-set-code}
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:sync-group: language
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```kotlin
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val store = RelevancyStore(dbPath)
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```
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```swift
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let store = RelevancyStore(dbPath: "path/to/database")
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```
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:::
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* `dbPath`: This is the path to the SQLite database where the relevancy data is stored. The initialization is non-blocking, and the database is opened lazily.
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## Ingesting relevancy data
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To build the user's interest vector, call the `ingest` function with a list of URLs ranked by frequency. This method downloads the interest data, classifies the user's top URLs, and builds the interest vector. This process may take time and should only be called from a worker thread.
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### Example usage of `ingest`:
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:::{tab-set-code}
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:sync-group: language
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```kotlin
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val topUrlsByFrequency = listOf("https://example.com", "https://another-example.com")
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val interestVector = store.ingest(topUrlsByFrequency)
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```
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```swift
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let topUrlsByFrequency = ["https://example.com", "https://another-example.com"]
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let interestVector = store.ingest(topUrlsByFrequency)
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```
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:::
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* `topUrlsByFrequency`: A list of URLs ranked by how often and recently the user has visited them. This data is used to build the user's interest vector.
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* The `ingest` function returns an `InterestVector`, which contains the user's interest levels for different tracked categories.
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