54 lines
1.9 KiB
Rust
54 lines
1.9 KiB
Rust
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use anyhow::Result;
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use chrono::{DateTime, Utc};
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use feedsignal_core::Article;
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use uuid::Uuid;
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/// Fetches and parses one RSS/Atom feed. `feed-rs` normalizes both formats
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/// into a common model so callers don't need to branch on feed type.
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pub async fn fetch_feed(feed_url: &str, feed_id: Uuid) -> Result<Vec<Article>> {
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let bytes = reqwest::get(feed_url).await?.bytes().await?;
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let parsed = feed_rs::parser::parse(&bytes[..])?;
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let articles = parsed
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.entries
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.into_iter()
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.filter_map(|entry| {
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let url = entry.links.first()?.href.clone();
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let title = entry.title.map(|t| t.content).unwrap_or_default();
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let summary = entry
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.summary
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.map(|s| s.content)
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.or_else(|| entry.content.and_then(|c| c.body))
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.unwrap_or_default();
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let published_at: Option<DateTime<Utc>> = entry.published.or(entry.updated);
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let estimated_read_seconds = Some(estimate_read_seconds(&summary));
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Some(Article {
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id: Uuid::new_v4(),
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feed_id,
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url,
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title,
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summary,
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published_at,
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topics: Vec::new(),
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embedding_score: None,
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llm_score: None,
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final_score: None,
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estimated_read_seconds,
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})
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})
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.collect();
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Ok(articles)
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}
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/// Rough estimate from word count at ~200 wpm, used as the denominator for
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/// dwell-time-based engagement scoring (see `feedsignal_core::affinity`).
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/// This is a placeholder — the full article body isn't fetched here, so
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/// it's a floor rather than an accurate estimate until content extraction
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/// is added.
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fn estimate_read_seconds(text: &str) -> u32 {
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let words = text.split_whitespace().count() as u32;
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((words.max(1) as f32 / 200.0) * 60.0) as u32
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}
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