git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
837 lines
27 KiB
Rust
837 lines
27 KiB
Rust
//! CrossRef API Integration
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//!
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//! This module provides an async client for fetching scholarly publications from CrossRef.org,
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//! converting responses to SemanticVector format for RuVector discovery.
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//!
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//! # CrossRef API Details
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//! - Base URL: https://api.crossref.org
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//! - Free access, no authentication required
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//! - Returns JSON responses
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//! - Rate limit: ~50 requests/second with polite pool
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//! - Polite pool: Include email in User-Agent or Mailto header for better rate limits
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//!
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//! # Example
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//! ```rust,ignore
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//! use ruvector_data_framework::crossref_client::CrossRefClient;
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//!
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//! let client = CrossRefClient::new(Some("your-email@example.com".to_string()));
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//!
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//! // Search publications by keywords
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//! let vectors = client.search_works("machine learning", 20).await?;
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//!
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//! // Get work by DOI
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//! let work = client.get_work("10.1038/nature12373").await?;
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//!
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//! // Search by funder
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//! let funded = client.search_by_funder("10.13039/100000001", 10).await?;
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//!
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//! // Find recent publications
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//! let recent = client.search_recent("quantum computing", "2024-01-01").await?;
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//! ```
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use std::collections::HashMap;
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use std::time::Duration;
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use chrono::{DateTime, NaiveDate, Utc};
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use reqwest::{Client, StatusCode};
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use serde::Deserialize;
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use tokio::time::sleep;
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use crate::api_clients::SimpleEmbedder;
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use crate::ruvector_native::{Domain, SemanticVector};
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use crate::{FrameworkError, Result};
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/// Rate limiting configuration for CrossRef API
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const CROSSREF_RATE_LIMIT_MS: u64 = 1000; // 1 second between requests for safety (API allows ~50/sec)
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const MAX_RETRIES: u32 = 3;
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const RETRY_DELAY_MS: u64 = 2000;
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const DEFAULT_EMBEDDING_DIM: usize = 384;
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// ============================================================================
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// CrossRef API Structures
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// ============================================================================
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/// CrossRef API response for works search
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#[derive(Debug, Deserialize)]
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struct CrossRefResponse {
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#[serde(default)]
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message: CrossRefMessage,
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}
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#[derive(Debug, Default, Deserialize)]
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struct CrossRefMessage {
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#[serde(default)]
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items: Vec<CrossRefWork>,
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#[serde(rename = "total-results", default)]
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total_results: Option<u64>,
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}
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/// CrossRef work (publication)
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#[derive(Debug, Deserialize)]
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struct CrossRefWork {
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#[serde(rename = "DOI")]
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doi: String,
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#[serde(default)]
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title: Vec<String>,
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#[serde(rename = "abstract", default)]
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abstract_text: Option<String>,
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#[serde(default)]
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author: Vec<CrossRefAuthor>,
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#[serde(rename = "published-print", default)]
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published_print: Option<CrossRefDate>,
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#[serde(rename = "published-online", default)]
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published_online: Option<CrossRefDate>,
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#[serde(rename = "container-title", default)]
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container_title: Vec<String>,
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#[serde(rename = "is-referenced-by-count", default)]
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citation_count: Option<u64>,
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#[serde(rename = "references-count", default)]
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references_count: Option<u64>,
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#[serde(default)]
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subject: Vec<String>,
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#[serde(default)]
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funder: Vec<CrossRefFunder>,
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#[serde(rename = "type", default)]
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work_type: Option<String>,
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#[serde(default)]
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publisher: Option<String>,
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}
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#[derive(Debug, Deserialize)]
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struct CrossRefAuthor {
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#[serde(default)]
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given: Option<String>,
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#[serde(default)]
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family: Option<String>,
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#[serde(default)]
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name: Option<String>,
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#[serde(rename = "ORCID", default)]
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orcid: Option<String>,
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}
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#[derive(Debug, Deserialize)]
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struct CrossRefDate {
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#[serde(rename = "date-parts", default)]
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date_parts: Vec<Vec<i32>>,
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}
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#[derive(Debug, Deserialize)]
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struct CrossRefFunder {
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#[serde(default)]
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name: Option<String>,
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#[serde(rename = "DOI", default)]
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doi: Option<String>,
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}
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// ============================================================================
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// CrossRef Client
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// ============================================================================
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/// Client for CrossRef.org scholarly publication API
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///
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/// Provides methods to search for publications, filter by various criteria,
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/// and convert results to SemanticVector format for RuVector analysis.
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///
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/// # Rate Limiting
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/// The client automatically enforces conservative rate limits (1 request/second).
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/// Includes polite pool support via email configuration for better rate limits.
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/// Includes retry logic for transient failures.
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pub struct CrossRefClient {
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client: Client,
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embedder: SimpleEmbedder,
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base_url: String,
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polite_email: Option<String>,
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}
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impl CrossRefClient {
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/// Create a new CrossRef API client
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///
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/// # Arguments
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/// * `polite_email` - Email for polite pool access (optional but recommended for better rate limits)
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///
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/// # Example
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/// ```rust,ignore
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/// let client = CrossRefClient::new(Some("researcher@university.edu".to_string()));
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/// ```
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pub fn new(polite_email: Option<String>) -> Self {
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Self::with_embedding_dim(polite_email, DEFAULT_EMBEDDING_DIM)
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}
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/// Create a new CrossRef API client with custom embedding dimension
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///
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/// # Arguments
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/// * `polite_email` - Email for polite pool access
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/// * `embedding_dim` - Dimension for text embeddings (default: 384)
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pub fn with_embedding_dim(polite_email: Option<String>, embedding_dim: usize) -> Self {
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let user_agent = if let Some(ref email) = polite_email {
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format!("RuVector-Discovery/1.0 (mailto:{})", email)
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} else {
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"RuVector-Discovery/1.0".to_string()
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};
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Self {
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client: Client::builder()
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.user_agent(&user_agent)
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.timeout(Duration::from_secs(30))
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.build()
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.expect("Failed to create HTTP client"),
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embedder: SimpleEmbedder::new(embedding_dim),
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base_url: "https://api.crossref.org".to_string(),
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polite_email,
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}
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}
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/// Search publications by keywords
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///
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/// # Arguments
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/// * `query` - Search query (title, abstract, author, etc.)
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/// * `limit` - Maximum number of results to return
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///
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/// # Example
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/// ```rust,ignore
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/// let vectors = client.search_works("climate change machine learning", 50).await?;
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/// ```
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pub async fn search_works(&self, query: &str, limit: usize) -> Result<Vec<SemanticVector>> {
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let encoded_query = urlencoding::encode(query);
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let mut url = format!(
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"{}/works?query={}&rows={}",
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self.base_url, encoded_query, limit
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);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Get a single work by DOI
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///
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/// # Arguments
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/// * `doi` - Digital Object Identifier (e.g., "10.1038/nature12373")
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///
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/// # Example
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/// ```rust,ignore
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/// let work = client.get_work("10.1038/nature12373").await?;
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/// ```
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pub async fn get_work(&self, doi: &str) -> Result<Option<SemanticVector>> {
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let normalized_doi = Self::normalize_doi(doi);
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let mut url = format!("{}/works/{}", self.base_url, normalized_doi);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("?mailto={}", email));
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}
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sleep(Duration::from_millis(CROSSREF_RATE_LIMIT_MS)).await;
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let response = self.fetch_with_retry(&url).await?;
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let json_response: CrossRefResponse = response.json().await?;
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if let Some(work) = json_response.message.items.into_iter().next() {
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Ok(Some(self.work_to_vector(work)))
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} else {
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Ok(None)
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}
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}
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/// Search publications funded by a specific organization
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///
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/// # Arguments
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/// * `funder_id` - Funder DOI (e.g., "10.13039/100000001" for NSF)
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/// * `limit` - Maximum number of results
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///
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/// # Example
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/// ```rust,ignore
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/// // Search NSF-funded research
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/// let nsf_works = client.search_by_funder("10.13039/100000001", 20).await?;
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/// ```
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pub async fn search_by_funder(&self, funder_id: &str, limit: usize) -> Result<Vec<SemanticVector>> {
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let mut url = format!(
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"{}/funders/{}/works?rows={}",
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self.base_url, funder_id, limit
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);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Search publications by subject area
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///
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/// # Arguments
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/// * `subject` - Subject area or field
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/// * `limit` - Maximum number of results
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///
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/// # Example
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/// ```rust,ignore
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/// let biology_works = client.search_by_subject("molecular biology", 30).await?;
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/// ```
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pub async fn search_by_subject(&self, subject: &str, limit: usize) -> Result<Vec<SemanticVector>> {
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let encoded_subject = urlencoding::encode(subject);
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let mut url = format!(
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"{}/works?filter=has-subject:true&query.subject={}&rows={}",
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self.base_url, encoded_subject, limit
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);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Get publications that cite a specific DOI
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///
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/// # Arguments
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/// * `doi` - DOI of the work to find citations for
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/// * `limit` - Maximum number of results
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///
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/// # Example
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/// ```rust,ignore
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/// let citing_works = client.get_citations("10.1038/nature12373", 15).await?;
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/// ```
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pub async fn get_citations(&self, doi: &str, limit: usize) -> Result<Vec<SemanticVector>> {
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let normalized_doi = Self::normalize_doi(doi);
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let mut url = format!(
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"{}/works?filter=references:{}&rows={}",
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self.base_url, normalized_doi, limit
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);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Search recent publications since a specific date
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///
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/// # Arguments
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/// * `query` - Search query
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/// * `from_date` - Start date in YYYY-MM-DD format
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/// * `limit` - Maximum number of results
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///
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/// # Example
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/// ```rust,ignore
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/// let recent = client.search_recent("artificial intelligence", "2024-01-01", 25).await?;
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/// ```
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pub async fn search_recent(&self, query: &str, from_date: &str, limit: usize) -> Result<Vec<SemanticVector>> {
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let encoded_query = urlencoding::encode(query);
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let mut url = format!(
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"{}/works?query={}&filter=from-pub-date:{}&rows={}",
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self.base_url, encoded_query, from_date, limit
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);
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Search publications by type
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///
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/// # Arguments
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/// * `work_type` - Type of publication (e.g., "journal-article", "book-chapter", "proceedings-article", "dataset")
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/// * `query` - Optional search query
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/// * `limit` - Maximum number of results
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///
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/// # Supported Types
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/// - `journal-article` - Journal articles
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/// - `book-chapter` - Book chapters
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/// - `proceedings-article` - Conference proceedings
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/// - `dataset` - Research datasets
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/// - `monograph` - Monographs
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/// - `report` - Technical reports
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///
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/// # Example
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/// ```rust,ignore
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/// let datasets = client.search_by_type("dataset", Some("climate"), 10).await?;
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/// let articles = client.search_by_type("journal-article", None, 20).await?;
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/// ```
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pub async fn search_by_type(
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&self,
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work_type: &str,
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query: Option<&str>,
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limit: usize,
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) -> Result<Vec<SemanticVector>> {
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let mut url = format!(
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"{}/works?filter=type:{}&rows={}",
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self.base_url, work_type, limit
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);
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if let Some(q) = query {
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let encoded_query = urlencoding::encode(q);
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url.push_str(&format!("&query={}", encoded_query));
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}
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if let Some(email) = &self.polite_email {
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url.push_str(&format!("&mailto={}", email));
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}
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self.fetch_and_parse(&url).await
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}
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/// Fetch and parse CrossRef API response
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async fn fetch_and_parse(&self, url: &str) -> Result<Vec<SemanticVector>> {
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// Rate limiting
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sleep(Duration::from_millis(CROSSREF_RATE_LIMIT_MS)).await;
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let response = self.fetch_with_retry(url).await?;
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let crossref_response: CrossRefResponse = response.json().await?;
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// Convert works to SemanticVectors
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let vectors = crossref_response
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.message
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.items
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.into_iter()
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.map(|work| self.work_to_vector(work))
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.collect();
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Ok(vectors)
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}
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/// Convert CrossRef work to SemanticVector
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fn work_to_vector(&self, work: CrossRefWork) -> SemanticVector {
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// Extract title
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let title = work
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.title
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.first()
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.cloned()
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.unwrap_or_else(|| "Untitled".to_string());
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// Extract abstract
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let abstract_text = work.abstract_text.unwrap_or_default();
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// Parse publication date (prefer print, fallback to online)
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let timestamp = work
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.published_print
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.or(work.published_online)
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.and_then(|date| Self::parse_crossref_date(&date))
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.unwrap_or_else(Utc::now);
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// Generate embedding from title + abstract
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let combined_text = if abstract_text.is_empty() {
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title.clone()
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} else {
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format!("{} {}", title, abstract_text)
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};
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let embedding = self.embedder.embed_text(&combined_text);
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// Extract authors
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let authors = work
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.author
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.iter()
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.map(|a| Self::format_author_name(a))
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.collect::<Vec<_>>()
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.join("; ");
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// Extract journal/container
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let journal = work
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.container_title
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.first()
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.cloned()
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.unwrap_or_default();
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// Extract subjects
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let subjects = work.subject.join(", ");
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// Extract funders
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let funders = work
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.funder
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.iter()
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.filter_map(|f| f.name.clone())
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.collect::<Vec<_>>()
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.join(", ");
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// Build metadata
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let mut metadata = HashMap::new();
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metadata.insert("doi".to_string(), work.doi.clone());
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metadata.insert("title".to_string(), title);
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metadata.insert("abstract".to_string(), abstract_text);
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metadata.insert("authors".to_string(), authors);
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metadata.insert("journal".to_string(), journal);
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metadata.insert("subjects".to_string(), subjects);
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metadata.insert(
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"citation_count".to_string(),
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work.citation_count.unwrap_or(0).to_string(),
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);
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metadata.insert(
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"references_count".to_string(),
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work.references_count.unwrap_or(0).to_string(),
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);
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metadata.insert("funders".to_string(), funders);
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metadata.insert(
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"type".to_string(),
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work.work_type.unwrap_or_else(|| "unknown".to_string()),
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);
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if let Some(publisher) = work.publisher {
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metadata.insert("publisher".to_string(), publisher);
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}
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metadata.insert("source".to_string(), "crossref".to_string());
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|
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SemanticVector {
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id: format!("doi:{}", work.doi),
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embedding,
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domain: Domain::Research,
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timestamp,
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metadata,
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}
|
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}
|
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|
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/// Parse CrossRef date format
|
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fn parse_crossref_date(date: &CrossRefDate) -> Option<DateTime<Utc>> {
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if let Some(parts) = date.date_parts.first() {
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if parts.is_empty() {
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return None;
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}
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let year = parts[0];
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let month = parts.get(1).copied().unwrap_or(1).max(1).min(12);
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let day = parts.get(2).copied().unwrap_or(1).max(1).min(31);
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NaiveDate::from_ymd_opt(year, month as u32, day as u32)
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.and_then(|d| d.and_hms_opt(0, 0, 0))
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.map(|dt| dt.and_utc())
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} else {
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None
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}
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}
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|
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/// Format author name from CrossRef author structure
|
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fn format_author_name(author: &CrossRefAuthor) -> String {
|
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if let Some(name) = &author.name {
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name.clone()
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} else {
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let given = author.given.as_deref().unwrap_or("");
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let family = author.family.as_deref().unwrap_or("");
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format!("{} {}", given, family).trim().to_string()
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}
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}
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|
|
|
/// Normalize DOI (remove http://, https://, doi.org/ prefixes)
|
|
fn normalize_doi(doi: &str) -> String {
|
|
doi.trim()
|
|
.trim_start_matches("http://")
|
|
.trim_start_matches("https://")
|
|
.trim_start_matches("doi.org/")
|
|
.trim_start_matches("dx.doi.org/")
|
|
.to_string()
|
|
}
|
|
|
|
/// Fetch with retry logic
|
|
async fn fetch_with_retry(&self, url: &str) -> Result<reqwest::Response> {
|
|
let mut retries = 0;
|
|
loop {
|
|
match self.client.get(url).send().await {
|
|
Ok(response) => {
|
|
if response.status() == StatusCode::TOO_MANY_REQUESTS && retries < MAX_RETRIES
|
|
{
|
|
retries += 1;
|
|
tracing::warn!(
|
|
"Rate limited by CrossRef, retrying in {}ms",
|
|
RETRY_DELAY_MS * retries as u64
|
|
);
|
|
sleep(Duration::from_millis(RETRY_DELAY_MS * retries as u64)).await;
|
|
continue;
|
|
}
|
|
if !response.status().is_success() {
|
|
return Err(FrameworkError::Network(
|
|
reqwest::Error::from(response.error_for_status().unwrap_err()),
|
|
));
|
|
}
|
|
return Ok(response);
|
|
}
|
|
Err(_) if retries < MAX_RETRIES => {
|
|
retries += 1;
|
|
tracing::warn!("Request failed, retrying ({}/{})", retries, MAX_RETRIES);
|
|
sleep(Duration::from_millis(RETRY_DELAY_MS * retries as u64)).await;
|
|
}
|
|
Err(e) => return Err(FrameworkError::Network(e)),
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
impl Default for CrossRefClient {
|
|
fn default() -> Self {
|
|
Self::new(None)
|
|
}
|
|
}
|
|
|
|
// ============================================================================
|
|
// Tests
|
|
// ============================================================================
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
|
|
#[test]
|
|
fn test_crossref_client_creation() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
assert_eq!(client.base_url, "https://api.crossref.org");
|
|
assert_eq!(client.polite_email, Some("test@example.com".to_string()));
|
|
}
|
|
|
|
#[test]
|
|
fn test_crossref_client_without_email() {
|
|
let client = CrossRefClient::new(None);
|
|
assert_eq!(client.base_url, "https://api.crossref.org");
|
|
assert_eq!(client.polite_email, None);
|
|
}
|
|
|
|
#[test]
|
|
fn test_custom_embedding_dim() {
|
|
let client = CrossRefClient::with_embedding_dim(None, 512);
|
|
let embedding = client.embedder.embed_text("test");
|
|
assert_eq!(embedding.len(), 512);
|
|
}
|
|
|
|
#[test]
|
|
fn test_normalize_doi() {
|
|
assert_eq!(
|
|
CrossRefClient::normalize_doi("10.1038/nature12373"),
|
|
"10.1038/nature12373"
|
|
);
|
|
assert_eq!(
|
|
CrossRefClient::normalize_doi("http://doi.org/10.1038/nature12373"),
|
|
"10.1038/nature12373"
|
|
);
|
|
assert_eq!(
|
|
CrossRefClient::normalize_doi("https://dx.doi.org/10.1038/nature12373"),
|
|
"10.1038/nature12373"
|
|
);
|
|
assert_eq!(
|
|
CrossRefClient::normalize_doi(" 10.1038/nature12373 "),
|
|
"10.1038/nature12373"
|
|
);
|
|
}
|
|
|
|
#[test]
|
|
fn test_parse_crossref_date() {
|
|
// Full date
|
|
let date1 = CrossRefDate {
|
|
date_parts: vec![vec![2024, 3, 15]],
|
|
};
|
|
let parsed1 = CrossRefClient::parse_crossref_date(&date1);
|
|
assert!(parsed1.is_some());
|
|
let dt1 = parsed1.unwrap();
|
|
assert_eq!(dt1.format("%Y-%m-%d").to_string(), "2024-03-15");
|
|
|
|
// Year and month only
|
|
let date2 = CrossRefDate {
|
|
date_parts: vec![vec![2024, 3]],
|
|
};
|
|
let parsed2 = CrossRefClient::parse_crossref_date(&date2);
|
|
assert!(parsed2.is_some());
|
|
|
|
// Year only
|
|
let date3 = CrossRefDate {
|
|
date_parts: vec![vec![2024]],
|
|
};
|
|
let parsed3 = CrossRefClient::parse_crossref_date(&date3);
|
|
assert!(parsed3.is_some());
|
|
|
|
// Empty date parts
|
|
let date4 = CrossRefDate {
|
|
date_parts: vec![vec![]],
|
|
};
|
|
let parsed4 = CrossRefClient::parse_crossref_date(&date4);
|
|
assert!(parsed4.is_none());
|
|
}
|
|
|
|
#[test]
|
|
fn test_format_author_name() {
|
|
// Full name
|
|
let author1 = CrossRefAuthor {
|
|
given: Some("John".to_string()),
|
|
family: Some("Doe".to_string()),
|
|
name: None,
|
|
orcid: None,
|
|
};
|
|
assert_eq!(
|
|
CrossRefClient::format_author_name(&author1),
|
|
"John Doe"
|
|
);
|
|
|
|
// Name field only
|
|
let author2 = CrossRefAuthor {
|
|
given: None,
|
|
family: None,
|
|
name: Some("Jane Smith".to_string()),
|
|
orcid: None,
|
|
};
|
|
assert_eq!(
|
|
CrossRefClient::format_author_name(&author2),
|
|
"Jane Smith"
|
|
);
|
|
|
|
// Family name only
|
|
let author3 = CrossRefAuthor {
|
|
given: None,
|
|
family: Some("Einstein".to_string()),
|
|
name: None,
|
|
orcid: None,
|
|
};
|
|
assert_eq!(
|
|
CrossRefClient::format_author_name(&author3),
|
|
"Einstein"
|
|
);
|
|
}
|
|
|
|
#[test]
|
|
fn test_work_to_vector() {
|
|
let client = CrossRefClient::new(None);
|
|
|
|
let work = CrossRefWork {
|
|
doi: "10.1234/example.2024".to_string(),
|
|
title: vec!["Deep Learning for Climate Science".to_string()],
|
|
abstract_text: Some("We propose a novel approach to climate modeling...".to_string()),
|
|
author: vec![
|
|
CrossRefAuthor {
|
|
given: Some("Alice".to_string()),
|
|
family: Some("Johnson".to_string()),
|
|
name: None,
|
|
orcid: Some("0000-0001-2345-6789".to_string()),
|
|
},
|
|
CrossRefAuthor {
|
|
given: Some("Bob".to_string()),
|
|
family: Some("Smith".to_string()),
|
|
name: None,
|
|
orcid: None,
|
|
},
|
|
],
|
|
published_print: Some(CrossRefDate {
|
|
date_parts: vec![vec![2024, 6, 15]],
|
|
}),
|
|
published_online: None,
|
|
container_title: vec!["Nature Climate Change".to_string()],
|
|
citation_count: Some(42),
|
|
references_count: Some(35),
|
|
subject: vec!["Climate Science".to_string(), "Machine Learning".to_string()],
|
|
funder: vec![CrossRefFunder {
|
|
name: Some("National Science Foundation".to_string()),
|
|
doi: Some("10.13039/100000001".to_string()),
|
|
}],
|
|
work_type: Some("journal-article".to_string()),
|
|
publisher: Some("Nature Publishing Group".to_string()),
|
|
};
|
|
|
|
let vector = client.work_to_vector(work);
|
|
|
|
assert_eq!(vector.id, "doi:10.1234/example.2024");
|
|
assert_eq!(vector.domain, Domain::Research);
|
|
assert_eq!(
|
|
vector.metadata.get("doi").unwrap(),
|
|
"10.1234/example.2024"
|
|
);
|
|
assert_eq!(
|
|
vector.metadata.get("title").unwrap(),
|
|
"Deep Learning for Climate Science"
|
|
);
|
|
assert_eq!(
|
|
vector.metadata.get("authors").unwrap(),
|
|
"Alice Johnson; Bob Smith"
|
|
);
|
|
assert_eq!(
|
|
vector.metadata.get("journal").unwrap(),
|
|
"Nature Climate Change"
|
|
);
|
|
assert_eq!(vector.metadata.get("citation_count").unwrap(), "42");
|
|
assert_eq!(
|
|
vector.metadata.get("subjects").unwrap(),
|
|
"Climate Science, Machine Learning"
|
|
);
|
|
assert_eq!(
|
|
vector.metadata.get("funders").unwrap(),
|
|
"National Science Foundation"
|
|
);
|
|
assert_eq!(vector.metadata.get("type").unwrap(), "journal-article");
|
|
assert_eq!(
|
|
vector.metadata.get("publisher").unwrap(),
|
|
"Nature Publishing Group"
|
|
);
|
|
assert_eq!(vector.embedding.len(), DEFAULT_EMBEDDING_DIM);
|
|
}
|
|
|
|
#[tokio::test]
|
|
#[ignore] // Ignore by default to avoid hitting CrossRef API in tests
|
|
async fn test_search_works_integration() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
let results = client.search_works("machine learning", 5).await;
|
|
assert!(results.is_ok());
|
|
|
|
let vectors = results.unwrap();
|
|
assert!(vectors.len() <= 5);
|
|
|
|
if !vectors.is_empty() {
|
|
let first = &vectors[0];
|
|
assert!(first.id.starts_with("doi:"));
|
|
assert_eq!(first.domain, Domain::Research);
|
|
assert!(first.metadata.contains_key("title"));
|
|
assert!(first.metadata.contains_key("doi"));
|
|
}
|
|
}
|
|
|
|
#[tokio::test]
|
|
#[ignore] // Ignore by default to avoid hitting CrossRef API in tests
|
|
async fn test_get_work_integration() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
|
|
// Try to fetch a known work (Nature paper on AlphaFold)
|
|
let result = client.get_work("10.1038/s41586-021-03819-2").await;
|
|
assert!(result.is_ok());
|
|
|
|
let work = result.unwrap();
|
|
assert!(work.is_some());
|
|
|
|
let vector = work.unwrap();
|
|
assert_eq!(vector.id, "doi:10.1038/s41586-021-03819-2");
|
|
assert_eq!(vector.domain, Domain::Research);
|
|
}
|
|
|
|
#[tokio::test]
|
|
#[ignore] // Ignore by default to avoid hitting CrossRef API in tests
|
|
async fn test_search_by_funder_integration() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
|
|
// Search NSF-funded works
|
|
let results = client.search_by_funder("10.13039/100000001", 3).await;
|
|
assert!(results.is_ok());
|
|
|
|
let vectors = results.unwrap();
|
|
assert!(vectors.len() <= 3);
|
|
}
|
|
|
|
#[tokio::test]
|
|
#[ignore] // Ignore by default to avoid hitting CrossRef API in tests
|
|
async fn test_search_by_type_integration() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
|
|
// Search for datasets
|
|
let results = client.search_by_type("dataset", Some("climate"), 5).await;
|
|
assert!(results.is_ok());
|
|
|
|
let vectors = results.unwrap();
|
|
assert!(vectors.len() <= 5);
|
|
}
|
|
|
|
#[tokio::test]
|
|
#[ignore] // Ignore by default to avoid hitting CrossRef API in tests
|
|
async fn test_search_recent_integration() {
|
|
let client = CrossRefClient::new(Some("test@example.com".to_string()));
|
|
|
|
// Search recent papers
|
|
let results = client
|
|
.search_recent("quantum computing", "2024-01-01", 5)
|
|
.await;
|
|
assert!(results.is_ok());
|
|
|
|
let vectors = results.unwrap();
|
|
assert!(vectors.len() <= 5);
|
|
}
|
|
}
|