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import React, { useState, useEffect } from 'react'; | |
import { ExternalLink, FileText, Loader2, Brain, Cpu, MessageSquare } from 'lucide-react'; | |
import { Link } from 'react-router-dom'; | |
import api from '../services/api'; | |
interface Algorithm { | |
algorithm: string; | |
name: string; | |
category: string; | |
description: string; | |
count: number; | |
sampleIds: string[]; | |
} | |
interface Paper { | |
pmid: string; | |
title: string; | |
authors: string[]; | |
journal: string; | |
pubDate: string; | |
} | |
interface AlgorithmCardProps { | |
algorithm: Algorithm; | |
problem: string; | |
onSeeMorePapers: (algorithm: string) => void; | |
} | |
const AlgorithmCard: React.FC<AlgorithmCardProps> = ({ algorithm, problem, onSeeMorePapers }) => { | |
const [samplePapers, setSamplePapers] = useState<Paper[]>([]); | |
const [loadingPapers, setLoadingPapers] = useState(false); | |
useEffect(() => { | |
// Temporarily disabled to avoid PubMed API rate limiting issues | |
// if (algorithm.sampleIds.length > 0) { | |
// fetchSamplePapers(); | |
// } | |
}, [algorithm.sampleIds]); | |
const fetchSamplePapers = async () => { | |
try { | |
setLoadingPapers(true); | |
console.log(`[${algorithm.name}] Fetching sample papers for IDs:`, algorithm.sampleIds); | |
const papers = []; | |
// Fetch papers sequentially with delays to avoid rate limiting | |
for (let i = 0; i < algorithm.sampleIds.length && i < 2; i++) { | |
try { | |
console.log(`[${algorithm.name}] Fetching paper ${i + 1}/${Math.min(algorithm.sampleIds.length, 2)}: ${algorithm.sampleIds[i]}`); | |
if (i > 0) { | |
// Add delay between requests to avoid rate limiting | |
await new Promise(resolve => setTimeout(resolve, 500)); | |
} | |
const response = await api.get(`/pubmed/paper/${algorithm.sampleIds[i]}`); | |
console.log(`[${algorithm.name}] Response for ${algorithm.sampleIds[i]}:`, response.status, response.data); | |
if (response.data && response.data.title) { | |
papers.push(response.data); | |
console.log(`[${algorithm.name}] Successfully added paper: ${response.data.title}`); | |
} else { | |
console.log(`[${algorithm.name}] Invalid paper data for ${algorithm.sampleIds[i]}:`, response.data); | |
} | |
} catch (error) { | |
console.error(`[${algorithm.name}] Failed to fetch paper ${algorithm.sampleIds[i]}:`, { | |
status: error.response?.status, | |
statusText: error.response?.statusText, | |
data: error.response?.data, | |
message: error.message | |
}); | |
// Continue with next paper if one fails | |
} | |
} | |
console.log(`[${algorithm.name}] Final fetched papers:`, papers); | |
setSamplePapers(papers); | |
} catch (error) { | |
console.error(`[${algorithm.name}] Failed to fetch sample papers:`, error); | |
} finally { | |
setLoadingPapers(false); | |
} | |
}; | |
const getCategoryIcon = (category: string) => { | |
switch (category) { | |
case 'deep_learning': | |
return <Cpu className="h-5 w-5 text-purple-600" />; | |
case 'llms': | |
return <MessageSquare className="h-5 w-5 text-green-600" />; | |
default: | |
return <Brain className="h-5 w-5 text-blue-600" />; | |
} | |
}; | |
const getCategoryColor = (category: string) => { | |
switch (category) { | |
case 'deep_learning': | |
return 'bg-purple-100 text-purple-800'; | |
case 'llms': | |
return 'bg-green-100 text-green-800'; | |
default: | |
return 'bg-blue-100 text-blue-800'; | |
} | |
}; | |
return ( | |
<div className="bg-white rounded-lg shadow-md hover:shadow-lg transition-shadow duration-200 overflow-hidden h-full flex flex-col"> | |
<div className="p-6 flex-grow"> | |
<div className="flex items-start justify-between mb-4"> | |
<div className="flex items-center space-x-3"> | |
{getCategoryIcon(algorithm.category)} | |
<Link | |
to={`/algorithm/${algorithm.algorithm}`} | |
className="text-lg font-semibold text-gray-900 leading-tight hover:text-blue-600 transition-colors" | |
> | |
{algorithm.name} | |
</Link> | |
</div> | |
<span className={`px-3 py-1 rounded-full text-xs font-semibold ${getCategoryColor(algorithm.category)} whitespace-nowrap ml-2`}> | |
{algorithm.category === 'deep_learning' ? 'Deep Learning' : algorithm.category === 'llms' ? 'LLMs' : 'Classical ML'} | |
</span> | |
</div> | |
<p className="text-gray-600 text-sm mb-4">{algorithm.description}</p> | |
<div className="mb-4"> | |
<div className="text-center bg-gray-50 rounded-lg p-4"> | |
<div className="text-3xl font-bold text-gray-900">{algorithm.count.toLocaleString()}</div> | |
<div className="text-sm text-gray-500 font-medium">Papers Found</div> | |
</div> | |
</div> | |
{algorithm.sampleIds.length > 0 && ( | |
<div className="mb-4"> | |
<h4 className="text-sm font-medium text-gray-900 mb-2">Sample Papers:</h4> | |
{loadingPapers ? ( | |
<div className="flex items-center justify-center py-4"> | |
<Loader2 className="h-4 w-4 animate-spin text-gray-400" /> | |
<span className="ml-2 text-sm text-gray-500">Loading papers...</span> | |
</div> | |
) : samplePapers.length > 0 ? ( | |
<div className="space-y-3"> | |
{samplePapers.slice(0, 2).map((paper) => ( | |
<div key={paper.pmid} className="p-3 bg-gray-50 rounded-lg border border-gray-100"> | |
<p className="font-medium text-gray-900 text-sm line-clamp-2 mb-1">{paper.title}</p> | |
<p className="text-gray-500 text-xs"> | |
{paper.journal} {paper.pubDate && `(${paper.pubDate})`} | |
</p> | |
</div> | |
))} | |
</div> | |
) : ( | |
<div className="p-3 bg-blue-50 rounded-lg border border-blue-100"> | |
<p className="text-xs text-blue-600 text-center"> | |
{algorithm.count} papers found - Click "See More Papers on PubMed" to view | |
</p> | |
</div> | |
)} | |
</div> | |
)} | |
</div> | |
<div className="p-6 pt-0 mt-auto"> | |
<button | |
onClick={() => onSeeMorePapers(algorithm.algorithm)} | |
className="w-full bg-blue-600 text-white py-3 px-4 rounded-lg hover:bg-blue-700 transition-colors flex items-center justify-center text-sm font-medium shadow-sm" | |
> | |
<ExternalLink className="h-4 w-4 mr-2" /> | |
See More Papers on PubMed | |
</button> | |
</div> | |
</div> | |
); | |
}; | |
export default AlgorithmCard; |