Create arxiv_tool.py

tools/arxiv_tool.py

@@ -0,0 +1,92 @@
+import arxiv
+from datetime import datetime, timedelta
+import json
+import os
+from typing import List, Dict
+from smolagents import Tool
+
+class ArxivSearchTool(Tool):
+    name = "search_arxiv"
+    description = "Search ArXiv for papers matching the query"
+    input_types = {"query": str, "max_results": int}
+    output_type = List[Dict]
+
+    def __call__(self, query: str = "artificial intelligence", 
+                max_results: int = 50) -> List[Dict]:
+        try:
+            # Configure the search client
+            client = arxiv.Client()
+            
+            # Create the search query
+            search = arxiv.Search(
+                query=query,
+                max_results=max_results,
+                sort_by=arxiv.SortCriterion.SubmittedDate
+            )
+            
+            # Get results
+            results = []
+            for paper in client.results(search):
+                result = {
+                    'title': paper.title,
+                    'authors': [str(author) for author in paper.authors],
+                    'summary': paper.summary,
+                    'published': paper.published.strftime("%Y-%m-%d"),
+                    'pdf_url': paper.pdf_url,
+                    'entry_id': paper.entry_id,
+                    'primary_category': paper.primary_category,
+                    'categories': paper.categories
+                }
+                results.append(result)
+                
+            return results
+        except Exception as e:
+            return [{"error": f"Error searching ArXiv: {str(e)}"}]
+
+class LatestPapersTool(Tool):
+    name = "get_latest_papers"
+    description = "Get papers from the last N days from saved results"
+    input_types = {"days_back": int}
+    output_type = List[Dict]
+
+    def __call__(self, days_back: int = 1) -> List[Dict]:
+        papers = []
+        base_dir = "daily_papers"
+        
+        # Get dates to check
+        dates = [
+            (datetime.now() - timedelta(days=i)).strftime("%Y-%m-%d")
+            for i in range(days_back)
+        ]
+        
+        # Load papers for each date
+        for date in dates:
+            file_path = os.path.join(base_dir, f"ai_papers_{date}.json")
+            if os.path.exists(file_path):
+                with open(file_path, 'r', encoding='utf-8') as f:
+                    day_papers = json.load(f)
+                    papers.extend(day_papers)
+        
+        return papers
+
+def save_daily_papers(output_dir: str = "daily_papers") -> List[Dict]:
+    """Helper function to save daily papers - not exposed as a tool"""
+    os.makedirs(output_dir, exist_ok=True)
+    today = datetime.now().strftime("%Y-%m-%d")
+    
+    arxiv_tool = ArxivSearchTool()
+    papers = arxiv_tool(
+        query='cat:cs.AI OR cat:cs.LG OR cat:cs.CL OR "artificial intelligence"',
+        max_results=100
+    )
+    
+    today_papers = [
+        paper for paper in papers 
+        if paper.get('published') == today
+    ]
+    
+    output_file = os.path.join(output_dir, f"ai_papers_{today}.json")
+    with open(output_file, 'w', encoding='utf-8') as f:
+        json.dump(today_papers, f, indent=2)
+    
+    return today_papers