Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

.vscode/settings.json

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+{
+    "sqltools.connections": [
+        {
+            "mysqlOptions": {
+                "authProtocol": "default",
+                "enableSsl": "Disabled"
+            },
+            "previewLimit": 50,
+            "server": "localhost",
+            "port": 3306,
+            "driver": "MySQL",
+            "name": "local",
+            "database": "b3log_symphony",
+            "username": "root",
+            "password": "123456"
+        }
+    ]
+}

README.md

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+# paper-ai
+ 根据ai寻找到的论文自动生成引用

getPaper.py

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+import arxiv
+
+def get_authors(authors, first_author = False):
+    output = str()
+    if first_author == False:
+        output = ", ".join(str(author) for author in authors)
+    else:
+        output = authors[0]
+    return output
+
+def get_daily_papers(topic,query="slam", max_results=2):
+    """
+    @param topic: str
+    @param query: str
+    @return paper_with_code: dict
+    """
+
+    # output 
+    content = dict() 
+    
+    search_engine = arxiv.Search(
+        query = query,
+        max_results = max_results,
+        sort_by = arxiv.SortCriterion.SubmittedDate
+    )
+
+    for result in search_engine.results():
+
+        paper_id       = result.get_short_id()
+        paper_title    = result.title
+        paper_url      = result.entry_id
+
+        paper_abstract = result.summary.replace("\n"," ")
+        paper_authors  = get_authors(result.authors)
+        paper_first_author = get_authors(result.authors,first_author = True)
+        primary_category = result.primary_category
+
+        publish_time = result.published.date()
+
+        print("Time = ", publish_time ,
+              " title = ", paper_title,
+              " author = ", paper_first_author)
+
+        # eg: 2108.09112v1 -> 2108.09112
+        ver_pos = paper_id.find('v')
+        if ver_pos == -1:
+            paper_key = paper_id
+        else:
+            paper_key = paper_id[0:ver_pos] 
+
+        content[paper_key] = f"|**{publish_time}**|**{paper_title}**|{paper_first_author} et.al.|[{paper_id}]({paper_url})|\n"
+    data = {topic:content}
+    
+    return data 
+ 
+ 
+if __name__ == "__main__":
+
+    data_collector = []
+    keywords = dict()
+    keywords["SLAM"] = "SLAM"
+ 
+    for topic,keyword in keywords.items():
+ 
+        print("Keyword: " + topic)
+        data = get_daily_papers(topic, query = keyword, max_results = 10)
+        data_collector.append(data)
+        print("\n")
+
+
+

pass

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+wW5gVm+DjTU.WV~
+anonpublic:eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6InlpZGZ1a2Zicmx1aXpqdmZycnNqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MDQ4NjMyNjEsImV4cCI6MjAyMDQzOTI2MX0.EXIXAdNIGLFo5wHmwmY2-9bqLO9vyFYDvMMtCtkxgig
+
+service_role: