chore: Refactor comment posting functionality and improve performance

app.py

@@ -96,9 +96,6 @@ def format_comment(result: str):
     return result
 
 
-from typing import Tuple
-
-
 def post_comment(
     paper_url: str, comment: str, comment_id: str | None = None, token: str = HF_TOKEN
 ) -> Tuple[bool, str]:
@@ -123,9 +120,12 @@ def post_comment(
         paper_id = paper_url.split("/")[-1]
         if comment_id:
             url = f"https://huggingface.co/api/papers/{paper_id}/comment/{comment_id}/reply"
+            gr.Info(f"Replying to comment {comment_id}")
+            print(f"Replying to comment {comment_id}")
         else:
             url = f"https://huggingface.co/api/papers/{paper_id}/comment"
-
+            print(f"Posting comment for {paper_url}")
+            gr.Info(f"Posting comment for {paper_url}")
         headers = {
             "Authorization": f"Bearer {token}",
             "Content-Type": "application/json",
@@ -240,36 +240,47 @@ def log_comments(paper_url: str, comment: str):
 
 
 def return_recommendations(
-    url: str, comment_id: str | None = None, post_to_paper: bool = True
+    url: str, comment_id: str | None, post_to_paper: bool = True
 ) -> str:
     arxiv_id = parse_arxiv_id_from_paper_url(url)
     recommendations = get_recommendations_from_semantic_scholar(f"ArXiv:{arxiv_id}")
     filtered_recommendations = filter_recommendations(recommendations)
+
     if post_to_paper:
-        existing_comments, comment_id = check_if_lib_bot_comment_exists(url)
+        formatted_recommendation = format_recommendation_into_markdown(
+            arxiv_id, filtered_recommendations
+        )
+        comment = format_comment(formatted_recommendation)
+
+        # Check if a librarian-bot comment already exists.
+        existing_comments, existing_comment_id = check_if_lib_bot_comment_exists(url)
         if existing_comments:
-            gr.Info(f"Existing comment: {comment_id}...skipping posting comment")
+            gr.Info(
+                f"Librarian-bot already commented on this paper. Comment ID: {existing_comment_id}. No further action will be taken."
+            )
+            return formatted_recommendation  # Return formatted recommendation without posting.
+
+        # If no existing librarian-bot comment, check if a specific comment_id is provided for replying.
+        if comment_id:
+            comment_status, posted_comment_id = post_comment(
+                url, comment, comment_id, token=HF_TOKEN
+            )
+            if comment_status:
+                log_comments(url, comment)
+                gr.Info(f"Posted reply to comment {posted_comment_id}")
         else:
-            comment = format_comment(
-                format_recommendation_into_markdown(arxiv_id, filtered_recommendations)
+            # If no comment_id is provided, post a new comment.
+            comment_status, posted_comment_id = post_comment(
+                url, comment, token=HF_TOKEN
             )
-            if comment_id:
-                comment_status, posted_comment_id = post_comment(
-                    url, comment, comment_id, token=HF_TOKEN
-                )
-                if comment_status:
-                    log_comments(url, comment)
-                    gr.Info(f"Posted reply to comment {posted_comment_id}")
-            if not comment_id:
-                comment_status, posted_comment_id = post_comment(
-                    url, comment, token=HF_TOKEN
-                )
-                if comment_status:
-                    log_comments(url, comment)
-                    gr.Info(f"Posted comment {posted_comment_id}")
-            else:
-                gr.Info("Failed to post comment")
-    return format_recommendation_into_markdown(arxiv_id, filtered_recommendations)
+            if comment_status:
+                log_comments(url, comment)
+                gr.Info(f"Posted new comment {posted_comment_id}")
+
+        if not comment_status:
+            gr.Info("Failed to post comment")
+
+    return formatted_recommendation
 
 
 title = "Semantic Scholar Paper Recommender"