davanstrien HF staff commited on
Commit
91bf496
1 Parent(s): 0255055

Add comment posting functionality

Browse files
Files changed (1) hide show
  1. app.py +125 -4
app.py CHANGED
@@ -1,9 +1,33 @@
1
  import gradio as gr
2
  import requests
3
  from cachetools import cached, TTLCache
 
 
 
 
 
 
 
 
 
 
 
4
 
5
  CACHE_TIME = 60 * 60 * 6 # 6 hours
6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7
 
8
  def parse_arxiv_id_from_paper_url(url):
9
  return url.split("/")[-1]
@@ -59,10 +83,106 @@ def format_recommendation_into_markdown(arxiv_id, recommendations):
59
  return comment
60
 
61
 
62
- def return_recommendations(url):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
63
  arxiv_id = parse_arxiv_id_from_paper_url(url)
64
  recommendations = get_recommendations_from_semantic_scholar(f"ArXiv:{arxiv_id}")
65
  filtered_recommendations = filter_recommendations(recommendations)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
  return format_recommendation_into_markdown(arxiv_id, filtered_recommendations)
67
 
68
 
@@ -73,15 +193,16 @@ description = (
73
  " yet if they are new or have not been indexed by Semantic Scholar."
74
  )
75
  examples = [
76
- "https://huggingface.co/papers/2309.12307",
77
- "https://huggingface.co/papers/2211.10086",
78
  ]
79
  interface = gr.Interface(
80
  return_recommendations,
81
- gr.Textbox(lines=1),
82
  gr.Markdown(),
83
  examples=examples,
84
  title=title,
85
  description=description,
86
  )
 
87
  interface.launch()
 
1
  import gradio as gr
2
  import requests
3
  from cachetools import cached, TTLCache
4
+ from bs4 import BeautifulSoup
5
+ from httpx import Client
6
+ import json
7
+ from pathlib import Path
8
+ from huggingface_hub import CommitScheduler
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+ from dotenv import load_dotenv
10
+ import os
11
+
12
+ load_dotenv()
13
+
14
+ HF_TOKEN = os.getenv("HF_TOKEN")
15
 
16
  CACHE_TIME = 60 * 60 * 6 # 6 hours
17
 
18
+ client = Client()
19
+
20
+ REPO_ID = "librarian-bots/paper-recommendations-v2"
21
+
22
+ scheduler = CommitScheduler(
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+ repo_id=REPO_ID,
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+ repo_type="dataset",
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+ folder_path="comments",
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+ path_in_repo="data",
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+ every=5,
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+ token=HF_TOKEN,
29
+ )
30
+
31
 
32
  def parse_arxiv_id_from_paper_url(url):
33
  return url.split("/")[-1]
 
83
  return comment
84
 
85
 
86
+ def format_comment(result: str):
87
+ result = (
88
+ "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\n"
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+ + result
90
+ )
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+ result += "\n\n Please give a thumbs up to this comment if you found it helpful!"
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+ result += "\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space"
93
+ return result
94
+
95
+
96
+ def post_comment(
97
+ paper_url: str, comment: str, token: str | None = None, base_url: str | None = None
98
+ ) -> bool:
99
+ if not base_url:
100
+ base_url = "https://huggingface.co"
101
+ paper_id = paper_url.split("/")[-1]
102
+ url = f"{base_url}/api/papers/{paper_id}/comment"
103
+ comment_data = {"comment": comment}
104
+ headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
105
+ response = requests.post(url, json=comment_data, headers=headers)
106
+ if response.status_code == 201:
107
+ print(f"Comment posted successfully for {paper_url}!")
108
+ return True
109
+ else:
110
+ print(f"Failed to post comment! (Status Code: {response.status_code})")
111
+ print(response.text)
112
+ return False
113
+
114
+
115
+ def is_comment_from_librarian_bot(html: str) -> bool:
116
+ """
117
+ Checks if the given HTML contains a comment from the librarian-bot.
118
+
119
+ Args:
120
+ html (str): The HTML content to check.
121
+
122
+ Returns:
123
+ bool: True if a comment from the librarian-bot is found, False otherwise.
124
+ """
125
+ soup = BeautifulSoup(html, "lxml")
126
+ librarian_bot_links = soup.find_all("a", string="librarian-bot")
127
+ return any(librarian_bot_links)
128
+
129
+
130
+ def check_if_lib_bot_comment_exists(paper_url: str) -> bool:
131
+ """
132
+ Checks if a comment from the librarian bot exists for a given paper URL.
133
+
134
+ Args:
135
+ paper_url (str): The URL of the paper.
136
+
137
+ Returns:
138
+ bool: True if a comment from the librarian bot exists, False otherwise.
139
+ """
140
+ try:
141
+ resp = client.get(paper_url)
142
+ return is_comment_from_librarian_bot(resp.text)
143
+ except Exception as e:
144
+ print(f"Error checking if comment exists for {paper_url}: {e}")
145
+ return True # default to not posting comment
146
+
147
+
148
+ def log_comments(paper_url: str, comment: str):
149
+ """
150
+ Logs comments for a given paper URL.
151
+
152
+ Args:
153
+ paper_url (str): The URL of the paper.
154
+ comment (str): The comment to be logged.
155
+
156
+ Returns:
157
+ None
158
+ """
159
+ paper_id = paper_url.split("/")[-1]
160
+ file_path = Path(f"comments/{paper_id}.json")
161
+ if not file_path.exists():
162
+ with scheduler.lock:
163
+ with open(file_path, "w") as f:
164
+ data = {"paper_url": paper_url, "comment": comment}
165
+ json.dump(data, f)
166
+
167
+
168
+ def return_recommendations(url: str, post_to_paper: bool = True) -> str:
169
  arxiv_id = parse_arxiv_id_from_paper_url(url)
170
  recommendations = get_recommendations_from_semantic_scholar(f"ArXiv:{arxiv_id}")
171
  filtered_recommendations = filter_recommendations(recommendations)
172
+ if post_to_paper:
173
+ if comment_already_exists := check_if_lib_bot_comment_exists(url):
174
+ gr.Info(
175
+ f"Existing comment: {comment_already_exists}...skipping posting comment"
176
+ )
177
+ else:
178
+ comment = format_comment(
179
+ format_recommendation_into_markdown(arxiv_id, filtered_recommendations)
180
+ )
181
+ if comment_status := post_comment(url, comment, token=HF_TOKEN):
182
+ log_comments(url, comment)
183
+ gr.Info(f"Comment status: {comment_status}")
184
+ else:
185
+ gr.Info("Failed to post comment")
186
  return format_recommendation_into_markdown(arxiv_id, filtered_recommendations)
187
 
188
 
 
193
  " yet if they are new or have not been indexed by Semantic Scholar."
194
  )
195
  examples = [
196
+ ["https://huggingface.co/papers/2309.12307", False],
197
+ ["https://huggingface.co/papers/2211.10086", False],
198
  ]
199
  interface = gr.Interface(
200
  return_recommendations,
201
+ [gr.Textbox(lines=1), gr.Checkbox(label="Post to Paper", default=False)],
202
  gr.Markdown(),
203
  examples=examples,
204
  title=title,
205
  description=description,
206
  )
207
+ interface.queue()
208
  interface.launch()