updates

app.py

@@ -9,20 +9,11 @@ def check_password(username, password):
     else:
         return False
 
-def remove_latex_tags(input_string):
-    if input_string.startswith("```latex") and input_string.endswith("```"):
-        # Remove the ```latex at the beginning and ``` at the end
-        result_string = input_string[len("```latex"):-len("```")]
-        return result_string
-    else:
-        # If the input string doesn't have the expected tags, return it unchanged
-        return input_string
 
 def func(file, number_of_pages, secret):
     if secret != os.environ["ACCESS"]:
         return "Wrong password, please try again"
     text = client.predict(file, number_of_pages)
-    text = remove_latex_tags(text)
     # generate a random sequence of numbers
     # s = "".join([str(random.randint(0, 9)) for i in range(10)])
     # with open(f"{s}.tex", "w", encoding="utf-8") as f:
@@ -33,7 +24,7 @@ def upload_file(file):
     return file.name
 
 description = r"""
-<h3> Scideck is a tool that allows you to convert your PDF files into a presentation deck.</h3>
+<h3> SCIDECK is a tool that allows you to convert your PDF files into a presentation deck.</h3>
 <br>
 
 ❗️❗️❗️[<b>Important</b>] Instructions:<br>
@@ -45,6 +36,11 @@ description = r"""
 
  
 📝 If you get an error message, you can send me email with the PDF file attached to this email address: <b>nkoisheke [at] ethz [dot] ch</b>, and I will generate the slides for you. If there are any other issues or questions, please do not hesitate to contact me 🤗 <br>
+
+🖼️ Some examples of slides generated using SCIDECK are shown below: <br>
+1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift [[Paper]](https://arxiv.org/pdf/1502.03167.pdf) [[Slides]](https://drive.google.com/file/d/1Zt5FFH0nKxut-LyEr9pNAIdtgR_lBtIj/view?usp=sharing) <br>
+2. Attention Is All You Need [[Paper]](https://arxiv.org/pdf/1706.03762.pdf) [[Slides]](https://drive.google.com/file/d/1xKgohh_QKV9pD_XjDuXR566h0VJ1S7WI/view?usp=sharing) <br>
+3. Denoising Diffusion Probabilistic Models [[Paper]](https://arxiv.org/pdf/2006.11239.pdf) [[Slides]](https://drive.google.com/file/d/1D2ZfoJpHR3kP0JdsYyjxUq-vjVMV-KTO/view?usp=sharing) <br>
 """
 
 read_key = os.environ.get("HF_TOKEN", None)