Upload 23 files

hashed_codes.txt

@@ -0,0 +1,100 @@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interfaces/iupac2smiles.py

@@ -1,7 +1,9 @@
 import gradio as gr
-from utils import ChemicalConverter, validate_smiles2iupac, plot_mol
+from utils import ChemicalConverter, validate_smiles2iupac, plot_mol, login
 
-def convert(chemical_name, plot):
+def convert(access_code, chemical_name, plot):
+    if not login(access_code.replace(" ", "")):
+        return "Currently, you don't have access to the service.", None
     # Initialize the ChemicalConverter
     converter = ChemicalConverter(mode="IUPAC2SMILES")
     converted_name = ""
@@ -16,12 +18,13 @@ iupac2smiles = gr.Interface(
     fn=convert,
     allow_flagging='auto',
     inputs=[
+        gr.Textbox(label="Enter your access code", placeholder=""),
         gr.Textbox(label="Enter your IUPAC name", placeholder="Enter IUPAC name here"),
         gr.Checkbox(label="Plot molecule", value=True)
     ],
     outputs=[gr.Text(label="Converted Name"),
              gr.Image(type='pil', label="Molecule Plot", height=170, width=890)],
     examples=[
-        ["ethanol", True]
+        [None, "ethanol", True]
     ],
 )

interfaces/iupac2style.py

@@ -1,7 +1,9 @@
 import gradio as gr
-from utils import ChemicalConverter, validate_smiles2iupac, plot_mol
+from utils import ChemicalConverter, validate_smiles2iupac, plot_mol, login
 
-def convert(chemical_name, plot):
+def convert(access_code, chemical_name, plot):
+    if not login(access_code.replace(" ", "")):
+        return "Currently, you don't have access to the service."
     # Initialize the ChemicalConverter
     converter = ChemicalConverter(mode="IUPAC2SMILES")
     converted_name = converter.convert(chemical_name)[:6]
@@ -13,10 +15,11 @@ iupac2style = gr.Interface(
     fn=convert,
     allow_flagging='auto',
     inputs=[
+        gr.Textbox(label="Enter your access code", placeholder=""),
         gr.Textbox(label="Enter your IUPAC name", placeholder="Enter IUPAC name here"),
     ],
     outputs=[gr.Text(label="IUPAC style")],
     examples=[
-        ["propan-2-yl 2-[4-(4-chlorophenyl)carbonylphenoxy]-2-methyl-propanoate"]
+        [None, "propan-2-yl 2-[4-(4-chlorophenyl)carbonylphenoxy]-2-methyl-propanoate"]
     ],
 )

interfaces/smiles2iupac.py

@@ -1,7 +1,9 @@
 import gradio as gr
-from utils import ChemicalConverter, validate_smiles2iupac, plot_mol
+from utils import ChemicalConverter, validate_smiles2iupac, plot_mol, login
 
-def convert(chemical_name, style, validate, plot):
+def convert(access_code, chemical_name, style, validate, plot):
+    if not login(access_code.replace(" ", "")):
+        return "Currently, you don't have access to the service.", None, None
     # Initialize the ChemicalConverter
     converter = ChemicalConverter(mode="SMILES2IUPAC")
     converted_name = ""
@@ -19,6 +21,7 @@ smiles2iupac = gr.Interface(
     fn=convert,
     allow_flagging='auto',
     inputs=[
+        gr.Textbox(label="Enter your access code", placeholder=""),
         gr.Textbox(label="Enter your SMILES name", placeholder="Enter your SMILES name here"),
         gr.Radio(
             choices=["BASE", "SYSTEMATIC", "TRADITIONAL"],
@@ -31,6 +34,6 @@ smiles2iupac = gr.Interface(
              gr.Text(label="Input-Target similarity score"),
              gr.Image(type='pil', label="Molecule Plot", height=170, width=890)],
     examples=[
-        ["CCO", "BASE", True, True]
+        [None, "CCO", "BASE", True, True]
     ],
 )

materials/introduction.html

@@ -3,7 +3,7 @@
 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>ChemicalConverters App Description</title>
+    <title>ChemConverters App Description</title>
     <style>
         body {
             font-family: Arial, sans-serif;
@@ -29,7 +29,7 @@
             background-color: #c0dcfc;
         }
         .link-button img {
-            height: 30px;
+            height: 20px;
             width: auto;
             display: block;
         }
@@ -50,8 +50,8 @@
         <li>Choose your preferred IUPAC naming style: BASE, SYSTEMATIC, or TRADITIONAL 📚</li>
         <li>Validate chemical naming with molecules fingerprints similarity for accuracy checks ✔️</li>
     </ol>
-    <h3>What is ChemicalConverters?</h3>
-    <p>ChemConverters serves as a foundational showcase of our technological capabilities within the chemical domain. The models deployed in this application represent our entry-level offerings, designed to provide a glimpse into the potential applications of our advanced solutions. For access to our comprehensive suite of larger and more precise models, we invite interested parties to engage directly with us. Developed by the brilliant minds at Knowladgator, this app showcases the abilities of our chemical transformer models. Whether you're working on a research project, studying for an exam, or just exploring the chemical universe, ChemicalConverters is your go-to tool 🛠.<p>
+    <h3>What is ChemConverters?</h3>
+    <p>ChemicalConverters serves as a foundational showcase of our technological capabilities within the chemical domain. The models deployed in this application represent our entry-level offerings, designed to provide a glimpse into the potential applications of our advanced solutions. For access to our comprehensive suite of larger and more precise models, we invite interested parties to engage directly with us. Developed by the brilliant minds at Knowledgator, this app showcases the abilities of our chemical transformer models. Whether you're working on a research project, studying for an exam, or just exploring the chemical universe, ChemicalConverters is your go-to tool 🛠.<p>
     <h3>Models Availability</h3>
     <p>All models used in the applications are available on <a href="https://huggingface.co/knowledgator/" target="_blank">our Hugging Face page</a>. For translating from SMILES to IUPAC, the <a href="https://huggingface.co/knowledgator/SMILES2IUPAC-canonical-base" target="_blank">knowledgator/SMILES2IUPAC-canonical-base</a> model was used. To translate from IUPAC to SMILES, the <a href="https://huggingface.co/knowledgator/IUPAC2SMILES-canonical-base" target="_blank">knowledgator/IUPAC2SMILES-canonical-base</a> model was used.</p>
     <h3>Citation</h3>
@@ -61,7 +61,10 @@
     <div class="links-container">
         <a href="https://www.knowledgator.com/" class="link-button" target="_blank"><img src="https://assets-global.website-files.com/65902be8ba48a05dfdb73331/6590476fcc8e8f35b2332781_Group%201000002504%20(1).png" alt="Visit our website"></a>
         <a href="https://www.linkedin.com/company/knowledgator/" class="link-button" target="_blank"><img src="https://www.edigitalagency.com.au/wp-content/uploads/Linkedin-logo-png.png" alt="Follow on LinkedIn"></a>
-        <a href="https://huggingface.co/knowledgator/" class="link-button" target="_blank"><img src="https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo-with-title.png" alt="Hugging Face Profile"></a>
+        <a href="https://huggingface.co/knowledgator/" class="link-button" target="_blank"><img src="https://vectorseek.com/wp-content/uploads/2023/12/Hugging-Face-Logo-Vector.svg-.png" alt="Hugging Face Profile"></a>
+        <a href="https://twitter.com/knowledgator" class="link-button" target="_blank"><img src="https://freepnglogo.com/images/all_img/1691832278twitter-x-logo-png.png" alt="Follow on X"></a>
+        <a href="https://discord.com/invite/dkyeAgs9DG" class="link-button" target="_blank"><img src="https://assets-global.website-files.com/6257adef93867e50d84d30e2/636e0b52aa9e99b832574a53_full_logo_blurple_RGB.png" alt="Join our Discord"></a>
+        <a href="https://blog.knowledgator.com/" class="link-button" target="_blank"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/0/0d/Medium_%28website%29_logo.svg/2560px-Medium_%28website%29_logo.svg.png" alt="Follow on Medium"></a>
     </div>
 </body>
 </html>

models/SMILES2IUPAC/config.json

@@ -10,7 +10,7 @@
   "decoder_vocab_size": 822,
   "dense_act_fn": "gelu_new",
   "dropout_rate": 0.1,
-  "encoder_vocab_size": 137,
+  "encoder_vocab_size": 138,
   "eos_token_id": 1,
   "feed_forward_proj": "gated-gelu",
   "initializer_factor": 1.0,

models/SMILES2IUPAC/model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4307a50d6b192a06bb81552d7cd6bcf6ac7ea6bb21d72ca4755e28d7d28655d2
-size 23878608
+oid sha256:28bed3f7c72ae8201fad8175b253ea29891394cf5482c111f06b18d61dd77d5c
+size 23879632

utils/__init__.py

@@ -1,2 +1,3 @@
 from .main_model import ChemicalConverter
-from .rdkit_utils import validate_smiles2iupac, plot_mol
+from .rdkit_utils import validate_smiles2iupac, plot_mol
+from .login import login

utils/login.py

@@ -0,0 +1,16 @@
+import hashlib
+
+def hash_password(access_code):
+    """Hash a password for storing."""
+    sha256 = hashlib.sha256()
+    sha256.update(access_code.encode('utf-8'))
+    return sha256.hexdigest()
+
+
+def login(access_code):
+    hashed_code = hash_password(access_code)
+    with open("hashed_codes.txt") as file:
+        for line in file:
+            if hashed_code in line:
+                return True
+    return False