Update app.py

app.py

@@ -16,7 +16,7 @@ urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
 st.set_page_config(layout='wide')
 st.sidebar.title('🔮 GenPro2.5')
-st.sidebar.write('GenPro2 is an end-to-end protein sequence generator, structure predictor, and analysis that uses [ESMFold](https://esmatlas.com/explore?at=1%2C1%2C21.999999344348925) and the ESM-2 language model | [Potion.Bio](https://www.potion.bio)beta v2.51')
+st.sidebar.write('GenPro2.5 is an end-to-end protein sequence generator, structure predictor, and analysis that uses [ESMFold](https://esmatlas.com/explore?at=1%2C1%2C21.999999344348925) and the ESM-2 language model | beta v2.51')
 
 def generate_sequence_from_words(words, length):
     seed = ' '.join(words).encode('utf-8')
@@ -128,7 +128,7 @@ def update(sequence, word1, word2, word3, sequence_length):
         st.write("Please try again later or contact support if the issue persists.")
 
 def share_on_twitter(word1, word2, word3, length, plddt):
-    tweet_text = f"I just generated a unique protein using #GenPro2 by @WandsAI using the seed words #{word1}, #{word2}, #{word3} + sequence length of {length}. My Protein has a {plddt}% plDDT score! #PostYourProtein"
+    tweet_text = f"I just discoved a new protein using the seed words: #{word1}, #{word2}, #{word3} | generated by @PotionBio"
     tweet_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(tweet_text)}"
     return tweet_url
 
@@ -154,14 +154,12 @@ Protein Length Guide:
 - 50-100 amino acids: Small proteins/peptides
 - 100-300 amino acids: Average protein domains
 - 300-500 amino acids: Larger single-domain proteins
-
 """)
 
 st.markdown("""
 1. Start by entering any three seed words of your choice and select a sequence length in the sidebar.
 2. Click 'Generate and Predict' to generate a unique protein sequence based on your inputs.
 3. GenPro2 then predicts the 3D structure of your protein and provides a confidence score.
-
 More about GenPro2 and Proteins:  
 Your unique protein could be the key to unlocking new therapeutic possibilities or understanding disease mechanisms. Who knows? Your next generated sequence might just lead to a breakthrough. Start your journey into computational protein exploration!  [Learn more](https://www.youtube.com/watch?v=KpedmJdrTpY)
     """)
@@ -181,7 +179,7 @@ if st.sidebar.button('Generate and Predict'):
 # Display structure information if available
 if st.session_state.structure_info:
     info = st.session_state.structure_info
-    st.subheader(f'I just discovered a new protein using seed words: {info["word1"]}, {info["word2"]}, and {info["word3"]} generated by @PotionBio')
+    st.subheader(f'Predicted protein structure using seed: {info["word1"]}, {info["word2"]}, and {info["word3"]}')
     render_mol(info['pdb_string'])
     
     st.subheader('plDDT Confidence Score')
@@ -192,21 +190,20 @@ if st.session_state.structure_info:
     st.subheader("Share your unique protein on X(Twitter)")
     
     st.markdown("""
-    <div style='background-color: #000000; padding: 10px; border-radius: 5px; font-size: 0.8em;'>
+    <div style='background-color: #e6f2ff; padding: 10px; border-radius: 5px; font-size: 0.8em;'>
     <ol>
         <li>Take a screenshot of the protein structure above.</li>
-        <li>Click the 'Share Results' link below to open a pre-filled post with your proteins seed-words.</li>
-        <li>Upload your protein and post!</li>
+        <li>Click the 'Share Results' link below to open a pre-filled post with your proteins seed-words and plDDT score.</li>
+        <li>Be sure to attach a screenshot of your protein before you post!</li>
     </ol>
     </div>
     """, unsafe_allow_html=True)
     
-    tweet_url = share_on_twitter(info["word1"], info["word2"], info["word3"])
+    tweet_url = share_on_twitter(info["word1"], info["word2"], info["word3"], info["sequence_length"], plddt_score)
     st.markdown(f"[Share Results]({tweet_url})")
 
     st.markdown("""
     ## What to do next:
-
     """)
 
     col1, col2 = st.columns(2)
@@ -228,9 +225,7 @@ if st.session_state.structure_info:
     1. Click the 'analyze protein' button to search the [BLAST](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastp&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome) protein database and see if your protein matches any known sequences.  The sequence identity will show how close your sequence matches. *Note this can take several minutes
     2. Download your protein data and visit the [Protein Data Bank (PDB)](https://www.rcsb.org/) to match your protein structure against known protein structures.
     3. If you think you've discovered a unique and useful protein share it with the world on social media!
-
   
     **Remember, this folding is based on randomly generated sequences. Interpret the results with caution.
     Enjoy exploring the world of protein sequences!
-    """)
-
+    """)