Update app.py

app.py

@@ -6,7 +6,17 @@ from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 import numpy as np
 pipe=pipeline('sentiment-analysis')
-text=st.text_area('ecrivez votre requete')
+
+text = """
+Welcome to SorboBot, a Hugging Face Space designed to revolutionize the way you find published articles.
+
+Powered by a full export from ScanR and Hal at Sorbonne University, SorboBot utilizes advanced language model technology to provide you with a list of published articles based on your prompt
+
+Work in progress
+
+Write your request:
+"""
+text=st.text_area(text)
 
 
 if text:
@@ -35,19 +45,20 @@ if text:
     
     # Affichage des titres d'articles trouvés
     if resultats:
-        st.write("Titres d'articles correspondant à votre recherche :")
+        st.write("Titles of articles corresponding to your search:")
         for row in resultats[:3]:
             st.json(row[0])
     else:
-        st.json("Aucun article trouvé pour les mots-clés spécifiés.")
+        st.json("No artcicles found in the database")
     
     
     conn.close()
     generator = pipeline("text-generation", model="gpt2") # to modify for another model
-    txt=generator(
+    txt = generator(
         text,
         max_length=150,
         num_return_sequences=2,
     )
 
+    st.write("\n\n")
     st.write(txt)