Update app.py

app.py

@@ -112,18 +112,17 @@ st.info("Text-to-Pictograms traduit une phrase en français en pictogrammes ARAS
 
 sentence = st.text_input("Entrez une phrase en français:")
 with st.spinner("Affichage des pictogrammes..."):
-    if st.button('Valider'):
-        inputs = tokenizer(sentence, return_tensors="pt").input_ids
-        outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
-        pred = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    inputs = tokenizer(sentence, return_tensors="pt").input_ids
+    outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
+    pred = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-        sentence_to_map = process_output_trad(pred)
-        pictogram_ids = [get_id_picto_from_predicted_lemma(lexicon, lemma) for lemma in sentence_to_map]
+    sentence_to_map = process_output_trad(pred)
+    pictogram_ids = [get_id_picto_from_predicted_lemma(lexicon, lemma) for lemma in sentence_to_map]
 
-        html = generate_html(pictogram_ids)
-        st.components.v1.html(html, height=500, scrolling=True)
+    html = generate_html(pictogram_ids)
+    st.components.v1.html(html, height=500, scrolling=True)
 
-        # Container to hold the download button
-        pdf_path = generate_pdf(pictogram_ids)
-        with open(pdf_path, "rb") as pdf_file:
-            st.download_button(label="Télécharger la traduction en PDF", data=pdf_file, file_name="pictograms.pdf", mime="application/pdf")
+    # Container to hold the download button
+    pdf_path = generate_pdf(pictogram_ids)
+    with open(pdf_path, "rb") as pdf_file:
+        st.download_button(label="Télécharger la traduction en PDF", data=pdf_file, file_name="pictograms.pdf", mime="application/pdf")