Implementatation de async

requirements.txt

@@ -34,3 +34,4 @@ https://files.pythonhosted.org/packages/cc/58/96aff0e5cb8b59c06232ea7e249ed902d0
 streamlit-option-menu==0.3.12
 deep-translator==1.11.4
 requests==2.27.0
+asyncio

tabs/modelisation_seq2seq_tab.py

@@ -24,6 +24,7 @@ from gtts import gTTS
 from extra_streamlit_components import tab_bar, TabBarItemData
 from translate_app import tr
 import requests
+import asyncio
 
 title = "Traduction Sequence à Sequence"
 sidebar_name = "Traduction Seq2Seq"
@@ -272,7 +273,7 @@ n1 = 0
 df_data_en, df_data_fr, translation_en_fr, translation_fr_en, lang_classifier, model_speech, rnn_en_fr, rnn_fr_en,\
     transformer_en_fr, transformer_fr_en, finetuned_translation_en_fr = load_all_data() 
 
-
+'''
 def display_translation(n1, Lang,model_type):
     global df_data_src, df_data_tgt, placeholder
     
@@ -302,6 +303,41 @@ def display_translation(n1, Lang,model_type):
     with placeholder:
         st.write("<p style='text-align:center;background-color:red; color:white')>Score Bleu = "+str(int(round(corpus_bleu(s_trad,[s_trad_ref]).score,0)))+"%</p>", \
             unsafe_allow_html=True)
+'''
+def display_translation(n1, Lang,model_type):
+    global df_data_src, df_data_tgt, placeholder
+    
+    async def decode_seq_all(model_type,s, source, target):
+        for i in range(3):      
+            params = {"lang_tgt": target, "texte": s[i]}
+            if model_type==1:
+                # URL de votre endpoint FastAPI avec les paramètres de requête
+                url = "https://demosthene-or-api-avr23-cds-translation.hf.space/small_vocab/rnn"
+            else:
+                # URL de votre endpoint FastAPI avec les paramètres de requête
+                url = "https://demosthene-or-api-avr23-cds-translation.hf.space/small_vocab/transformer"
+
+            # Envoie d'une requête GET avec les paramètres de requête
+            s_trad.append(requests.get(url, params=params).json())
+        await (len(s_trad) == 3)
+        return s_trad
+            
+    placeholder = st.empty()
+    with st.status(":sunglasses:", expanded=True):
+        s = df_data_src.iloc[n1:n1+5][0].tolist()
+        s_trad = []
+        s_trad_ref = df_data_tgt.iloc[n1:n1+5][0].tolist()
+        source = Lang[:2]
+        target = Lang[-2:]
+        s_trad = decode_seq_all(model_type,s, source, target)
+        for i in range(3):
+            st.write("**"+source+"   :**  :blue["+ s[i]+"]")
+            st.write("**"+target+"   :**  "+s_trad[-1])
+            st.write("**ref. :** "+s_trad_ref[i])
+            st.write("")
+    with placeholder:
+        st.write("<p style='text-align:center;background-color:red; color:white')>Score Bleu = "+str(int(round(corpus_bleu(s_trad,[s_trad_ref]).score,0)))+"%</p>", \
+            unsafe_allow_html=True)
         
 @st.cache_data        
 def find_lang_label(lang_sel):