Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import pandas as pd
 from graph_utils import *
+from transformers import pipeline
 
 languages = pd.read_csv("model_lang.csv", names=["Lang_acr"])
 
@@ -68,14 +69,15 @@ examples_re = [
 ]
 
 interface_words = gr.Interface(
-            fn=check_lang,
-            inputs="text", 
-            outputs="text",
-            title=title,
-            description=description_main,
-            examples=[["en"], ["it"], ["pl"]],
+        fn=check_lang,
+        inputs="text", 
+        outputs="text",
+        title=title,
+        description=description_main,
+        examples=[["en"], ["it"], ["pl"]],
+        cache_examples=True,
 )
-
+    
 # interface_model_L = gr.Interface(
 #             description=description_L,
 #             examples=examples,
@@ -83,12 +85,18 @@ interface_words = gr.Interface(
 # )
 # interface_model_L.load("models/DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence")
 
+pipe_S = pipeline("text2text-generation", model="DReAMy-lib/t5-base-DreamBank-Generation-Emot-Char")
+def predict(text):
+  return pipe_S(text)
+interface_model_S =  gr.Interface(
+        fn=pipe_S,
+        inputs='text',
+        outputs='labels',
+        examples=examples[0],
+        title="SA Base English-Only",
+        cache_examples=True,
 
-# interface_model_S = gr.Interface.load(
-#             "models/DReAMy-lib/bert-base-cased-DreamBank-emotion-presence",
-#             examples=examples[0],
-#             title="SA Base English-Only",
-# )
+)
 
 # interface_model_G = gr.Interface.load(
 #             "models/DReAMy-lib/t5-base-DreamBank-Generation-Emot-Char",
@@ -117,6 +125,6 @@ interface_model_RE = gr.Interface(
 # )
 
 gr.TabbedInterface(
-    [interface_words, interface_model_RE], 
-    ["Main", "RE"],
+    [interface_words, interface_model_S, interface_model_RE], 
+    ["Main", "SA English", "RE"],
 ).launch()