Multiple language support added.

app.py

@@ -40,11 +40,11 @@ def detect_lang(sequence, labels):
                   lbl_lang))
 
     if seq_lang in models:
-        print("Sequence Language detected:",
+        print("Sequence Language detected.",
               "Date:{}, Sequence:{}, Sequence Language:{}".format(
                   str(datetime.datetime.now()),
                   sequence,
-                  labels))
+                  seq_lang))
     else:
         print("Language not supported. Defaulting to English!",
               "Date:{}, Sequence:{}, Sequence Language:{}".format(
@@ -61,9 +61,9 @@ def sequence_to_classify(sequence, labels):
 
     lang = detect_lang(sequence, labels)
     classifier = pipeline("zero-shot-classification",
-                          #hypothesis_template=hypothesis_templates[lang],
+                          hypothesis_template=hypothesis_templates[lang],
                           model=models[lang])
-    response = classifier(sequence, label_clean, multi_class=True)
+    response = classifier(sequence, label_clean, multi_label=True)
 
     predicted_labels = response['labels']
     predicted_scores = response['scores']
@@ -75,10 +75,17 @@ def sequence_to_classify(sequence, labels):
 
     return clean_output
 
-example_text1="Folkehelseinstituttets mest optimistiske anslag er at alle voksne er ferdigvaksinert innen midten av september."
-example_labels1="politikk,helse,sport,religion"
-example_text2="Kutt smør i terninger, og la det temperere seg litt mens deigen elter. Ha hvetemel, sukker, gjær, salt og kardemomme i en bakebolle til kjøkkenmaskin. Bruker du fersk gjær kan du smuldre gjæren i bollen, eller røre den ut i melken. Alt vil ettehvert blande seg godt, så begge deler er like bra."
-example_labels2="helse,sport,religion, mat"
+example_text1 = "Climate change refers to long-term shifts in temperatures and weather patterns. \
+These shifts may be natural, but since the 1800s, human activities have been the main driver of climate change, \
+primarily due to the burning of fossil fuels (like coal, oil, and gas), which produces heat-trapping gases."
+example_labels1="business,nature,religion"
+example_text2="Ja, vi elsker dette landet,\
+som det stiger frem,\
+furet, værbitt over vannet,\
+med de tusen hjem.\
+Og som fedres kamp har hevet\
+det av nød til seir"\
+example_labels2="helse,sport,religion,mat,patriotisme og nasjonalisme"
 
 iface = gr.Interface(
     title="Multilingual Multi-label Zero-shot Classification",
@@ -89,7 +96,7 @@ iface = gr.Interface(
         placeholder="Text here..."),
         gr.inputs.Textbox(lines=5,
         label="Possible candidate labels (separated by comma)...",
-        placeholder="laLels here...")],
+        placeholder="Labels here separated by comma...")],
     outputs=gr.outputs.Label(num_top_classes=5),
     capture_session=True,
     #interpretation="default",