Upload app.py

app.py

@@ -1,16 +1,22 @@
 from transformers import pipeline
 import gradio as gr
 
-pipe = pipeline(model="khalidey/ID2223_Lab2_Whisper_SV")  # change to "your-username/the-name-you-picked"
+pipe1 = pipeline(model="khalidey/ID2223_Lab2_Whisper_SV")  # change to "your-username/the-name-you-picked"
+pipe2 = pipeline('text-generation', model='birgermoell/swedish-gpt')
 
 def transcribe(audio):
-    text = pipe(audio)["text"]
+    text = pipe1(audio)["text"]
     return text
 
+def generateText(audio):
+    text = pipe1(audio)["text"]
+    generated_text = pipe2(text, max_length = 30, num_return_sequences=1)['generated_text']
+    return generated_text
+
 iface = gr.Interface(
     fn=transcribe, 
     inputs=gr.Audio(source="microphone", type="filepath"), 
-    outputs="text",
+    outputs=["text","generated_text"],
     title="Whisper Small Swedish",
     description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.",
 )