Update app.py

app.py

@@ -1,22 +1,18 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Load the model
-model_name = "ychafiqui/whisper-medium-darija"
-transcriber = pipeline("automatic-speech-recognition", model=model_name)
+# Charger le modèle et le tokenizer
+model_name = "jondurbin/airoboros-gpt-3.5-turbo-100k-7b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-def transcribe_audio(audio):
-    transcription = transcriber(audio)
-    return transcription['text']
-
-# Gradio interface
-iface = gr.Interface(
-    fn=transcribe_audio,
-    
-    inputs=gr.Audio(type="filepath"),
-    outputs="text",
-    title="Darija Audio Transcription",
-    description="Upload an audio file in Darija to get the transcription."
-)
+# Fonction pour générer des réponses
+def generate_response(input_text):
+    inputs = tokenizer.encode(input_text, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=150)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
 
+# Interface Gradio
+iface = gr.Interface(fn=generate_response, inputs="text", outputs="text", title="GPT-3.5 Turbo Chatbot")
 iface.launch()