Update app.py

app.py

@@ -1,17 +1,13 @@
 import gradio as gr
-from pydantic import BaseModel
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 tokenizer = AutoTokenizer.from_pretrained("mrm8488/flan-t5-small-finetuned-samsum")
 
 model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/flan-t5-small-finetuned-samsum")
 
-class Input(BaseModel):
-    text: str
 
-    
-def predict_sentiment(input: Input, words):
-    input_ids = tokenizer(input.text, return_tensors="pt").input_ids 
+def predict_sentiment(input, words):
+    input_ids = tokenizer(input, return_tensors="pt").input_ids 
     outputs = model.generate(input_ids, max_length=words)
     decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return f"{decoded_output}"
@@ -19,6 +15,6 @@ def predict_sentiment(input: Input, words):
 conversation = gr.Textbox(lines=2, placeholder="Conversations Here...")
 
 
-iface = gr.Interface(fn=predict_sentiment, inputs=[Input(text=conversation), gr.Slider(10, 100)], outputs="text")
+iface = gr.Interface(fn=predict_sentiment, inputs=[conversation, gr.Slider(10, 100)], outputs="text")
 
 iface.launch()