Update app.py

app.py

@@ -1,10 +1,42 @@
 import gradio as gr
 from transformers import pipeline
+Examples_to_teach_model=f"""
+Text: I hate apples
+Sentiment analysis:
+Sentiments: Negative
+PPrint Key words: hate, aples
+Text: I enjoy watching movies
+Sentiment analysis:
+Sentiments: Positive
+PPrint Key words: enjoy, movies
+Text: I'm tired of this long process
+Sentiment analysis:
+Sentiments: Negative
+PPrint Key words: tired, long process
+"""
+question="""
+Text: I love chips.
+Sentiment analysis:
+"""
+def make_prompt(sentence):
+    prompt = Examples_to_teach_model+ "Text: " + sentence + "Sentiment analysis:"
 
-pipe = pipeline(task="image-classification", 
-                model="thuyentruong/food_classification_model")
+    return prompt
+
+def get_sentiment_from_llm(sentence):
+  input = make_prompt(sentence)
+  inputs = tokenizer(input, return_tensors='pt')
+  output = tokenizer.decode(
+    model.generate(
+        inputs["input_ids"],
+        max_new_tokens=100,
+    )[0],
+    skip_special_tokens=True)
+  return "\n".join(output.split('PPrint '))
+
+get_rules_from_llm(question)
+    
 gr.Interface.from_pipeline(pipe, 
-                           title="Food Image Classification",
-                           description="Image classification",
-                           examples = ['beignets.jpeg','spagetti.jpeg'],
+                           title="Sentiment Analysis",
+                           description="Sentiment analysis and keywords extraction.",
                            ).launch()