Update app.py

app.py

@@ -2,14 +2,14 @@ import streamlit as st
 from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 
 def img2text(url):
-    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
     text = image_to_text_model(url)[0]["generated_text"]
     return text
 
 def text2story(text):
-    story_generator = pipeline("text-generation", model="perplexity-ai/r1-1776", trust_remote_code=True)
-    prompt = [{"role": "user", "content": f"Create a short story under 100 words based on: {text}"}]
-    generated = story_generator(prompt, max_length=100)
+    story_generator = pipeline("text2text-generation", model="google/flan-t5-xl")
+    prompt = f"Create a short story under 100 words based on: {text}"}
+    generated = story_generator(prompt)
     story_text = generated[0]['generated_text']
     return story_text