Update app.py

app.py

@@ -4,10 +4,10 @@ from transformers import pipeline
 from gtts import gTTS
 import os
 
-# Function to convert image to text using Hugging Face's vit-gpt2-image-captioning model
+# Function to convert image to text using Hugging Face's BLIP model
 def img2text(url):
     """
-    Converts an image to text using the nlpconnect/vit-gpt2-image-captioning model.
+    Converts an image to text using the Salesforce/blip-image-captioning-base model.
     
     Args:
         url (str): Path to the image file.
@@ -15,7 +15,7 @@ def img2text(url):
     Returns:
         str: Generated text caption from the image, without words like "illustration".
     """
-    image_to_text_model = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
+    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
     text = image_to_text_model(url)[0]["generated_text"]
     
     # Remove unwanted words like "illustration"
@@ -28,7 +28,7 @@ def img2text(url):
 # Function to generate a kid-friendly story from the text caption
 def text2story(text):
     """
-    Generates a kid-friendly story from the text caption using the aspis/gpt2-genre-story-generation model.
+    Generates a kid-friendly story from the text caption using the pranavpsv/gpt2-genre-story-generator model.
     
     Args:
         text (str): Text caption generated from the image.
@@ -40,15 +40,15 @@ def text2story(text):
     prompt = f"Write a kids story based on below scenario :{text}."
     
     # Load the text generation model
-    story_generator = pipeline("text-generation", model="aspis/gpt2-genre-story-generation")
+    story_generator = pipeline("text-generation", model="pranavpsv/gpt2-genre-story-generator")
     
     # Generate the story
-    story = story_generator(prompt, max_length=150, num_return_sequences=1, temperature=0.7)[0]["generated_text"]
+    story = story_generator(prompt, max_length=150, num_return_sequences=1)[0]["generated_text"]
     
     # Remove the prompt from the generated story
     story = story.replace(prompt, "").strip()
     
-    # Ensure the story is within 95 words
+    # Ensure the story is within 100 words
     story_words = story.split()
     if len(story_words) > 100:
         story = " ".join(story_words[:100])