Update app.py

app.py

@@ -4,27 +4,26 @@ import streamlit as st
 from transformers import pipeline
 from dotenv import load_dotenv
 from langchain import PromptTemplate, HuggingFaceHub, LLMChain
+import requests
 
 if Path(".env").is_file():
     load_dotenv(".env")
 st.set_page_config(layout="wide")
-HF_TOKEN = os.getenv("HF_TOKEN")
+HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
 def img2Text(url):
     image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
-    text = image_to_text(url)
+    text = image_to_text(url)[0]["generated_text"]
     st.subheader("Caption :")
     st.subheader(text)
-    print(text)
     return text
-img2Text("photo.png")
+img2Text("photo.jpg")
 
 #llm
 def generate_story(scenario):
     template = """
     You are a story teller;
     You can generate a short story based on a simple narrative, the story should be no momre than 20 words;
-
     CONTEXT: {scenario}
     STORY:
     """
@@ -39,4 +38,6 @@ def generate_story(scenario):
     st.subheader(story)
     print(story)
     return story
-    
+
+scenario = img2Text("photo.jpg")
+story = generate_story(scenario)