Update app.py

app.py

@@ -3,7 +3,7 @@ from pathlib import Path
 import streamlit as st
 from transformers import pipeline
 from dotenv import load_dotenv
-
+from langchain import PromptTemplate, LLNChain, OpenAI
 if Path(".env").is_file():
     load_dotenv(".env")
 st.set_page_config(layout="wide")
@@ -12,7 +12,30 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 def img2Text(url):
     image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
     text = image_to_text(url)
+    st.header("Caption :")
     st.subheader(text)
     print(text)
     return text
-img2Text(test-photo.png)
+img2Text(test-photo.png)
+
+#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 mmomre than 20 words;
+
+    CONTEXT: {scenario}
+    STORY:
+    """
+
+    prompt = PromptTemplate(template=template,input_variables=["scenario"])
+
+    story_llm = LLMChain(llm=OpenAI(
+        model_name="gpt-3.5-turbo", temperature=1), prompt=prompt, verbose=True)
+
+    story = story_llm.predict(scenario=scenario)
+    st.header("Story :")
+    st.subheader(story)
+    print(story)
+    return story
+