Update app.py

app.py

@@ -1,10 +1,52 @@
-import streamlit as st 
-from langchain_openai import ChatOpenAI 
-from langchain_core.prompts import ChatPromptTemplate
+import streamlit as st
+from PIL import Image
+import base64
 import os
+from langchain.llms import OpenAI
+from langchain.prompts import ChatPromptTemplate
 
-os.environ["OPENAI_API_KEY"] = os.getenv["k1"]
-st.title("Image Caption Generator :frame_with_picture:")
+# Set up environment variable for OpenAI API key
+os.environ["OPENAI_API_KEY"] = os.getenv("k1")
 
-file_uploader = st.file_uploader(label = "Upload a file")
+# Initialize OpenAI with LangChain
+llm = OpenAI(api_key=os.environ["OPENAI_API_KEY"], model="gpt-3.5-turbo", temperature=0)
 
+# Prompt template for image captioning
+caption_template = """
+You are an expert image captioner. Given an image in base64 format, provide a descriptive caption for the image.
+
+Image (base64): {image_base64}
+
+Caption:
+"""
+
+prompt = ChatPromptTemplate.from_messages([("system", caption_template)])
+
+def generate_caption(image):
+    # Convert the image to base64
+    buffered = BytesIO()
+    image.save(buffered, format="JPEG")
+    img_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
+    
+    # Create the prompt
+    formatted_prompt = prompt.format(image_base64=img_base64)
+    
+    # Generate the caption using OpenAI
+    response = llm(formatted_prompt)
+    
+    return response.choices[0].text.strip()
+
+# Streamlit UI
+st.title("Image Captioning Application :robot_face:")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image.", use_column_width=True)
+    
+    if st.button("Generate Caption"):
+        with st.spinner("Generating caption..."):
+            caption = generate_caption(image)
+            st.write("Caption: ")
+            st.write(caption)