Update app.py

app.py

@@ -1,25 +1,6 @@
-import os
-import io
 import openai
 import gradio as gr
 
-import IPython.display
-from PIL import Image
-
-import base64 
-from dotenv import load_dotenv, find_dotenv
-_ = load_dotenv(find_dotenv()) # read local .env file
-hf_api_key ='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'
-
-import requests
-
-def query(payload):
-	response = requests.post(API_URL, headers=headers, json=payload)
-	return response.content
-
-# Helper function
-import requests, json
-
 openai.api_key = "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"  
 
 def predict(message, history):
@@ -50,11 +31,12 @@ A1 = gr.ChatInterface(predict,
                 clear_btn="Clear")
 
 A2 = gr.load(
-             "huggingface/google/vit-base-patch16-224",
-              title="Upon Further Review - AI Vision and Identity Technology",
+             "huggingface/Salesforce/blip-image-captioning-large",
+              title="Upon Further Review...",
+              description="Upload or Take a Photo Image, I'll Give You Description",
               theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime"))
 
 A3 = gr.load("huggingface/google/vit-base-patch16-224")
 
-pcp = gr.TabbedInterface([A1, A2], ["Chat", "Describe", "Create"], theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime"))
+pcp = gr.TabbedInterface([A1, A2], ["Chat",  "Vision"], theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime"))
 pcp.queue().launch()