Update app.py

app.py

@@ -1,23 +1,21 @@
 import gradio as gr
-#from transformers import AutoProcessor, BlipForConditionalGeneration
+from transformers import AutoProcessor, BlipForConditionalGeneration
 from langchain_core.chat_history import InMemoryChatMessageHistory
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.messages import HumanMessage
 from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_groq import ChatGroq
 import os
-import tempfile
-import requests
+
 # Load BLIP model and processor
 #processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
 #model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
 
-HF_T2 = os.getenv("HF_T2")
-HF_TOK=f"Bearer {HF_T2}"
 
+import requests
 
 API_URL = "https://api-inference.huggingface.co/models/Salesforce/blip2-opt-2.7b"
-headers = {"Authorization": HF_TOK}
+headers = {"Authorization": "Bearer hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
 
 def query(filename):
     with open(filename, "rb") as f:
@@ -28,7 +26,9 @@ def query(filename):
 
 # Define the image description function
 def image_description(image):
-    return query(image)
+    inputs = processor(images=image, return_tensors="pt")
+    out = model.generate(**inputs)
+    return processor.decode(out[0], skip_special_tokens=True)
 
 # Define the problem categorization function
 def problem_categorization(problem_description):
@@ -149,17 +149,15 @@ chain = prompt | chat_model
 # Function to handle Gradio inputs
 def handle_input(image, text, session_id):
     if image:
-        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as temp_file:
-                image.save(temp_file.name)
-                temp_filename = temp_file.name
-        image_desc=image_description(temp_filename)
+        # Handle image input
+        image_desc = image_description(image)
         category = problem_categorization(image_desc)
         if category=='NA':
             response="Please upload a better image"
         else:
             response=f"Your request has been forwarded to the {category} department"
-        if text:
-            response+=f"With the description: {text}"       
+            if text:
+                response+=f"With the description: {text}"
     else:
         # Handle text input
         if text=='':