Update app.py

app.py

@@ -24,7 +24,7 @@ transformers.logging.set_verbosity_error()
 
 
 
-def image_to_query(imagefile):
+def image_to_query(image):
     """
     input: Image
 
@@ -32,10 +32,14 @@ def image_to_query(imagefile):
 
     output: Query for the LLM
     """
-    #image = Image.open(imagefile)
-    classifier = pipeline("image-classification", model = "nprasad24/bean_classifier", from_tf = True)
+    image = Image.open(image)
 
-    scores = classifier(imagefile)
+    model = AutoModelForImageClassification.from_pretrained("nprasad24/bean_classifier", from_tf=True)
+    image_processor = AutoImageProcessor.from_pretrained("nprasad24/bean_classifier")
+
+    classifier = pipeline("image-classification", model=model, image_processor=image_processor)
+
+    scores = classifier(image)
 
     # Get the dictionary with the maximum score
     max_score_dict = max(scores, key=lambda x: x['score'])
@@ -84,14 +88,14 @@ def ragChain():
         [
             (
                 "system",
-                """You are a knowledgeable agricultural assistant. If a disease is detected, you have to give information on the disease. 
+                """You are a knowledgeable agricultural assistant. If a disease is detected, you have to give information on the disease.
+                If the image is not of a plant, ask human to upload image of a plant and stop generating any response.
                 If the plant is healthy, just give maintenance tips. """
             ),
             (
                 "human",
                 """Provide information about the leaf disease in question in bullet points. 
                 Start your answer by mentioning the disease (if any) or healthy in this format: 'Condition: disease name'.
-                If the image is not of a plant, ask human to upload image of a plant and stop generating any response.
                 """,
             ),
             
@@ -127,7 +131,6 @@ def main(image):
     query = image_to_query(image)
     chain = ragChain()
     output = generate_response(chain, query)
-    output = Markdown(output)
     return output
 
 title = "Bean Classifier and Instructor"