Update app.py

app.py

@@ -17,7 +17,7 @@ API_KEY = os.getenv("API_KEY")
 BRAIN_TUMOR_API_URL = "https://api-inference.huggingface.co/models/Devarshi/Brain_Tumor_Classification"
 BREAST_CANCER_API_URL = "https://api-inference.huggingface.co/models/MUmairAB/Breast_Cancer_Detector"
 ALZHEIMER_API_URL = "https://api-inference.huggingface.co/models/AhmadHakami/alzheimer-image-classification-google-vit-base-patch16"
-headers = {"Authorization": "Bearer "+ API_KEY+"", 'Content-Type': 'application/json'}
+headers = {"Authorization": "Bearer "+API_KEY+"", 'Content-Type': 'application/json'}
 
 
 # Create a function to Detect/Classify Alzheimer
@@ -32,7 +32,7 @@ def classify_alzheimer(image):
     return result
 
 
-# Create a function to Detect/Classify Breast Cancer
+# Create a function to Detect/Classify Breast_Cancer
 def classify_breast_cancer(image):
     image_data = np.array(image, dtype=np.uint8)
     _, buffer = cv2.imencode('.jpg', image_data)
@@ -44,7 +44,7 @@ def classify_breast_cancer(image):
     return result
 
 
-# Create a function to Detect/Classify Brain Tumor
+# Create a function to Detect/Classify Brain_Tumor
 def classify_brain_tumor(image):
     image_data = np.array(image, dtype=np.uint8)
     _, buffer = cv2.imencode('.jpg', image_data)
@@ -65,15 +65,18 @@ with gr.Blocks(theme=theme) as Alzheimer:
             image = gr.Image()
             output = gr.Label(label='Alzheimer Classification', container=True, scale=2)
             with gr.Row():
-                button = gr.Button(value="Submit", variant="primary")
                 gr.ClearButton([image, output])
+                button = gr.Button(value="Submit", variant="primary")
+            gr.Examples(inputs=image, fn=classify_alzheimer, examples=[os.path.join(os.path.dirname(__file__), "diseases/Alzheimer/mild_12.jpg"),
+                                                                       os.path.join(os.path.dirname(__file__), "diseases/Alzheimer/moderate_21.jpg"),
+                                                                       os.path.join(os.path.dirname(__file__), "diseases/Alzheimer/verymild_1013.jpg")])
 
         button.click(classify_alzheimer, [image], [output])
 
         def respond(message, history):
             bot_message = g4f.ChatCompletion.create(
                 model="gpt-3.5-turbo",
-                provider=g4f.Provider.GptGo,
+                provider=g4f.Provider.You,
                 messages=[{"role": "user",
                            "content": "Your role is Alzheimer Disease Expert. Now I will provide you with the user query. First check if the user query is related to Alzheimer or not. If it is not related to Alzheimer then do not reply the query whereas if related to Alzheimer reply it as usual. Here's the user Query:" + message}],
             )
@@ -84,7 +87,7 @@ with gr.Blocks(theme=theme) as Alzheimer:
         with gr.Column():
             gr.Markdown("# Health Bot for Alzheimer")
             gr.Markdown("> **Note:** The information may not be accurate. Please consult a Doctor before considering any actions.")
-            gr.ChatInterface(respond, autofocus=False).queue()
+            gr.ChatInterface(respond, autofocus=False, examples=["Explain Alzhiemer diasease.", "What are the types of Alzhiemer diasease?", "Alzhiemer Prevention methods."]).queue()
 
 
 with gr.Blocks(theme=theme) as BreastCancer:
@@ -95,25 +98,30 @@ with gr.Blocks(theme=theme) as BreastCancer:
             image = gr.Image()
             output = gr.Label(label='Breast Cancer Classification', container=True, scale=2)
             with gr.Row():
-                button = gr.Button(value="Classify")
+                button = gr.Button(value="Submit", variant="primary")
                 gr.ClearButton([image, output])
+            gr.Examples(inputs=image, fn=classify_breast_cancer,
+                        examples=[os.path.join(os.path.dirname(__file__), "diseases/Breast_Cancer/class0.png"),
+                                  os.path.join(os.path.dirname(__file__), "diseases/Breast_Cancer/class0_1.png"),
+                                  os.path.join(os.path.dirname(__file__), "diseases/Breast_Cancer/class1.png"),
+                                  os.path.join(os.path.dirname(__file__), "diseases/Breast_Cancer/class1_1.png")])
 
         button.click(classify_breast_cancer, [image], [output])
 
         def respond(message, history):
             bot_message = g4f.ChatCompletion.create(
                 model="gpt-3.5-turbo",
-                provider=g4f.Provider.GptGo,
+                provider=g4f.Provider.You,
                 messages=[{"role": "user",
-                           "content": "Your role is Breast Cancer Disease Expert. Now I will provide you with the user query. First check if the user query is related to Breast Cancer or not. If it is not related to Breast Cancer then do not reply the query whereas if related to Breast Cancer reply it as usual. Here's the user Query:" + message}],
+                           "content": "Your role is Breast_Cancer Disease Expert. Now I will provide you with the user query. First check if the user query is related to Breast_Cancer or not. If it is not related to Breast_Cancer then do not reply the query whereas if related to Breast_Cancer reply it as usual. Here's the user Query:" + message}],
             )
             time.sleep(1)
-            return str(bot_message)
+            yield str(bot_message)
 
         with gr.Column():
             gr.Markdown("# Health Bot for Breast Cancer")
             gr.Markdown("> **Note:** The information may not be accurate. Please consult a Doctor before considering any actions.")
-            gr.ChatInterface(respond, autofocus=False).queue()
+            gr.ChatInterface(respond, autofocus=False, examples=["Explain Breast Cancer.", "What are the types of Breast Cancer?", "Breast Cancer Prevention methods."]).queue()
 
 
 with gr.Blocks(theme=theme) as BrainTumor:
@@ -122,10 +130,15 @@ with gr.Blocks(theme=theme) as BrainTumor:
             gr.Markdown("# Brain Tumor Detection and Classification")
             gr.Markdown("> Classify the Brain Tumor.")
             image = gr.Image()
-            output = gr.Label(label='Brain Tumor Classification', container=True, scale=2)
+            output = gr.Label(label='Brain_Tumor Classification', container=True, scale=2)
             with gr.Row():
-                button = gr.Button(value="Classify")
+                button = gr.Button(value="Submit", variant="primary")
                 gr.ClearButton([image, output])
+            gr.Examples(inputs=image, fn=classify_brain_tumor,
+                    examples=[os.path.join(os.path.dirname(__file__), "diseases/Brain_Tumor/glioma.jpg"),
+                              os.path.join(os.path.dirname(__file__), "diseases/Brain_Tumor/meningioma.jpg"),
+                              os.path.join(os.path.dirname(__file__), "diseases/Brain_Tumor/no_tumor.jpg"),
+                              os.path.join(os.path.dirname(__file__), "diseases/Brain_Tumor/pituitary.jpg")])
 
         button.click(classify_brain_tumor, [image], [output])
 
@@ -142,11 +155,11 @@ with gr.Blocks(theme=theme) as BrainTumor:
         with gr.Column():
             gr.Markdown("# Health Bot for Brain Tumor")
             gr.Markdown("> **Note:** The information may not be accurate. Please consult a Doctor before considering any actions.")
-            gr.ChatInterface(respond, autofocus=False, examples=["Explain Brain Tumor."]).queue()
+            gr.ChatInterface(respond, autofocus=False, examples=["Explain Brain Tumor.", "What are the types of Brain Tumor?", "Brain Tumor Prevention methods."]).queue()
 
 
 Main = gr.TabbedInterface([Alzheimer, BreastCancer, BrainTumor], ["Alzheimer", "Breast Cancer", "Brain Tumor"],
                           theme=theme,
-                          css=".gradio-container {  background: rgba(255, 255, 255, 0.2) !important; box-shadow: 0 8px 32px 0 rgba( 31, 38, 135, 0.37 ) !important !important; backdrop-filter: blur( 10px ) !important; -webkit-backdrop-filter: blur( 10px ) !important; border-radius: 10px !important; border: 1px solid rgba( 255, 255, 255, 0.18 ) !important;}")
+                          css=".gradio-container {  background: rgba(255, 255, 255, 0.2) !important; box-shadow: 0 8px 32px 0 rgba( 31, 38, 135, 0.37 ) !important; backdrop-filter: blur( 10px ) !important; -webkit-backdrop-filter: blur( 10px ) !important; border-radius: 10px !important; border: 1px solid rgba( 0, 0, 0, 0.5 ) !important;}")
 
-Main.launch()
+Main.launch()