Upload app.py

app.py

@@ -3,7 +3,7 @@ from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
 from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
 from clarifai_grpc.grpc.api.status import status_code_pb2
 
-# Set your Clarifai credentials and model details for GPT-4 Vision
+# Set your Clarifai credentials and model details for NewsGuardian model
 PAT_GPT4 = '3ca5bd8b0f2244eb8d0e4b2838fc3cf1'
 USER_ID_GPT4 = 'openai'
 APP_ID_GPT4 = 'chat-completion'
@@ -54,14 +54,14 @@ image_upload = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
 
 # Button to generate result
 if st.button("NewsGuardian News Result"):
-    if model_type == "GPT-4 Vision":
-        # Set up gRPC channel for GPT-4 Vision
+    if model_type == "NewsGuardian model":
+        # Set up gRPC channel for NewsGuardian model
         channel_gpt4 = ClarifaiChannel.get_grpc_channel()
         stub_gpt4 = service_pb2_grpc.V2Stub(channel_gpt4)
         metadata_gpt4 = (('authorization', 'Key ' + PAT_GPT4),)
         userDataObject_gpt4 = resources_pb2.UserAppIDSet(user_id=USER_ID_GPT4, app_id=APP_ID_GPT4)
 
-        # Prepare the request for GPT-4 Vision
+        # Prepare the request for NewsGuardian model
         input_data_gpt4 = resources_pb2.Data()
 
         if raw_text:
@@ -81,16 +81,16 @@ if st.button("NewsGuardian News Result"):
             metadata=metadata_gpt4  # Use metadata directly in the gRPC request
         )
 
-        # Check if the request was successful for GPT-4 Vision
+        # Check if the request was successful for NewsGuardian model
         if post_model_outputs_response_gpt4.status.code != status_code_pb2.SUCCESS:
-            st.error(f"GPT-4 Vision API request failed: {post_model_outputs_response_gpt4.status.description}")
+            st.error(f"NewsGuardian model API request failed: {post_model_outputs_response_gpt4.status.description}")
         else:
-            # Get the output for GPT-4 Vision
+            # Get the output for NewsGuardian model
             output_gpt4 = post_model_outputs_response_gpt4.outputs[0].data
 
-            # Display the result for GPT-4 Vision
+            # Display the result for NewsGuardian model
             if output_gpt4.HasField("image"):
-                st.image(output_gpt4.image.base64, caption='Generated Image (GPT-4 Vision)', use_column_width=True)
+                st.image(output_gpt4.image.base64, caption='Generated Image (NewsGuardian model)', use_column_width=True)
             elif output_gpt4.HasField("text"):
                 # Display the text result
                 st.text(output_gpt4.text.raw)