Update app.py

app.py

@@ -1,96 +1,100 @@
-### Invoice extractor (modified for pet image analysis)
-
-## Importing All the modules
-import streamlit as st
-import os
-from PIL import Image
-import google.generativeai as genai
-from dotenv import load_dotenv
-
-
-# Load all environment Variables
-load_dotenv()
-
-## Configuring the api key
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-## Function to load Gemini Vison Pro Vision Model and Get response
-
-def get_gemini_response(image, prompt):
-
-  ## Loading the desired Model
-  model= genai.GenerativeModel("gemini-pro-vision")
-  response=model.generate_content([image[0],prompt])
-  return response.text
-
-## Function to extract data from Image Uploaded
-
-def input_image_setup(uploaded_file):
-  # Check if a file has been uploaded
-  if uploaded_file is not None:
-    # Read the file into bytes
-    bytes_data = uploaded_file.getvalue()
-
-    image_parts = [
-      {
-        "mime_type": uploaded_file.type,  # Get the mime type of the uploaded file
-        "data": bytes_data
-      }
-    ]
-    return image_parts
-  else:
-    raise FileNotFoundError("No file uploaded")
-
-#  Initializing our Streamlit Prompt
-
-st.set_page_config(page_title="Pet Image Analyzer")
-
-st.header("Analyze Your Pet's Image")
-
-## Removed user input for text prompt
-
-uploaded_file = st.file_uploader("Choose a pet image...", type=["jpg", "jpeg", "png","webp"])
-image = None
-
-if uploaded_file is not None:
-  image = Image.open(uploaded_file)
-  st.image(image, caption="Uploaded Image.", use_column_width=True)
-
-  ## Defining a System Prompt (pre-defined)
-  input_prompt = f"""Image: (content of the uploaded image)
-
-  Text: Analyze the image and provide the following information:
-
-  * Breed: Identify the breed of the animal in the image (if possible).
-  * Disease Detection: If the image shows a diseased area, identify the specific disease (if possible).
-  * Severity: If a disease is detected, assess the severity of the disease.
-  * Symptoms: Describe the common symptoms associated with the detected disease.
-  * Precautions: Recommend preventative measures to avoid the disease.
-
-  Give response with headings,
-  Inform the user if the image is not related to pet care.
-  """
-
-  submit = st.button("Analyze Image")
-  Disclaimer ="""**Disclaimer:** 
-
-This application uses image analysis to provide potential information about your pet's health. The results are for informational purposes only and should not be considered a replacement for professional veterinary diagnosis. 
-
-For any concerns about your pet's health, please consult a licensed veterinarian. They can conduct a thorough examination and provide personalized recommendations for your pet's well-being."""
-
-
-  if submit:
-    if image:
-      image_data = input_image_setup(uploaded_file)
-      response = get_gemini_response(image_data, input_prompt)
-
-      st.subheader("Analysis Result:")
-      st.write(response)
-      st.warning(Disclaimer)
-    else:
-      st.error("Please upload an image to proceed.")
-
-else:
-  st.info("Upload an image of your pet to get started!")
-  
-# st.balloons()
+### Invoice extractor (modified for pet image analysis)
+
+## Importing All the modules
+import streamlit as st
+import os
+from PIL import Image
+import google.generativeai as genai
+from dotenv import load_dotenv
+
+
+# Load all environment Variables
+load_dotenv()
+
+## Configuring the api key
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+## Function to load Gemini Vison Pro Vision Model and Get response
+
+def get_gemini_response(image, prompt):
+
+  ## Loading the desired Model
+  model= genai.GenerativeModel("gemini-pro-vision")
+  response=model.generate_content([image[0],prompt])
+  return response.text
+
+## Function to extract data from Image Uploaded
+
+def input_image_setup(uploaded_file):
+  # Check if a file has been uploaded
+  if uploaded_file is not None:
+    # Read the file into bytes
+    bytes_data = uploaded_file.getvalue()
+
+    image_parts = [
+      {
+        "mime_type": uploaded_file.type,  # Get the mime type of the uploaded file
+        "data": bytes_data
+      }
+    ]
+    return image_parts
+  else:
+    raise FileNotFoundError("No file uploaded")
+
+#  Initializing our Streamlit Prompt
+
+st.set_page_config(page_title="Pet Image Analyzer")
+
+st.header("Analyze Your Pet's Image")
+
+## Removed user input for text prompt
+
+uploaded_file = st.file_uploader("Choose a pet image...", type=["jpg", "jpeg", "png","webp"])
+image = None
+
+if uploaded_file is not None:
+  image = Image.open(uploaded_file)
+  st.image(image, caption="Uploaded Image.", use_column_width=True)
+
+  ## Defining a System Prompt (pre-defined)
+  input_prompt = f"""Image: (content of the uploaded image)
+  
+
+  Text: Analyze the image and provide the following information:
+
+  If the uploaded image is not related to Pets then give them a Applogise message but dont give any improper respones.
+
+  * Breed: Identify the breed of the animal in the image (if possible).
+  * Disease Detection: If the image shows a diseased area, identify the specific disease (if possible).
+  * Severity: If a disease is detected, assess the severity of the disease.
+  * Symptoms: Describe the common symptoms associated with the detected disease.
+  * Precautions: Recommend preventative measures to avoid the disease.
+
+  Give response with headings, 
+  Give the response in proper format with the headings.
+  Inform the user if the image is not related to pet care.
+  """
+
+  submit = st.button("Analyze Image")
+  Disclaimer ="""**Disclaimer:** 
+
+This application uses image analysis to provide potential information about your pet's health. The results are for informational purposes only and should not be considered a replacement for professional veterinary diagnosis. 
+
+For any concerns about your pet's health, please consult a licensed veterinarian. They can conduct a thorough examination and provide personalized recommendations for your pet's well-being."""
+
+
+  if submit:
+    if image:
+      image_data = input_image_setup(uploaded_file)
+      response = get_gemini_response(image_data, input_prompt)
+
+      st.subheader("Analysis Result:")
+      st.write(response)
+      st.warning(Disclaimer)
+    else:
+      st.error("Please upload an image to proceed.")
+
+else:
+  st.info("Upload an image of your pet to get started!")
+  
+# st.balloons()