Create app.py

app.py

@@ -0,0 +1,153 @@
+!pip install google-generativeai
+!pip install gradio huggingface_hub
+
+from pathlib import Path
+import google.generativeai as genai
+import re
+from PIL import Image
+import os
+#from google.colab import userdata
+#os.environ['GOOGLE_API_KEY'] = userdata.get('GOOGLE_API_KEY')
+#GOOGLE_API_KEY = os.environ['GOOGLE_API_KEY']
+#genai.configure(api_key=os.environ["GOOGLE_API_KEY"])
+#or use this for personal notebook genai.configure(api_key="AIzaSyD----")
+
+# Configuration for our Gemini Models
+
+textgeneration_config = {
+  "temperature": 0.9,
+  "top_p": 1,
+  "top_k": 1,
+  "max_output_tokens": 2048,}
+
+
+visiongeneration_config = {
+  "temperature": 0.9,
+  "top_p": 1,
+  "top_k": 10,
+  "max_output_tokens": 1024,
+}
+
+safety_settings = [
+  {
+    "category": "HARM_CATEGORY_HARASSMENT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_HATE_SPEECH",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+]
+
+# Two models - vision and text
+textmodel = genai.GenerativeModel('gemini-1.0-pro',
+                              generation_config=textgeneration_config,
+                              safety_settings=safety_settings)
+
+#imagemodel = genai.GenerativeModel('gemini-pro-vision')
+
+visionmodel = genai.GenerativeModel(model_name="gemini-1.0-pro-vision-latest",
+                              generation_config=visiongeneration_config,
+                              safety_settings=safety_settings)
+
+
+
+# Utility Functions
+# Convert an image to base64 string format
+import base64
+def img2base64(image):
+    with open(image, 'rb') as img:
+        encoded_string = base64.b64encode(img.read())
+    return encoded_string.decode('utf-8')
+
+
+# Check image format and display user messages in GUI
+def user_inputs(history, txt, img):
+    if not img:
+        history += [(txt, None)]
+        return history
+
+    # Open the image for format verification
+    try:
+        with Image.open(img) as image:
+            # Get image format (e.g., PNG, JPEG)
+            image_format = image.format.upper()
+    except (IOError, OSError):
+        return history
+
+    if image_format not in ('JPEG','JPG','PNG'):
+        print(f"Warning: Unsupported image format: {image_format}")
+        return history
+
+    base64 = img2base64(img)
+    data_url = f"data:image/{image_format.lower()};base64,{base64}"
+    history += [(f"{txt} ![]({data_url})", None)]
+
+
+
+import gradio as gr
+
+TITLE = """<h1 align="center">Your Personal Health Coach</h1>"""
+SUBTITLE = """<h2 align="center">Upload an image of your food to knows its calories, macronutrients or ask questions about heath and exercise.</h2>"""
+DES = """
+<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
+    <span>You need to enter your FREE GEMINI KEY in the first text box to connect to Gemini Models. You can find your key here:
+        <a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>. <br><br>
+        <b> If you wish to ask a question unrelated to the image you have uploaded, just cross the image (top right corner of image) and then submit your question in the textbox.
+    </span>
+</div>
+"""
+
+def generate_model_response(api_key, history, text, img):
+  genai.configure(api_key=api_key)
+  if not img:
+        text = "You are an expert nutritionist and fitness coach. You are accurate, you always stick to the facts, and never make up new facts. \
+            For the questions asked by the user, answer accurately and to the point, in a friendly tone." + text
+        response = textmodel.generate_content(text)
+
+  else:
+        text = "From the image uploaded by the user answer with following information: Food items in the image, \
+            percentage of each macronutrient in the food in image and approximate number of calories in the food in image. If there is any additional question, answer that too." + text
+        img = Image.open(img)
+        response = visionmodel.generate_content([text,img])
+  history += [(None, response.text)]
+  return history
+
+
+with gr.Blocks() as app:
+
+  gr.HTML(TITLE)
+  gr.HTML(SUBTITLE)
+  gr.HTML(DES)
+
+  api_key_box = gr.Textbox(placeholder = "Enter your GEMINI API KEY", label="Your GEMINI API KEY", type="password")
+
+  with gr.Row():
+    image_box = gr.Image(type="filepath")
+    chatbot = gr.Chatbot(
+      scale=3,
+      height=750
+    )
+
+  text_box = gr.Textbox(
+    placeholder="Ask something about the image your uploaded or ask for any health and fitness advice without uploading an image too",
+    container=False,
+  )
+
+  btn = gr.Button("Submit")
+
+  btn_clicked = btn.click(user_inputs,
+                     [chatbot, text_box, image_box],
+                     chatbot).then(generate_model_response,[api_key_box, chatbot, text_box, image_box], chatbot)
+
+app.queue()
+app.launch(debug=True)
+