Update app.py

app.py

@@ -1,9 +1,67 @@
+import gradio as gr
+from PIL import Image
+import os
+from dotenv import load_dotenv
+from simple_salesforce import Salesforce
 from datetime import datetime
+import hashlib
+import shutil
+import base64
 import pytz
 
+# Load environment variables
+load_dotenv()
+SF_USERNAME = os.getenv("SF_USERNAME")
+SF_PASSWORD = os.getenv("SF_PASSWORD")
+SF_SECURITY_TOKEN = os.getenv("SF_SECURITY_TOKEN")
+
+# Validate Salesforce credentials
+if not all([SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN]):
+    raise ValueError("Missing Salesforce credentials. Set SF_USERNAME, SF_PASSWORD, and SF_SECURITY_TOKEN in environment variables.")
+
+# Initialize Salesforce connection
+try:
+    sf = Salesforce(
+        username=SF_USERNAME,
+        password=SF_PASSWORD,
+        security_token=SF_SECURITY_TOKEN,
+        domain='login'
+    )
+except Exception as e:
+    print(f"Salesforce connection failed: {str(e)}")
+    raise
+
+# Valid milestones
+VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
+
 # Adjust the timezone to your local timezone (replace 'Asia/Kolkata' with your timezone if needed)
 local_timezone = pytz.timezone("Asia/Kolkata")
 
+# Deterministic AI prediction with fixed confidence and percent
+def mock_ai_model(image):
+    img = image.convert("RGB")
+    max_size = 1024
+    img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
+
+    img_bytes = img.tobytes()
+    img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
+
+    milestone_index = img_hash % len(VALID_MILESTONES)
+    milestone = VALID_MILESTONES[milestone_index]
+
+    milestone_completion_map = {
+        "Planning": 10,
+        "Foundation": 30,
+        "Walls Erected": 50,
+        "Completed": 100,
+    }
+    completion_percent = milestone_completion_map.get(milestone, 0)
+
+    confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
+    confidence_score = round(confidence_raw, 2)
+
+    return milestone, completion_percent, confidence_score
+
 # Image processing and Salesforce upload
 def process_image(image, project_name):
     try:
@@ -50,7 +108,7 @@ def process_image(image, project_name):
         milestone, percent_complete, confidence_score = mock_ai_model(img)
 
         # Adjust the current time to local timezone
-        local_time = datetime.now(local_timezone).strftime("%Y-%m-%dT%H:%M:%SZ")  # Updated format for Salesforce
+        local_time = datetime.now(local_timezone).strftime("%Y-%m-%dT%H:%M:%SZ")  # Correct ISO 8601 format for Salesforce
 
         # Create the Salesforce record with the image URL and AI prediction
         record = {
@@ -79,3 +137,25 @@ def process_image(image, project_name):
 
     except Exception as e:
         return f"Error: {str(e)}", "Failure", "", "", 0
+
+# Gradio UI
+with gr.Blocks(css=".gradio-container {background-color: #f0f4f8; font-family: Arial;} .title {color: #2c3e50; font-size: 24px; text-align: center;}") as demo:
+    gr.Markdown("<h1 class='title'>Construction Milestone Detector</h1>")
+    with gr.Row():
+        image_input = gr.Image(type="filepath", label="Upload Construction Site Photo (JPG/PNG, ≤ 20MB)")
+        project_name_input = gr.Textbox(label="Project Name (Required)", placeholder="e.g. Project_12345")
+
+    submit_button = gr.Button("Process Image")
+    output_text = gr.Textbox(label="Result")
+    upload_status = gr.Textbox(label="Upload Status")
+    milestone = gr.Textbox(label="Detected Milestone")
+    confidence = gr.Textbox(label="Confidence Score")
+    progress = gr.Slider(0, 100, label="Completion Percentage", interactive=False, value=0)
+
+    submit_button.click(
+        fn=process_image,
+        inputs=[image_input, project_name_input],
+        outputs=[output_text, upload_status, milestone, confidence, progress]
+    )
+
+demo.launch(share=True)