Update app.py

app.py

@@ -1,24 +1,88 @@
 import streamlit as st
 import requests
 import os
+from dotenv import load_dotenv
 
-# Important: Use localhost because they are in the same container
-BACKEND_URL = "http://127.0.0.1:8000/process-resume"
+load_dotenv()
 
-st.title("📄 Resume Parser")
+# Configuration
+# Defaults to localhost for dev, but can be overridden in production (e.g., Docker)
+BACKEND_URL = os.getenv("BACKEND_URL", "http://127.0.0.1:8000/process-resume")
 
-uploaded_file = st.file_uploader("Upload PDF", type="pdf")
+st.set_page_config(page_title="AI Resume Analyzer", page_icon="📄", layout="centered")
+
+st.title("📄 Intelligent Resume Parser")
+st.markdown("---")
+st.write("Upload a professional resume in PDF format to extract key insights using AI.")
+
+# Sidebar for status
+with st.sidebar:
+    st.info(f"Connected to Backend: `{BACKEND_URL}`")
+
+uploaded_file = st.file_uploader("Upload PDF Resume", type="pdf")
 
 if uploaded_file:
-    if st.button("Analyze"):
-        with st.spinner("Processing..."):
-            try:
-                files = {"file": (uploaded_file.name, uploaded_file.getvalue(), "application/pdf")}
-                response = requests.post(BACKEND_URL, files=files, timeout=30)
-                
-                if response.status_code == 200:
-                    st.json(response.json())
-                else:
-                    st.error(f"Error: {response.text}")
-            except Exception as e:
-                st.error(f"Connection Error: {e}")
+    # Basic Frontend Validation
+    if uploaded_file.size > 5 * 1024 * 1024:
+        st.error("File is too large! Please upload a file smaller than 5MB.")
+    else:
+        if st.button("Analyze Resume", type="primary"):
+            with st.spinner("Processing with AI..."):
+                try:
+                    files = {
+                        "file": (uploaded_file.name, uploaded_file.getvalue(), "application/pdf")
+                    }
+                    
+                    # Set a timeout to prevent hanging
+                    response = requests.post(BACKEND_URL, files=files, timeout=30)
+
+                    if response.status_code == 200:
+                        data = response.json()
+                        
+                        # Handle case where AI returns an error key
+                        if "error" in data:
+                            st.error(data["error"])
+                        else:
+                            st.success("Extraction Complete!")
+                            
+                            # Summary Section
+                            st.markdown("### 📝 Professional Summary")
+                            st.info(data.get('summary', 'No summary available.'))
+
+                            # Contact Info
+                            st.markdown("### 📇 Contact Details")
+                            c1, c2, c3 = st.columns(3)
+                            c1.metric("Name", data.get('name', 'N/A'))
+                            c2.metric("Email", data.get('email', 'N/A'))
+                            c3.metric("Phone", data.get('phone', 'N/A'))
+
+                            # Skills Section
+                            st.markdown("### 🛠 Technical Skills")
+                            skills = data.get('skills', [])
+                            if skills and isinstance(skills, list):
+                                # CSS styling for tags
+                                st.markdown(
+                                    f"""
+                                    <div style="display: flex; flex-wrap: wrap; gap: 10px;">
+                                        {''.join([f'<span style="background-color: #e0f2f1; color: #00695c; padding: 5px 10px; border-radius: 15px; font-size: 14px;">{skill}</span>' for skill in skills])}
+                                    </div>
+                                    """,
+                                    unsafe_allow_html=True
+                                )
+                            else:
+                                st.write("No specific skills detected.")
+
+                            with st.expander("View Raw JSON Data"):
+                                st.json(data)
+                                
+                    elif response.status_code == 413:
+                        st.error("The file is too large for the server to process.")
+                    else:
+                        st.error(f"Server Error: {response.status_code} - {response.text}")
+
+                except requests.exceptions.ConnectionError:
+                    st.error("🚨 Connection Failed: Could not reach the backend server.")
+                except requests.exceptions.Timeout:
+                    st.error("🚨 Request Timed Out: The AI took too long to respond.")
+                except Exception as e:
+                    st.error(f"An unexpected error occurred: {e}")