Update app.py

app.py

@@ -1,100 +1,82 @@
 import streamlit as st
 import os
 from groq import Groq
+import re
 
-# --- Load Groq API Key ---
+# Set your Groq API key
 GROQ_API_KEY = os.getenv("GROQ_API_KEY", "your_groq_api_key_here")
 client = Groq(api_key=GROQ_API_KEY)
 
-# --- Cute Stickers ---
-stickers = [
-    "https://media.giphy.com/media/3o6Zt481isNVuQI1l6/giphy.gif",
-    "https://media.giphy.com/media/l3q2XB76CaWPcSspC/giphy.gif",
-    "https://media.giphy.com/media/ICOgUNjpvO0PC/giphy.gif",
-    "https://media.giphy.com/media/26BRuo6sLetdllPAQ/giphy.gif"
-]
+# Emoji-based section colors
+section_colors = {
+    "🌟": "#3B82F6",  # Greeting
+    "🩺": "#10B981",  # Skin Issue
+    "🧴": "#F59E0B",  # Routine
+    "📷": "#8B5CF6",  # Image
+    "💡": "#EF4444",  # Advice
+}
 
-# --- Title ---
-st.title("💆‍♀️ SkinSense AI - Your Skincare Assistant")
+# Title
+st.title("💆 SkinSense AI – Your Skincare Helper")
 
-# --- Sidebar Input ---
-with st.sidebar:
-    st.header("📝 User Info")
-    name = st.text_input("Your Name")
-    gender = st.selectbox("Gender", ["Female", "Male", "Other"])
-    age = st.slider("Age", 10, 80, 25)
-    skin_concern = st.selectbox("Main Skin Concern", [
-        "Acne", "Dryness", "Oiliness", "Dark Spots", "Redness", "Wrinkles", "Dullness", "Other"
-    ])
-    description = st.text_area("Describe your skin condition (symptoms, triggers, etc.)")
-    duration = st.text_input("How long has this been happening?")
-    sensitivity = st.radio("Skin Sensitivity?", ["Yes", "No"])
-    routine = st.text_area("Current Skincare Routine (if any)")
-    image = st.file_uploader("Optional: Upload a photo of your skin (jpg/png)", type=["jpg", "png"])
+# Input fields
+name = st.text_input("Enter your name")
+gender = st.radio("Select your gender", ["Female", "Male", "Other"])
+age = st.slider("Select your age", 10, 60, 25)
+skin_concern = st.selectbox("Primary Skin Concern", ["Acne", "Dark Spots", "Dryness", "Oiliness", "Wrinkles"])
+description = st.text_area("Describe your skin concern")
+duration = st.selectbox("How long have you had this concern?", ["Less than 1 month", "1-3 months", "More than 3 months"])
+sensitivity = st.radio("Is your skin sensitive?", ["Yes", "No"])
+routine = st.text_area("Describe your current skincare routine (optional)")
+image = st.file_uploader("Upload a picture (optional)", type=["jpg", "jpeg", "png"])
 
-# --- Function to get response from Groq ---
-def skincare_advice(name, gender, age, skin_concern, description, duration, sensitivity, routine, image=None):
+# Send query to Groq
+def skincare_advice(name, gender, age, concern, description, duration, sensitivity, routine, image):
     prompt = f"""
-You are a skincare expert chatbot. A user named {name}, a {gender}, aged {age}, has the following skin concern: {skin_concern}.
-They described the issue as: {description}. The issue has been happening for: {duration}.
-Sensitive skin: {sensitivity}. Current routine: {routine}.
-Provide a friendly and professional skin analysis, possible causes, and a step-by-step personalized skincare routine.
-Include emojis to make it friendly. Use headings like "🌟 Greeting", "🩺 Skin Issue Summary", "📊 Possible Causes", "🧴 Skincare Routine", "🌿 Natural Remedies", "💡 Tips", "💬 Final Note".
-Don't recommend medicines.
-"""
-    completion = client.chat.completions.create(
-        model="llama3-8b-8192",
-        messages=[
-            {"role": "system", "content": "You are a friendly and expert skincare assistant."},
-            {"role": "user", "content": prompt}
-        ]
-    )
-    return completion.choices[0].message.content
-
-# --- Generate Button ---
-if st.button("✨ Get My Skincare Plan"):
-    with st.spinner("Analyzing your skin profile..."):
-        raw = skincare_advice(name, gender, age, skin_concern, description, duration, sensitivity, routine, image)
-
-        # --- Parse and Beautify Output ---
-        lines = raw.strip().split("\n")
-        html_output = ""
-        section_colors = {
-            "🌟": "#E53935", "🩺": "#D81B60", "📊": "#5E35B1",
-            "🧴": "#F57C00", "🌿": "#43A047", "💡": "#039BE5", "💬": "#6D4C41"
-        }
+You are a professional skincare assistant. Based on the following details, provide a personalized skincare advice in a friendly tone:
 
-        current_section = None
-        section_title = ""
-        section_buffer = []
+- Name: {name}
+- Gender: {gender}
+- Age: {age}
+- Concern: {concern}
+- Description: {description}
+- Duration: {duration}
+- Sensitive Skin: {sensitivity}
+- Current Routine: {routine if routine else "Not provided"}
+- Image Provided: {"Yes" if image else "No"}
 
-        for line in lines:
-            line = line.strip()
-            if not line:
-                continue
-
-            emoji = line[:2]
-            if emoji in section_colors:
-                # Flush previous section
-                if current_section:
-                    html_output += f"<h4 style='color:{section_colors[current_section]}; margin-top:20px;'>{section_title}</h4>\n"
-                    for item in section_buffer:
-                        html_output += f"<p style='margin:4px 0;'>{item}</p>\n"
-                    section_buffer = []
+Start with a short greeting, then address the concern, suggest a simple skincare routine, and provide helpful tips. Use emoji headers for each section like 🌟 Greeting, 🩺 Skin Issue, 🧴 Routine, 💡 Advice.
+"""
+    response = client.chat.completions.create(
+        model="llama3-70b-8192",
+        messages=[{"role": "user", "content": prompt}],
+        temperature=0.7,
+    )
+    return response.choices[0].message.content
 
-                current_section = emoji
-                section_title = line
-            else:
-                section_buffer.append(line)
+# Submit
+if st.button("Get Advice"):
+    if not name or not description:
+        st.warning("Please fill in your name and skin concern description.")
+    else:
+        with st.spinner("Analyzing your skin concern..."):
+            raw_response = skincare_advice(name, gender, age, skin_concern, description, duration, sensitivity, routine, image)
 
-        # Flush final section
-        if current_section:
-            html_output += f"<h4 style='color:{section_colors[current_section]}; margin-top:20px;'>{section_title}</h4>\n"
-            for item in section_buffer:
-                html_output += f"<p style='margin:4px 0;'>{item}</p>\n"
+            # Clean HTML output
+            html_output = ""
+            lines = raw_response.split("\n")
 
-        # --- Display Final HTML Output ---
-        st.markdown(html_output, unsafe_allow_html=True)
+            for line in lines:
+                # Remove all existing HTML tags from model's response
+                clean_line = re.sub(r"<.*?>", "", line.strip())
+                if not clean_line:
+                    continue
+                emoji = clean_line[:2]
+                if emoji in section_colors:
+                    color = section_colors.get(emoji, "#000")
+                    html_output += f"<h4 style='color:{color}; margin-top:20px;'>{clean_line}</h4>\n"
+                else:
+                    html_output += f"<p style='color:#111; margin:5px 0;'>{clean_line}</p>\n"
 
-        # --- Show Sticker ---
-        st.image(random.choice(stickers), use_column_width=True)
+            # Display HTML in Streamlit
+            st.markdown(html_output, unsafe_allow_html=True)