Create App.py

App.py

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+import gradio as gr
+import pandas as pd
+
+# Load food data CSV
+df = pd.read_csv("food_data_extended.csv")
+
+# Lowercase for consistent matching
+df["food"] = df["food"].str.lower()
+
+def analyze_foods(input_text):
+    input_items = [item.strip().lower() for item in input_text.split(",")]
+
+    matched = df[df["food"].isin(input_items)]
+
+    if matched.empty:
+        return "❌ Koi bhi food item match nahi hua. Dobara try karein."
+
+    result = ""
+    for _, row in matched.iterrows():
+        result += (
+            f"🍽️ **{row['food'].title()}**\n"
+            f"  🔹 Calories: {row['calories']} kcal\n"
+            f"  🔹 Protein: {row['protein']} g\n"
+            f"  🔹 Carbs: {row['carbs']} g\n"
+            f"  🔹 Fat: {row['fat']} g\n\n"
+        )
+    return result
+
+title = "🥗 NutriTrack AI - Food Nutrient Analyzer"
+description = "Kisi bhi food item ka naam likhein (1 ya zyada, comma se alag karein) aur iske calories, protein, carbs aur fat ka accurate data paayein. Example: `egg, milk, rice`"
+
+iface = gr.Interface(
+    fn=analyze_foods,
+    inputs=gr.Textbox(lines=2, placeholder="e.g. egg, chicken, rice"),
+    outputs=gr.Markdown(),
+    title=title,
+    description=description,
+    allow_flagging="never"
+)
+
+iface.launch()