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app.py

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+#import streamlit as st
+#from PIL import Image
+#from recipe_model import predict_dish, generate_recipe
+
+#st.set_page_config(page_title="AI Recipe Chef", layout="centered", page_icon="🍳")
+#st.title("👨‍🍳 AI Recipe Chef")
+#st.write("Upload any food image and get a real AI-generated recipe with filters.")
+#st.markdown(
+ #   "<h1 style='text-align: center; color: #F63366;'>👨‍🍳 AI Recipe Chef</h1>",
+  #  unsafe_allow_html=True
+#)
+#st.markdown("<p style='text-align: center;'>Upload a food image and get a personalized recipe with filters!</p>", unsafe_allow_html=True)
+#uploaded_image = st.file_uploader("Upload food image", type=["jpg", "jpeg", "png"])
+#st.sidebar.title("🔍History")
+#diet = st.selectbox("Dietary Preference", [
+ #   "Any", "Vegetarian", "Non-Vegetarian", "Keto", "Gluten-Free", "Paleo"])
+
+#cuisine = st.selectbox("Cuisine", ["Any","Indian", "Chinese", "Italian", "Mexican", "Meditarrean"])
+#cook_time = st.selectbox("Cook Time", ["Any","<15 mins", "15-30 mins", ">30 mins","1 hour"])
+
+#if uploaded_image:
+ #   st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
+ #   with st.spinner("Detecting dish..."):
+ #       dish = predict_dish(uploaded_image)
+ #   st.success(f"Detected Dish: {dish}")
+
+#  with st.spinner("Generating recipe..."):
+ #       import time
+ #       time.sleep(0.8)  
+ #       recipe = generate_recipe(dish, diet, cuisine, cook_time)
+        
+ #   st.subheader("📋 Ingredients & Instructions")
+ #   st.markdown(recipe, unsafe_allow_html=True)
+from __future__ import annotations
+import streamlit as st
+from PIL import Image
+from typing import Dict, List
+
+
+
+# ---------------- Dummy backend ----------------
+def generate_recipes(img: Image.Image, filters: Dict[str, str]) -> List[Dict]:
+    """Return hard-coded recipes; swap with real model later."""
+    return [
+        {
+            "title": "Cheesy Veg Sandwich",
+            "diet": filters["diet"],
+            "cuisine": filters["cuisine"],
+            "cook_time": filters["cook_time"],
+            "ingredients": [
+                "2 bread slices",
+                "1 slice cheese",
+                "Chopped tomato",
+                "Chopped onion",
+                "Butter",
+            ],
+            "instructions": [
+                "Spread butter on bread.",
+                "Add cheese and veggies.",
+                "Grill or toast till golden.",
+                "Serve hot with ketchup.",
+            ],
+        },
+        {
+            "title": "Quick Egg Fried Rice",
+            "diet": filters["diet"],
+            "cuisine": "Chinese",
+            "cook_time": "<30 min",
+            "ingredients": [
+                "1 cup cooked rice",
+                "2 eggs",
+                "Soy sauce",
+                "Chopped spring onion",
+                "Salt & pepper",
+            ],
+            "instructions": [
+                "Scramble eggs in a pan.",
+                "Add rice and soy sauce.",
+                "Mix well with veggies.",
+                "Garnish with spring onion.",
+            ],
+        },
+    ]
+
+# ---------------- UI ----------------
+def main() -> None:
+    
+    st.set_page_config(page_title="AI Recipe Generator", page_icon="🍳", layout="centered")
+    st.title("📸🍽️ AI-Powered Recipe Generator")
+
+    uploaded = st.file_uploader("Upload your fridge / pantry photo", type=["jpg", "jpeg", "png"])
+    if uploaded:
+        img = Image.open(uploaded)
+        st.image(img, caption="Uploaded image", use_column_width=True)
+
+        st.subheader("Filters")
+        col1, col2, col3 = st.columns(3)
+        with col1:
+            diet = st.selectbox("Diet", ["Any", "Vegetarian", "Vegan", "Keto", "Pescatarian", "Gluten-Free"])
+        with col2:
+            cuisine = st.selectbox("Cuisine", ["Any", "Indian", "Italian", "Mexican", "Chinese", "Mediterranean"])
+        with col3:
+            cook_time = st.selectbox("Cook time", ["Any", "<15 min", "<30 min", "<45 min", "1 hour+"])
+
+        if st.button("Generate Recipes", type="primary"):
+            with st.spinner("Chef-bot is thinking…"):
+                recs = generate_recipes(img, {"diet": diet, "cuisine": cuisine, "cook_time": cook_time})
+
+            if not recs:
+                st.warning("No recipes found — try relaxing a filter.")
+            else:
+                st.success(f"{len(recs)} recipe{'s' if len(recs)>1 else ''} found!")
+                show_recipes(recs)
+
+        if st.session_state.get("favourites"):
+            st.divider()
+            st.subheader("⭐ Saved favourites")
+            show_recipes(st.session_state["favourites"], favourite=True)
+    else:
+        st.info("👆 Upload an image to start.")
+
+def show_recipes(recs: List[Dict], favourite: bool = False) -> None:
+    for i, r in enumerate(recs):
+        with st.expander(f"🍽️  {r['title']}"):
+            c1, c2, c3 = st.columns([2, 1, 1])
+            with c1:
+                st.markdown(f"**Diet:** {r['diet']}")
+                st.markdown(f"**Cuisine:** {r['cuisine']}")
+                st.markdown(f"**Time:** {r['cook_time']}")
+            with c2:
+                rating = st.slider("Rate", 1, 5, 3, key=f"rating_{i}_{favourite}")
+                st.session_state.setdefault("ratings", {})[r["title"]] = rating
+            with c3:
+                fav_key = f"fav_{i}_{favourite}"
+                if st.checkbox("❤️ Save", key=fav_key):
+                    st.session_state.setdefault("favourites", []).append(r)
+
+            st.markdown("**Ingredients**")
+            st.markdown("\n".join(f"- {ing}" for ing in r["ingredients"]))
+            st.markdown("**Instructions**")
+            st.markdown("\n".join(f"{j+1}. {step}" for j, step in enumerate(r["instructions"])))
+
+if __name__ == "__main__":
+    main()
+
+
+
+
+
+# ---------- tiny helper to colour the diet tag ----------
+def diet_badge(diet: str) -> str:
+    colors = {
+        "Vegetarian":   "#34c759",   # green
+        "Vegan":        "#0a84ff",   # blue
+        "Keto":         "#ff9f0a",   # orange
+        "Gluten-Free":  "#ff375f",   # pink
+        "Any":          "#8e8e93",   # grey
+    }
+    col = colors.get(diet, "#8e8e93")
+    return (
+        f"<span style='background:{col};color:white;"
+        "border-radius:4px;padding:2px 6px;font-size:0.85rem;'>"
+        f"{diet}</span>"
+    )
+#if file:
+ #   img = Image.open(file)
+  #  st.image(img, caption="Your Image", use_column_width=True)
+   # with st.spinner("Thinking like a chef..."):
+    #    dish = predict_dish(img)
+     #   st.success(f"Detected Dish: **{dish}**")
+      #  recipe = generate_recipe(dish, diet, cuisine, cook_time)
+      #  st.subheader("📝 Recipe:")
+      #  st.write(recipe)
+

recipe_model.py

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+from transformers import AutoProcessor, AutoModelForImageClassification, pipeline
+from PIL import Image
+import torch
+
+
+def load_classification_model():
+    processor = AutoProcessor.from_pretrained("Shresthadev403/food-image-classification")
+    model = AutoModelForImageClassification.from_pretrained("Shresthadev403/food-image-classification")
+    return processor, model
+def load_text_generator():
+    return pipeline( "text2text-generation",model="distilgpt2")
+processor, model = load_classification_model()
+text_generator = load_text_generator()
+
+
+def predict_dish(image: Image.Image):
+    try:
+        image = Image.open(image).convert("RGB")
+        inputs = processor(images=image, return_tensors="pt")
+        with torch.no_grad():
+            outputs = model(**inputs)
+            logits = outputs.logits
+            predicted_class_idx = logits.argmax(-1).item()
+            label = model.config.id2label[predicted_class_idx]
+            return label.lower().replace(" ", "_")
+    except Exception as e:
+        print(f"❌ Error in dish prediction: {e}")
+        return "unknown_dish"
+
+
+
+def generate_recipe(dish, diet=None, cuisine=None, cook_time=None):
+
+    filters = []
+    if diet and diet != "Any":
+        filters.append(f"{diet} diet")
+    if cuisine and cuisine != "Any":
+        filters.append(f"{cuisine} cuisine")
+    if cook_time and cook_time != "Any":
+        filters.append(f"ready in {cook_time}")
+        filter_text = ", ".join(filters)
+    
+    prompt = f"""
+    Create a step-by-step recipe for {dish}.
+    Include:
+    - Ingredients with quantities
+    - Step-by-step instructions cooking steps
+    Make sure it's a {filter_text} recipe."""
+    try:
+        result = text_generator(prompt.strip(), max_length=282, do_sample=False)
+        return result[0]['generated_text']
+    except Exception as e:
+        print(f"❌ Error generating recipe: {e}")
+        return "Sorry, couldn't generate a recipe at the moment."

requirements.txt

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+streamlit
+torch
+torchvision
+transformers
+pillow