Add recipe recommender domain demo

README.md

@@ -26,7 +26,7 @@ If you plan to run the app in a conda or virtual environment, make sure to set u
 3. Run the application with the following command:
 
     ```bash
-    streamlit run recommender.py
+    streamlit run main.py
     ```
 
 4. Once running, the app will be accessible at `localhost:8501`.
@@ -55,10 +55,30 @@ You're done! Access the app at `localhost:8501` in your browser.
 
 The recommender system works by loading a set of random video links. Once the user hits the Run button, a video will be shown, and the system will suggest whether it recommends the video or not. The user can then provide feedback using "pain" or "pleasure" signals to guide the recommendation process. Based on this feedback, the system adjusts its responses and suggests another video. This cycle continues, allowing for more accurate and personalized recommendations over time.
 
+## Recipe Domain Demo
+
+This repository also includes a recipe and meal-planning recommender domain that demonstrates how the same continuously trainable pattern can work beyond YouTube videos.
+
+The demo uses a local recipe catalog with cuisine, meal slot, cook time, difficulty, dietary tags, and meal context labels. These features are converted into binary AO inputs in `recipe_domain.py`, using the architecture in `arch__RecipeRecommender.py`.
+
+Run the recipe demo with:
+
+```bash
+streamlit run recipe_recommender.py
+```
+
+The recipe app supports a live AO Agent when `ao_core` and `ao_arch` are installed. If those private packages are unavailable during review, it falls back to a deterministic scorer so the workflow, dataset, and feature encoding can still be tested locally.
+
+Recipe-domain validation:
+
+```bash
+python3 -m unittest discover -s tests
+python3 -m py_compile recipe_domain.py recipe_recommender.py arch__RecipeRecommender.py tests/test_recipe_domain.py
+```
+
 
 ## Contributing
 
 Fork the repository, make your changes, and submit a pull request for review. 
 
 
-

arch__RecipeRecommender.py

@@ -0,0 +1,16 @@
+# -*- coding: utf-8 -*-
+"""
+AO architecture for the recipe-domain recommender demo.
+"""
+
+import ao_arch as ar
+
+description = "Recipe Recommender System"
+
+# recipe attributes plus requested meal slot, cook-time limit, dietary preference, and mood
+arch_i = [3, 2, 2, 2, 4, 2, 2, 4, 2]
+arch_z = [12]
+arch_c = []
+connector_function = "full_conn"
+
+arch = ar.Arch(arch_i, arch_z, arch_c, connector_function, description)

recipe_domain.py

@@ -0,0 +1,252 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from math import ceil, log2
+
+
+@dataclass(frozen=True)
+class Recipe:
+    title: str
+    cuisine: str
+    meal_slot: str
+    cook_time_minutes: int
+    difficulty: str
+    dietary_tags: tuple[str, ...]
+    contexts: tuple[str, ...]
+    description: str
+    ingredients: tuple[str, ...]
+
+
+@dataclass(frozen=True)
+class MealContext:
+    meal_slot: str
+    mood: str
+    max_cook_time_minutes: int
+    dietary_preference: str | None = None
+
+
+CUISINES = (
+    "american",
+    "asian",
+    "latin",
+    "mediterranean",
+    "middle_eastern",
+    "indian",
+    "bakery",
+    "global",
+)
+MEAL_SLOTS = ("breakfast", "lunch", "dinner", "snack")
+DIFFICULTIES = ("easy", "moderate", "project")
+MOODS = ("quick", "comfort", "balanced", "adventurous")
+DIETARY_FLAGS = ("vegetarian", "high_protein", "gluten_free", "dairy_free")
+
+
+RECIPE_CATALOG = (
+    Recipe(
+        title="Miso Mushroom Rice Bowl",
+        cuisine="asian",
+        meal_slot="dinner",
+        cook_time_minutes=28,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "dairy_free"),
+        contexts=("quick", "balanced"),
+        description="Savory mushrooms, greens, and miso dressing over steamed rice.",
+        ingredients=("mushrooms", "rice", "miso", "spinach", "sesame"),
+    ),
+    Recipe(
+        title="Chickpea Shawarma Wraps",
+        cuisine="middle_eastern",
+        meal_slot="lunch",
+        cook_time_minutes=24,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "dairy_free"),
+        contexts=("quick", "adventurous"),
+        description="Roasted chickpeas, cucumber, herbs, and tahini in warm flatbread.",
+        ingredients=("chickpeas", "flatbread", "tahini", "cucumber", "parsley"),
+    ),
+    Recipe(
+        title="Turkey Chili with Black Beans",
+        cuisine="american",
+        meal_slot="dinner",
+        cook_time_minutes=45,
+        difficulty="moderate",
+        dietary_tags=("high_protein", "gluten_free", "dairy_free"),
+        contexts=("comfort", "balanced"),
+        description="Weeknight chili with lean turkey, beans, tomatoes, and warm spices.",
+        ingredients=("ground turkey", "black beans", "tomatoes", "chili powder"),
+    ),
+    Recipe(
+        title="Lemon Herb Salmon Tray Bake",
+        cuisine="mediterranean",
+        meal_slot="dinner",
+        cook_time_minutes=32,
+        difficulty="easy",
+        dietary_tags=("high_protein", "gluten_free", "dairy_free"),
+        contexts=("balanced", "quick"),
+        description="Salmon, potatoes, and green beans roasted on one tray.",
+        ingredients=("salmon", "potatoes", "green beans", "lemon", "dill"),
+    ),
+    Recipe(
+        title="Sweet Potato Breakfast Hash",
+        cuisine="american",
+        meal_slot="breakfast",
+        cook_time_minutes=30,
+        difficulty="moderate",
+        dietary_tags=("gluten_free", "high_protein"),
+        contexts=("comfort", "balanced"),
+        description="Crisp sweet potatoes with peppers, onions, and eggs.",
+        ingredients=("sweet potato", "eggs", "bell pepper", "onion"),
+    ),
+    Recipe(
+        title="Mango Coconut Overnight Oats",
+        cuisine="global",
+        meal_slot="breakfast",
+        cook_time_minutes=10,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "dairy_free"),
+        contexts=("quick", "balanced"),
+        description="No-cook oats with mango, coconut milk, chia, and lime.",
+        ingredients=("oats", "mango", "coconut milk", "chia", "lime"),
+    ),
+    Recipe(
+        title="Lentil Bolognese",
+        cuisine="mediterranean",
+        meal_slot="dinner",
+        cook_time_minutes=55,
+        difficulty="moderate",
+        dietary_tags=("vegetarian", "dairy_free", "high_protein"),
+        contexts=("comfort", "balanced"),
+        description="Rich tomato lentil sauce for pasta or roasted vegetables.",
+        ingredients=("lentils", "tomatoes", "carrot", "celery", "pasta"),
+    ),
+    Recipe(
+        title="Paneer Tikka Salad",
+        cuisine="indian",
+        meal_slot="lunch",
+        cook_time_minutes=35,
+        difficulty="moderate",
+        dietary_tags=("vegetarian", "high_protein", "gluten_free"),
+        contexts=("adventurous", "balanced"),
+        description="Spiced paneer over greens with cucumber, tomato, and mint yogurt.",
+        ingredients=("paneer", "yogurt", "greens", "cucumber", "garam masala"),
+    ),
+    Recipe(
+        title="Avocado Edamame Toast",
+        cuisine="global",
+        meal_slot="snack",
+        cook_time_minutes=12,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "dairy_free", "high_protein"),
+        contexts=("quick", "balanced"),
+        description="Smashed avocado and edamame on toast with chili crisp.",
+        ingredients=("bread", "avocado", "edamame", "lime", "chili crisp"),
+    ),
+    Recipe(
+        title="Cocoa Tahini Energy Bites",
+        cuisine="bakery",
+        meal_slot="snack",
+        cook_time_minutes=18,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "gluten_free", "dairy_free"),
+        contexts=("quick", "comfort"),
+        description="No-bake bites with oats, tahini, cocoa, dates, and seeds.",
+        ingredients=("oats", "tahini", "cocoa", "dates", "sunflower seeds"),
+    ),
+    Recipe(
+        title="Black Bean Taco Skillet",
+        cuisine="latin",
+        meal_slot="dinner",
+        cook_time_minutes=25,
+        difficulty="easy",
+        dietary_tags=("vegetarian", "gluten_free", "dairy_free"),
+        contexts=("quick", "comfort"),
+        description="A single-pan taco filling with black beans, corn, and salsa.",
+        ingredients=("black beans", "corn", "salsa", "tortillas", "cilantro"),
+    ),
+    Recipe(
+        title="Saffron Chickpea Pilaf",
+        cuisine="middle_eastern",
+        meal_slot="dinner",
+        cook_time_minutes=50,
+        difficulty="project",
+        dietary_tags=("vegetarian", "gluten_free", "dairy_free"),
+        contexts=("adventurous", "comfort"),
+        description="Fragrant rice with chickpeas, herbs, raisins, and toasted nuts.",
+        ingredients=("rice", "chickpeas", "saffron", "raisins", "almonds"),
+    ),
+)
+
+
+def _option_bits(value: str, options: tuple[str, ...]) -> list[int]:
+    normalized = value.lower()
+    if normalized not in options:
+        normalized = options[-1]
+    bit_width = ceil(log2(len(options)))
+    return [int(bit) for bit in format(options.index(normalized), f"0{bit_width}b")]
+
+
+def _cook_time_bits(minutes: int) -> list[int]:
+    if minutes <= 20:
+        return [0, 0]
+    if minutes <= 35:
+        return [0, 1]
+    if minutes <= 55:
+        return [1, 0]
+    return [1, 1]
+
+
+def _dietary_preference_bits(preference: str | None) -> list[int]:
+    return [int(preference == flag) for flag in DIETARY_FLAGS]
+
+
+def encode_recipe(recipe: Recipe, context: MealContext) -> list[int]:
+    return (
+        _option_bits(recipe.cuisine, CUISINES)
+        + _option_bits(recipe.meal_slot, MEAL_SLOTS)
+        + _cook_time_bits(recipe.cook_time_minutes)
+        + _option_bits(recipe.difficulty, DIFFICULTIES)
+        + [int(flag in recipe.dietary_tags) for flag in DIETARY_FLAGS]
+        + _option_bits(context.meal_slot, MEAL_SLOTS)
+        + _cook_time_bits(context.max_cook_time_minutes)
+        + _dietary_preference_bits(context.dietary_preference)
+        + _option_bits(context.mood, MOODS)
+    )
+
+
+def score_recipe(recipe: Recipe, context: MealContext) -> int:
+    score = 0
+    if recipe.meal_slot == context.meal_slot:
+        score += 35
+    if context.mood in recipe.contexts:
+        score += 25
+    if recipe.cook_time_minutes <= context.max_cook_time_minutes:
+        score += 20
+    else:
+        score -= min(25, recipe.cook_time_minutes - context.max_cook_time_minutes)
+    if context.dietary_preference:
+        if context.dietary_preference in recipe.dietary_tags:
+            score += 20
+        else:
+            score -= 35
+    if recipe.difficulty == "easy":
+        score += 8
+    elif recipe.difficulty == "project" and context.mood != "adventurous":
+        score -= 10
+    return max(0, min(100, score))
+
+
+def recommend_recipes(
+    context: MealContext,
+    catalog: tuple[Recipe, ...] = RECIPE_CATALOG,
+    limit: int = 5,
+) -> list[tuple[Recipe, int, list[int]]]:
+    ranked = [
+        (recipe, score_recipe(recipe, context), encode_recipe(recipe, context))
+        for recipe in catalog
+    ]
+    ranked.sort(key=lambda item: (-item[1], item[0].cook_time_minutes, item[0].title))
+    return ranked[:limit]
+
+
+def feedback_label(user_liked_recipe: bool, output_size: int) -> list[int]:
+    return [1 if user_liked_recipe else 0] * output_size