base skeleton

.gitignore

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+/.ipynb_checkpoints/
+/.idea/
+

app.py

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+import gradio as gr
+
+# Import your meal planning API or logic here
+from meal_planner_api import create_meal_plan  # Replace with your actual API or logic
+
+
+def generate_meal_plan(parameters):
+    # Call your API or logic to generate the meal plan based on the parameters
+    meal_plan = create_meal_plan.generate(parameters)
+    return meal_plan
+
+
+# Define input elements for user input
+inputs = [
+    gr.Textbox(lines=5,
+               placeholder="Enter your personal information (age, gender, weight, height, activity level, dietary "
+                           "preferences, allergies)"),
+    gr.Textbox(lines=4, placeholder="Enter your health goals (weight loss, muscle gain, health markers)"),
+    gr.Textbox(lines=3, placeholder="Enter your food preferences (likes, dislikes, cuisines)"),
+    gr.Textbox(lines=2, placeholder="Enter meal frequency and timing"),
+    gr.Textbox(lines=2, placeholder="Enter cooking skills and preferences"),
+    gr.Textbox(lines=1, placeholder="Enter your budget for groceries"),
+]
+
+# Define output elements to display the meal plan
+outputs = [
+    gr.Textbox(label="Generated Meal Plan"),
+]
+
+# Launch the Gradio app
+interface = gr.Interface(
+    fn=generate_meal_plan,
+    inputs=inputs,
+    outputs=outputs,
+    title="Personalized Meal Plan Generator",
+    description="Get a customized meal plan tailored to your needs and preferences.",
+)
+interface.launch()

meal_planner_api/connect_llm_api.py

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+import utils
+import google.generativeai as genai
+import os
+
+
+def generate_content(text: str):
+    GOOGLE_API_KEY = 'AIzaSyA2siKQix1_QLHi9jq6NH3MnO-wQR4zzMU'
+    model = connect()
+    response = model.generate_content(text)
+    return utils.to_markdown(response.text)
+
+
+def connect():
+    API_KEY = os.environ.get("GENAI_API_KEY")
+    genai.configure(api_key=API_KEY)
+    model = genai.GenerativeModel('gemini-pro')
+    return model
+
+

meal_planner_api/create_meal_plan.py

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+def generate(parameters):
+    """Generates a meal plan based on user-provided parameters."""
+
+    # 1. Extract relevant information from user input
+    age = parameters["age"]
+    gender = parameters["gender"]
+    weight = parameters["weight"]
+    # ... Extract other parameters
+
+    # 2. Calculate calorie and macronutrient requirements
+    daily_calories = calculate_calorie_needs(parameters)
+    macro_goals = calculate_macro_goals(parameters)
+
+    # 3. Filter recipes based on dietary preferences, allergies, and macronutrients
+    filtered_recipes = filter_recipes(recipes, parameters)
+
+    # 4. Generate meal plan structure (assign recipes to meals and days)
+    meal_plan = create_meal_schedule(filtered_recipes, daily_calories, macro_goals, parameters)
+
+    # 5. Refine meal plan based on cooking skills, time constraints, and budget
+    meal_plan = adjust_meal_plan(meal_plan, parameters)
+
+    # 6. Format meal plan output (structure as needed for Gradio app)
+    meal_plan_output = format_meal_plan(meal_plan)
+
+    return meal_plan_output

meal_planner_api/utils.py

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+import textwrap
+from IPython.display import Markdown
+
+
+def to_markdown(text):
+    text = text.replace('•', '  *')
+    return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))

mealplanner.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "07f0c4f3-7770-46b1-b22b-ccfc9588ea81",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import gradio as gr\n",
+    "from meal_planner_api import create_meal_plan\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3639a70f-8b97-456a-b31c-541086435fa6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def greet(name):\n",
+    "    return \"Hello \" + name + \"!\"\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "6d7091f8-3882-438c-b2c8-b1d57296772f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7864\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7864/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#demo = gr.Interface(fn=greet, inputs=\"text\", outputs=\"text\")\n",
+    "\n",
+    "demo = gr.Interface(\n",
+    "    fn=greet,\n",
+    "    inputs=gr.Textbox(lines=2, placeholder=\"Name Here...\"),\n",
+    "    outputs=\"text\",\n",
+    ")\n",
+    "\n",
+    "    \n",
+    "if __name__ == \"__main__\":\n",
+    "    demo.launch()\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "734a2cc4-a78a-40b5-a712-b3d2e314e1db",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}