init

.dockerignore

@@ -0,0 +1,172 @@
+# copied verbatim from .gitignore, with changes ##
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+##.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+.vscode/
+codealike.json
+
+# app specific
+test_data/
+
+## for Docker
+Dockerfile
+.gitignore

.env

@@ -0,0 +1,23 @@
+######################################################################################################
+# SambaNova Hosted Models reference: https://docs.sambanova.ai/cloud/docs/get-started/supported-models
+######################################################################################################
+
+LLAMA_API_BASE_URL=https://api.sambanova.ai/v1
+
+## 1. Llama Text LLM
+LLAMA_TEXT_MODEL=Meta-Llama-3.3-70B-Instruct
+LLAMA_TEXT_MAX_TOKENS=131072
+
+## 2. Llama Vision LLM
+LLAMA_VISION_MODEL=Llama-3.2-11B-Vision-Instruct
+LLAMA_VISION_MAX_TOKENS=4096
+
+######################################################################################################
+# Nebius Hosted Models reference: https://studio.nebius.com/models/text2image
+######################################################################################################
+
+IMAGE_GEN_API_BASE_URL=https://api.studio.nebius.ai/v1
+
+## 1. Image Gen Model
+IMAGE_GEN_MODEL=black-forest-labs/flux-schnell
+IMAGE_GEN_MAX_PROMPT_LEN=2000

.env_sample

@@ -0,0 +1,25 @@
+######################################################################################################
+# SambaNova Hosted Models reference: https://docs.sambanova.ai/cloud/docs/get-started/supported-models
+######################################################################################################
+
+LLAMA_API_BASE_URL=https://api.sambanova.ai/v1
+LLAMA_API_KEY=xxx
+
+## 1. Llama Text LLM
+LLAMA_TEXT_MODEL=Meta-Llama-3.3-70B-Instruct
+LLAMA_TEXT_MAX_TOKENS=131072
+
+## 2. Llama Vision LLM
+LLAMA_VISION_MODEL=Llama-3.2-11B-Vision-Instruct
+LLAMA_VISION_MAX_TOKENS=4096
+
+######################################################################################################
+# Nebius Hosted Models reference: https://studio.nebius.com/models/text2image
+######################################################################################################
+
+IMAGE_GEN_API_BASE_URL=https://api.studio.nebius.ai/v1
+IMAGE_GEN_API_KEY=xxx
+
+## 1. Image Gen Model
+IMAGE_GEN_MODEL=black-forest-labs/flux-schnell
+IMAGE_GEN_MAX_PROMPT_LEN=2000

.gitignore

@@ -0,0 +1,169 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+env.bak/
+venv.bak/
+
+# Environments
+# .env (allow .env to be committed)
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+.vscode/
+codealike.json
+
+# app specific
+test_data/

Dockerfile

@@ -0,0 +1,22 @@
+FROM python:3.12-slim-bookworm
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Add the requirements file to the container
+ADD requirements.txt .
+
+# Install the app dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the source code into the container
+COPY . .
+
+# Set env variables
+ENV PYTHONUNBUFFERED=1
+
+RUN --mount=type=secret,id=LLAMA_API_KEY,mode=0444,required=true
+RUN --mount=type=secret,id=IMAGE_GEN_API_KEY,mode=0444,required=true
+
+# Command to run the app on container startup
+CMD ["python", "-u", "/app/gradio_ui.py"]

README.md

@@ -9,4 +9,21 @@ license: mit
 short_description: An agent which generates a new 💓health-ai💓 recipe for you!
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# HealthAI Chef
+
+An agent which generates a new 💓health-ai💓 recipe for you from just an image of a meal, based on your dietary restrictions and medical diagnoses! For example, you loved eating hamburgers before, but now you have high cholesterol and need to eat vegetarian. Upload your favorite burger photo and the chef agent will scan it using Llama 3 Vision, figure out the recipe for it, use Llama 3 Text to generate a new recipe based on your health needs, and use an image gen model to generate an appetizing picture of the new recipe for you. The agent will show you the old and new pictures and recipes side by side, and even explain what changes it made. Also, if you don't have a meal photo handy, you can use the agent's internet search feature to find one, thanks to Llama's tool calling support.
+
+## Tech Stack
+
+The agent is built in Python 3.12 using the following technologies:
+
+- Llama 3.3 70B Text Instruct hosted on SambaNova
+- Llama 3.2 11B Vision Instruct hosted on SambaNova
+- Black Forest Labs Flux Schnell Image Gen hosted on Nebius
+- LangChain
+- LangGraph
+- Gradio
+- DuckDuckGo Search
+- Jinja
+
+_Note: these are all open-source._

data/dietary_restrictions.txt

@@ -0,0 +1,14 @@
+Dairy-Free
+Egg-Free
+Gluten-Free
+Halal
+Kosher
+Low-Carb
+Low-FODMAP
+Low-Sodium
+Nut-Free
+Paleo
+Pescatarian
+Soy-Free
+Vegan
+Vegetarian

data/medical_diagnoses.txt

@@ -0,0 +1,31 @@
+Anemia
+Arthritis
+Asthma
+Celiac Disease
+Diabetes (Type 1)
+Diabetes (Type 2)
+Digestive Issues
+Diverticulitis
+Egg Allergy
+Fatty Liver Disease (NAFLD/NASH)
+Fish Allergy
+GERD (Gastroesophageal Reflux Disease)
+Gout
+Heart Disease
+High Blood Pressure
+High Cholesterol
+Hyperlipidemia
+Hypertension
+Hypothyroidism
+Kidney Stones
+Lactose Intolerance
+Milk Allergy
+Osteoporosis
+Peanut Allergy
+Prediabetes
+Renal Disease
+Shellfish Allergy
+Soy Allergy
+Tree Nut Allergy
+Underweight
+Wheat Allergy

gradio_ui.py

@@ -0,0 +1,123 @@
+import gradio as gr
+
+from jinja2 import Environment, FileSystemLoader
+
+from log_util import logger
+from meal_image_search import search_meal_image
+from recipe_generator import get_altered_recipe, get_image_from_recipe, get_recipe_from_image
+from util import yield_lines_from_file
+
+BRAND = 'HealthAI'
+TITLE = f'{BRAND} Chef'
+
+env = Environment(loader=FileSystemLoader('templates'))
+template = env.get_template('recipe.html')
+
+DISCLAIMER = 'This recipe is a healthier option <em>generated by AI</em>. A registered dietitian can provide expert dietary advice 😀'
+
+async def process_image(file):
+    if not file:
+        yield None, None
+        return
+
+    image_path = file.name
+    yield image_path, None
+
+    try:
+        recipe = await get_recipe_from_image(image_path)
+        html = template.render(recipe=recipe)
+        yield image_path, html
+
+    except Exception as e:
+        logger.error(e)
+        yield None, None
+        if 'not a meal' in str(e).lower():
+            raise gr.Error("This image doesn't contain a meal.")
+        raise gr.Error("Sorry, this image can't be processed.")
+
+async def get_new_recipe(orig_recipe: str, restrictions: list[str], diagnoses: list[str]):
+    if not orig_recipe or (not restrictions and not diagnoses):
+        yield None, None
+
+        if not orig_recipe:
+            raise gr.Error('Please upload a meal pic first.')
+
+        if not restrictions and not diagnoses:
+            raise gr.Error(
+'Please select dietary restrictions or medical diagnoses, then try again. I will give you a new recipe based on your selections!')
+
+    try:
+        recipe = await get_altered_recipe(orig_recipe, restrictions, diagnoses)
+        recipe['disclaimer'] = DISCLAIMER
+        html = template.render(recipe=recipe)
+        yield html, None
+
+    except Exception as e:
+        logger.error(e)
+        yield None, None
+        raise gr.Error(f"Sorry, a new recipe can't be made.")
+
+    try:
+        image_url = get_image_from_recipe(recipe)
+        yield html, image_url
+
+    except Exception as e:
+        logger.error(e)
+        yield html, None
+
+def search_image(search_text: str) -> str:
+    if not search_text:
+        return None
+
+    try:
+        image_url = search_meal_image(search_text)
+        if image_url:
+            return image_url
+
+    except Exception as e:
+        logger.error(e)
+
+    raise gr.Error(f"Sorry, can't find a meal pic for {search_text}.")
+
+with gr.Blocks(title=TITLE, theme=gr.themes.Monochrome(), css='''
+    footer {visibility: hidden}
+
+    /* make container full width */
+    .gradio-container {
+        width: 100% !important; /* flll width */
+        max-width: 100% !important; /* prevent max-width restriction */
+        margin: 5px 0px 5px 0px !important; /* top, right, bottom, left */
+    }
+    '''.strip()) as demo:
+
+    with gr.Row():
+        gr.Markdown(f'# {TITLE} 🍽️')
+        new_recipe_button = gr.Button(f'Get {BRAND} Recipe 😋', scale=0)
+
+    file_select = gr.File(label='Upload Meal Pic', container=True, file_types=['.jpg', '.jpeg', '.png', '.gif', '.webp'])
+
+    search_text = gr.Textbox(placeholder='Or enter a meal to search for an image of it', submit_btn=True, container=False, interactive=True, max_lines=1)
+
+    with gr.Row():
+        restrictions_dropdown = gr.Dropdown(label='Dietary Restrictions', choices=yield_lines_from_file('dietary_restrictions.txt'), interactive=True, multiselect=True, value=None)
+        diagnoses_dropdown = gr.Dropdown(label='Medical Diagnoses', choices=yield_lines_from_file('medical_diagnoses.txt'), interactive=True, multiselect=True, value=None)
+
+    with gr.Row():
+        orig_meal = gr.Image(label='Original Meal', interactive=False)
+        new_meal = gr.Image(label=f'{BRAND} Meal', interactive=False)
+
+    with gr.Row():
+        orig_recipe = gr.HTML(label='Original Recipe', container=True, show_label=True)
+        new_recipe = gr.HTML(label=f'{BRAND} Recipe', container=True, show_label=True)
+
+    search_text.submit(search_image, inputs=search_text, outputs=file_select)
+
+    file_select.change(
+        process_image,
+        inputs=file_select,
+        outputs=[orig_meal, orig_recipe]
+    )
+
+    new_recipe_button.click(fn=get_new_recipe, inputs=[orig_recipe, restrictions_dropdown, diagnoses_dropdown], outputs=[new_recipe, new_meal])
+
+demo.launch(server_name='0.0.0.0')

image_generator.py

@@ -0,0 +1,43 @@
+import os
+
+from dotenv import load_dotenv
+from langchain_core.prompts import PromptTemplate
+from openai import OpenAI
+
+from log_util import logger
+from time_it import time_it
+from util import load_prompt
+
+load_dotenv()
+
+IMAGE_GEN_API_BASE_URL = os.getenv('IMAGE_GEN_API_BASE_URL')
+IMAGE_GEN_API_KEY = os.getenv('IMAGE_GEN_API_KEY')
+
+IMAGE_GEN_MODEL = os.getenv('IMAGE_GEN_MODEL')
+IMAGE_GEN_MAX_PROMPT_LEN = int(os.getenv('IMAGE_GEN_MAX_PROMPT_LEN'))
+
+IMAGE_GEN_OPTIONS = {
+    'response_extension': 'png',
+    'width': 1024,
+    'height': 1024,
+    'num_inference_steps': int(os.getenv('NUM_INFERENCE_STEPS', '16')),
+    'negative_prompt': '',
+    'seed': -1
+}
+
+@time_it
+def generate_image(prompt_file: str, input: dict) -> str:
+    prompt = load_prompt(prompt_file)
+
+    if len(prompt) > IMAGE_GEN_MAX_PROMPT_LEN:
+        logger.info(f'Prompt length {len(prompt)} exceeds {IMAGE_GEN_MAX_PROMPT_LEN} characters, will be truncated.')
+        prompt = prompt[:IMAGE_GEN_MAX_PROMPT_LEN]
+
+    prompt_template = PromptTemplate.from_template(prompt)
+    prompt = prompt_template.invoke(input).to_string()
+
+    images_client = OpenAI(base_url=IMAGE_GEN_API_BASE_URL, api_key=IMAGE_GEN_API_KEY).images
+    response = images_client.generate(model=IMAGE_GEN_MODEL, prompt=prompt, response_format='url', extra_body=IMAGE_GEN_OPTIONS)
+    image_url = response.data[0].url
+    logger.info(f'{image_url=}')
+    return image_url

llm.py

@@ -0,0 +1,38 @@
+import os
+
+from dotenv import load_dotenv
+from langchain_openai import ChatOpenAI
+
+from log_util import logger
+from time_it import time_it_async
+
+load_dotenv()
+
+LLAMA_API_BASE_URL = os.getenv('LLAMA_API_BASE_URL')
+LLAMA_API_KEY = os.getenv('LLAMA_API_KEY')
+
+LLAMA_TEXT_MODEL = os.getenv('LLAMA_TEXT_MODEL')
+LLAMA_TEXT_MAX_TOKENS = int(os.getenv('LLAMA_TEXT_MAX_TOKENS'))
+
+LLAMA_VISION_MODEL = os.getenv('LLAMA_VISION_MODEL')
+LLAMA_VISION_MAX_TOKENS = int(os.getenv('LLAMA_VISION_MAX_TOKENS'))
+
+TEMPERATURE = float(os.getenv('TEMPERATURE', '0.2'))
+
+TOKEN_FACTOR_FOR_PROMPT = 0.75
+
+def get_text_llm() -> ChatOpenAI:
+    return _get_llm(LLAMA_TEXT_MODEL, LLAMA_TEXT_MAX_TOKENS)
+
+def get_vision_llm() -> ChatOpenAI:
+    return _get_llm(LLAMA_VISION_MODEL, LLAMA_VISION_MAX_TOKENS)
+
+def _get_llm(model: str, max_tokens: int) -> ChatOpenAI:
+    return ChatOpenAI(base_url=LLAMA_API_BASE_URL, api_key=LLAMA_API_KEY,
+                      model=model, max_tokens=int(max_tokens*TOKEN_FACTOR_FOR_PROMPT), temperature=TEMPERATURE)
+
+@time_it_async
+async def invoke_llm_async(chain, input: dict | None = {}):
+    response = await chain.ainvoke(input)
+    logger.info(f'{response=}')
+    return response

log_util.py

@@ -0,0 +1,23 @@
+import logging
+import os
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+PROJECT_NAME = 'healthai-chef'
+
+default_log_args = {
+    'level': logging.DEBUG if int(os.getenv('DEBUG', '0')) else logging.INFO,
+    'format': '%(asctime)s [%(levelname)s] %(filename)s:%(lineno)d - %(message)s',
+    'datefmt': '%d-%b-%y %H:%M:%S',
+    'force': True,
+}
+logging.basicConfig(**default_log_args)
+logger = logging.getLogger(PROJECT_NAME)
+
+# disable 3rd party logs
+LOGGERS_TO_DISABLE = [
+]
+for logger_name in LOGGERS_TO_DISABLE:
+    logging.getLogger(logger_name).setLevel(logging.CRITICAL + 1)

meal_image_search.py

@@ -0,0 +1,81 @@
+import json
+import os
+
+from dotenv import load_dotenv
+from duckduckgo_search import DDGS
+from langchain_core.messages.tool import BaseMessage, ToolMessage
+from langchain_core.prompts import PromptTemplate
+from langchain_core.tools import tool
+from langgraph.graph import END, MessageGraph
+from langgraph.prebuilt import ToolNode
+from typing import TypedDict
+
+from llm import get_text_llm
+from log_util import logger
+from time_it import time_it
+from util import load_prompt
+
+load_dotenv()
+
+MAX_IMAGE_SEARCH_RESULTS = int(os.getenv('MAX_IMAGE_SEARCH_RESULTS', '3'))
+
+class ImageSearchResult(TypedDict):
+    title: str
+    url: str
+
+@time_it
+def search_meal_image(meal: str) -> str:
+    prompt = load_prompt('validate_is_meal.prompt.txt')
+
+    llm = get_text_llm()
+    tools = [search_meal_images]
+
+    def is_meal_router(messages: list[BaseMessage]) -> str:
+        if messages[-1].content.lower() == 'yes':
+            return 'is_meal'
+        return END
+
+    graph = MessageGraph()
+    graph.add_node('validate_is_meal', llm)
+    graph.add_conditional_edges('validate_is_meal', is_meal_router)
+    graph.add_node('is_meal', llm.bind_tools(tools))
+    graph.add_edge('is_meal', 'call_tools')
+    graph.add_node('call_tools', ToolNode(tools))
+    graph.add_edge('call_tools', END)
+    graph.set_entry_point('validate_is_meal')
+
+    prompt_template = PromptTemplate.from_template(prompt)
+    prompt = prompt_template.format(phrase=meal)
+
+    workflow = graph.compile()
+    messages: list = workflow.invoke(prompt)
+    tool_messages = [message for message in messages if isinstance(message, ToolMessage)]
+    if tool_messages and tool_messages[0].content:
+        meal_images: list[ImageSearchResult] = json.loads(tool_messages[0].content)
+        if meal_images:
+            meal_image_url = meal_images[0]['url']
+            logger.info(f'{meal_image_url=}')
+            return meal_image_url
+    return None
+
+@tool
+def search_meal_images(meal: str) -> list[ImageSearchResult]:
+    '''Searches for images of the given meal.'''
+    return search_images(meal)
+
+@time_it
+def search_images(keywords: str, max_results: int | None=MAX_IMAGE_SEARCH_RESULTS) -> list[ImageSearchResult]:
+    results = DDGS().images(
+        keywords=keywords,
+        region='wt-wt',
+        safesearch='on',
+        size=None,
+        color='color',
+        type_image='photo',
+        layout=None,
+        license_image=None,
+        max_results=max_results,
+    )
+    logger.info(f'{keywords=}: {results=}')
+    results = [ImageSearchResult(title=result['title'], url=result['image']) for result in results]
+    return results

prompts/alter_recipe_for_healthier.prompt.txt

@@ -0,0 +1,29 @@
+<system>
+You are a highly experienced registered dietitian, providing evidence-based nutritional recommendations.
+</system>
+
+Human:
+
+Given the provided recipe, alter it to be appropriate for your patient with the dietary restrictions and medical diagnoses below.
+
+Return your answer of the altered recipe as a JSON object only (no comments and not an array) with these properties:
+- name (string)
+- ingredients (array of string)
+- instructions (array of string, do NOT number the instructions)
+- meal_type (string: "lunch", "dinner", or "breakfast")
+- serves (string: "individual", "couple", or "family")
+- notes (string: a description of what you changed)
+
+For each ingredient specify the quantity or amount.
+
+<recipe>
+{recipe}
+</recipe>
+
+<dietary_restrictions>
+{dietary_restrictions}
+</dietary_restrictions>
+
+<medical_diagnoses>
+{medical_diagnoses}
+</medical_diagnoses>

prompts/get_image_from_recipe.prompt.txt

@@ -0,0 +1,11 @@
+<system>
+You are an expert chef and food photographer.
+</system>
+
+Human:
+
+Given the recipe below, generate an appetizing, realistic image of the meal with no text.
+
+<recipe>
+{recipe}
+</recipe>

prompts/get_recipe_from_image.prompt.txt

@@ -0,0 +1,20 @@
+<system>
+You are a highly experienced registered dietitian, providing evidence-based nutritional recommendations.
+</system>
+
+Human:
+
+Generate a recipe from the provided image of a prepared meal.
+
+Return your answer as a JSON object only (no comments and not an array) with these properties:
+- name (string)
+- ingredients (array of string)
+- instructions (array of string, do NOT number the instructions)
+- meal_type (string: "lunch", "dinner", or "breakfast")
+- serves (string: "individual", "couple", or "family")
+
+For each ingredient specify the quantity or amount.
+
+**Do not give any instruction beginning with "Serves as" because this is a recurring bug of yours.**
+
+If the image is not a meal, return the string "Not a meal" (and do not return JSON in this case).

prompts/validate_is_meal.prompt.txt

@@ -0,0 +1,12 @@
+<system>
+You are an expert on North American cuisine.
+</system>
+
+Human:
+
+Respond "yes" or "no" whether the phrase below describes a common, well-known meal eaten at home or restaurants (including fast food) in North America.
+No justification is needed for your answer, so do not respond with any other words except "yes" or "no".
+
+<phrase>
+{phrase}
+</phrase>

recipe_generator.py

@@ -0,0 +1,76 @@
+import base64
+
+from langchain_core.messages import HumanMessage
+from langchain_core.output_parsers import JsonOutputParser
+from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
+
+from image_generator import generate_image
+from llm import get_text_llm, get_vision_llm, invoke_llm_async
+from time_it import time_it_async
+from util import UTF8_ENCODING, load_prompt
+
+async def get_recipe_from_image(image_path: str) -> dict:
+    recipe: dict = await _analyze_image_from_path(image_path, 'get_recipe_from_image.prompt.txt')
+    return recipe
+
+async def get_altered_recipe(orig_recipe: dict, restrictions: list[str], diagnoses: list[str]) -> dict:
+    recipe: dict = await _generate_text('alter_recipe_for_healthier.prompt.txt',
+                                        {'recipe': orig_recipe, 'dietary_restrictions': restrictions, 'medical_diagnoses': diagnoses})
+    if 'recipe' in recipe:
+        recipe = recipe['recipe']
+    return recipe
+
+async def _analyze_image_from_path(image_path: str, prompt_file: str) -> dict | str:
+    with open(image_path, 'rb') as image_file:
+        image_data = image_file.read()
+    image_format = _get_image_format(image_path)
+    return await _analyze_image_from_bytes(image_data, prompt_file, image_format)
+
+@time_it_async
+async def _analyze_image_from_bytes(image_data: bytes, prompt_file: str, image_format: str, output_parser_type=JsonOutputParser) -> dict | str:
+    img_base64 = base64.b64encode(image_data).decode(UTF8_ENCODING)
+    prompt = load_prompt(prompt_file)
+    prompt_template = ChatPromptTemplate.from_messages([
+        HumanMessage(
+            content=[
+                {'type': 'text', 'text': prompt},
+                {
+                    'type': 'image_url',
+                    'image_url': {
+                        'url': f'data:image/{image_format};base64,{img_base64}',
+                        'detail': 'high'
+                    }
+                }
+            ]
+        ),
+    ])
+
+    llm = get_vision_llm()
+    chain = prompt_template | llm | output_parser_type()
+    response = await invoke_llm_async(chain)
+
+    return response
+
+def _get_image_format(image_path: str) -> str:
+    file_ext = image_path.split('.')[-1].lower()
+    match file_ext:
+        case 'jpg' | 'jpeg':
+            return 'jpeg'
+        case 'png' | 'gif' | 'webp':
+            return file_ext
+        case _:
+            raise ValueError(f'Unsupported image format for {image_path=}')
+
+async def _generate_text(prompt_file: str, input: dict) -> dict | str:
+    prompt = load_prompt(prompt_file)
+    prompt_template = PromptTemplate.from_template(prompt)
+
+    llm = get_text_llm()
+    chain = prompt_template | llm | JsonOutputParser()
+    response = await invoke_llm_async(chain, input)
+    return response
+
+def get_image_from_recipe(recipe: dict) -> str:
+    recipe_for_image_gen = {k: v for k, v in recipe.items() if k in {'name', 'ingredients', 'instructions', 'meal_type', 'serves'}}
+    image_url = generate_image('get_image_from_recipe.prompt.txt', {'recipe': recipe_for_image_gen})
+    return image_url

requirements.txt

@@ -0,0 +1,7 @@
+duckduckgo_search==7.5.2
+gradio==5.21.0
+jinja2==3.1.6
+langchain_core==0.3.45
+langchain_openai==0.3.8
+langgraph==0.3.11
+python-dotenv==1.0.1

templates/recipe.html

@@ -0,0 +1,93 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <style>
+        body {
+            font-family: 'Arial', sans-serif;
+            line-height: 1.6;
+            margin: 0;
+            padding: 20px;
+        }
+
+        h1 {
+            color: #333;
+            font-size: 2.5em;
+            margin-bottom: 1em;
+            text-align: center;
+        }
+
+        h2 {
+            color: #555;
+            font-size: 1.8em;
+            margin-top: 0.5em;
+            margin-bottom: 1em;
+        }
+
+        h3 {
+            color: #666;
+            font-size: 1.2em;
+            margin-bottom: 0.5em;
+        }
+
+        ul, ol {
+            padding-left: 30px;
+        }
+
+        li {
+            margin-bottom: 0.5em;
+        }
+
+        p {
+            margin-bottom: 1em;
+        }
+
+        strong {
+            font-weight: bold;
+        }
+
+        a {
+            color: #007bff; /* Blue link color */
+            text-decoration: none;
+        }
+
+        a:hover {
+            text-decoration: underline;
+        }
+
+        .recipe-container {
+            border: 1px solid #ddd;
+            padding: 20px;
+            margin-bottom: 2em;
+            box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
+            border-radius: 5px;
+        }
+    </style>
+</head>
+<body>
+    <div class="recipe-container">
+        <h2>{{ recipe.name }}</h2>
+        <p><strong>Meal suggestion:</strong> {{ recipe.meal_type }}</p>
+        <h3>Ingredients:</h3>
+        <ul>
+            {% for ingredient in recipe.ingredients %}
+            <li>{{ ingredient }}</li>
+            {% endfor %}
+        </ul>
+        <h3>Instructions:</h3>
+        <ol>
+            {% for instruction in recipe.instructions %}
+            <li>{{ instruction }}</li>
+            {% endfor %}
+        </ol>
+        {% if recipe.serves %}
+        <p><strong>Serves:</strong> {{ recipe.serves }}</p>
+        {% endif %}
+        {% if recipe.notes %}
+        <p><strong>Notes:</strong> {{ recipe.notes }}</p>
+        {% endif %}
+        {% if recipe.disclaimer %}
+        <p><strong>Disclaimer:</strong> {{ recipe.disclaimer }}</p>
+        {% endif %}
+    </div>
+</body>
+</html>

time_it.py

@@ -0,0 +1,55 @@
+import datetime
+import inspect
+import os
+import time
+
+from functools import lru_cache, wraps
+
+def time_it(func):
+    '''
+    Decorator to measure and print the execution time of a synchronous function, including when an error is raised.
+    '''
+    source_file, first_line_number = _get_function_location(func, line_offset=1) # get line number of function definition AFTER line with decorator
+
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        try:
+            return func(*args, **kwargs)
+        finally:
+            _log_execution_time(start_time, func, source_file, first_line_number)
+
+    return wrapper
+
+def time_it_async(func):
+    '''
+    Decorator to measure and print the execution time of an asynchronous function, including when an error is raised.
+    '''
+    source_file, first_line_number = _get_function_location(func, line_offset=1) # get line number of function definition AFTER line with decorator
+
+    @wraps(func)
+    async def wrapper(*args, **kwargs):
+        start_time = time.time()
+        try:
+            return await func(*args, **kwargs)
+        finally:
+            _log_execution_time(start_time, func, source_file, first_line_number)
+
+    return wrapper
+
+@lru_cache(maxsize=None)
+def _get_function_location(func, line_offset: int) -> tuple[str, int]:
+    try:
+        source_file = os.path.basename(inspect.getsourcefile(func))
+        first_line_number = inspect.getsourcelines(func)[1] + line_offset
+        return source_file, first_line_number
+    except OSError:
+        return None, None
+
+def _log_execution_time(start_time: float, func, source_file: str | None, first_line_number: int | None) -> None:
+    end_time = time.time()
+    execution_time = end_time - start_time
+    timestamp = datetime.datetime.now().strftime('%d-%b-%y %H:%M:%S')
+    message = f'[{func.__name__}] took {execution_time:.4f} sec'
+    source_line_ref = f'{source_file}:{first_line_number}' if source_file and first_line_number else ''
+    print(f'{timestamp} [TIME] {source_line_ref} - {message}')

util.py

@@ -0,0 +1,11 @@
+UTF8_ENCODING = 'utf-8'
+
+def load_prompt(file_name: str) -> str:
+    with open(f'prompts/{file_name}', 'r', encoding=UTF8_ENCODING) as f:
+        return f.read()
+
+def yield_lines_from_file(file_path: str):
+    with open(f'data/{file_path}', 'r', encoding=UTF8_ENCODING) as f:
+        for line in f:
+            if line: # includes newline
+                yield line.strip()