import os import gradio as gr import json import re from datetime import datetime import openai import random # from pyppeteer import launch # import tempfile user_db = { os.environ["username"]: os.environ["password"], } music_files = [ "RPReplay_Final1712757356.mp3", "RPReplay_Final1712801927.mp3", "RPReplay_Final1712802362.mp3", "RPReplay_Final1712802406.mp3", "RPReplay_Final1712757356.mp3", "RPReplay_Final1712802448.mp3", "RPReplay_Final1712802599.mp3" ] # Function to play background music def play_music(): """Returns the path to the music file and makes the audio player visible.""" music_path = random.choice(music_files) return music_path, gr.update(visible=True) # Main function to generate a cocktail recipe based on user preferences def generate_cocktail(mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests): """Generates a cocktail recipe using OpenAI's GPT-4 based on user input.""" client = openai.OpenAI(api_key=os.environ["API_TOKEN"]) instruction = "Please provide a cocktail recipe given the mood and preference of the user.\n\n" user_prompt = f"Mood: {mood}\nTaste: Sweetness {sweetness}/10, Sour {sour}/10, Savory {savory}/10, Bitter {bitter}/10\nFlavor: {flavor_association}\nDrinking Experience: {drinking_experience}\nLevel of Soberness: {soberness_level}\nAllergies: {allergies}\nAdditional Requests: {additional_requests}\n\nMake sure to avoid all allergic ingredients.\n\n" output_format = "Please strictly follow this output format:\n\nCocktail Name:[name]\nQuote:[one sentence quote related to the cocktail and the mood description]\nIngredients:[ingredient 1]\n[ingredient 2]\n...\nInstruction:1. [step 1]\n2. [step 2]\n...\nNotes:[notes]" prompt = instruction + user_prompt + output_format messages=[ {"role": "system", "content": "You are a helpful bartender assistant."}, {"role": "user", "content": prompt} ] try: response = client.chat.completions.create( model="gpt-4-0125-preview", messages=messages, max_tokens=1024) name, quote, ingredients, instruction, notes = extract_info(response.choices[0].message.content) return format_cocktail_output(name, quote, ingredients, instruction, notes), True except Exception as e: return f'

{str(e)}

' # Extract information from the response generated by OpenAI def extract_info(output_text): """Extracts the cocktail recipe information from the response text.""" pattern = r"Cocktail Name:(.*?)Quote:(.*?)Ingredients:(.*?)Instruction:(.*?)Notes:(.*?)$" match = re.search(pattern, output_text, re.DOTALL) if match: name = match.group(1).strip() quote = match.group(2).strip() ingredients = match.group(3).strip().replace('\n', '
') instruction = match.group(4).strip().replace('\n', '
') notes = match.group(5).strip() return name, quote, ingredients, instruction, notes else: return None # Format the cocktail recipe for display def format_cocktail_output(name, quote, ingredients, instruction, notes): """Formats the cocktail recipe into HTML for display.""" html_output = f'''

{name}

{quote}

Ingredients:
{ingredients}
Instruction:
{instruction}
Notes:
{notes}

''' return html_output # def save_as_pdf(html_content): # """Converts HTML content to PDF, encodes it in base64, and returns a download link.""" # html_path = "output_recipe.html" # pdf_path = "output_recipe.pdf" # # Write the HTML content to a temporary file # with open(html_path, 'w') as f: # f.write(html_content) # # Convert HTML to PDF # pdfkit.from_file(html_path, pdf_path) # # Encode the PDF file in base64 # with open(pdf_path, "rb") as pdf_file: # encoded_pdf = base64.b64encode(pdf_file.read()).decode("utf-8") # # Create a Data URL for the PDF # pdf_data_url = f"data:application/pdf;base64,{encoded_pdf}" # # Return HTML anchor tag for the download link # return f'Download PDF' # def generate_pdf_from_html(html_content): # browser = launch() # page = browser.newPage() # page.setContent(html_content) # # Create a temporary file to save the PDF # with tempfile.NamedTemporaryFile(suffix='.pdf', delete=False) as tmp_file: # pdf_path = tmp_file.name # page.pdf({'path': pdf_path, 'format': 'A4'}) # # Close browser # browser.close() # # Generate URL for the temporary PDF file # pdf_url = f'file://{pdf_path}' # return pdf_url, True with open('style.css', 'r') as file: css_styles = file.read() # Creating the Gradio interface with gr.Blocks(css=css_styles) as MoodShaker: with gr.Row(): gr.HTML('''
MoodShaker Cocktail Generator
''') with gr.Row(): mood = gr.Textbox(label="How are you feeling today?", elem_classes=["custom-input"]) flavor_association = gr.CheckboxGroup(label="Flavor", choices=["Fruity", "Herbal", "Spicy", "Floral", "Nutty", "Woody", "Earthy"], elem_classes=["custom-checkbox-group1"]) drinking_experience = gr.CheckboxGroup(label="Drinking Experience", choices=["Refreshing", "Warming", "Comforting", "Energizing", "Relaxing"], elem_classes=["custom-checkbox-group2"]) with gr.Row(): sweetness = gr.Slider(label="Sweetness", minimum=0, maximum=10, elem_id="slider-sweetness",elem_classes=["slider-sweetness"]) sour = gr.Slider(label="Sour", minimum=0, maximum=10, elem_id="slider-sour", elem_classes=["slider-sour"]) savory = gr.Slider(label="Savory", minimum=0, maximum=10, elem_id="slider-savory", elem_classes=["slider-savory"]) bitter = gr.Slider(label="Bitter", minimum=0, maximum=10, elem_id="slider-bitter", elem_classes=["slider-bitter"]) soberness_level = gr.Slider(label="Level of Soberness", minimum=0, maximum=10, value=10, elem_id="slider-soberness_level", elem_classes=["slider-soberness_level"]) with gr.Row(): allergies = gr.Textbox(label="Allergies", scale=6, elem_classes=["custom-input1"]) additional_requests = gr.Textbox(label="Anything else you would like to address", scale=6, elem_classes=["custom-input2"]) generate_button = gr.Button("Generate Your Cocktail Recipe", scale=3, elem_classes=["generate-button"]) clear_button = gr.Button("Clear", scale=1) with gr.Row(): output_recipe = gr.HTML(label="Your Cocktail Recipe") play_button = gr.Button("Play Music", visible=False, elem_classes=["generate-button"], scale=1) # Initially not visible background_music = gr.Audio(label="Background Music", autoplay=True, visible=False, scale=4) # Initially not visible # with gr.Row(): # save_pdf_button = gr.Button("Download Recipe as PDF", visible=False) # pdf_download_link = gr.File(label="Download Link", visible=False) # For displaying the PDF download link def on_generate_click(*args): recipe, show_play_button = generate_cocktail(*args) return recipe, gr.update(visible=show_play_button) def reset(): return "", 0, 0, 0, 0, [], [], 10, "", "", "", gr.update(visible=False), gr.update(visible=False) generate_button.click( fn=on_generate_click, inputs=[mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests], outputs=[output_recipe, play_button] ) play_button.click(fn=play_music, inputs=[], outputs=[background_music, background_music]) # save_pdf_button.click(fn=generate_pdf_from_html, inputs=[output_recipe], outputs=[pdf_download_link, pdf_download_link]) clear_button.click(fn=reset, inputs=[], outputs=[mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests, output_recipe, play_button, background_music]) if __name__ == "__main__": MoodShaker.launch(#enable_queue=False, # Creates an auth screen auth=lambda u, p: user_db.get(u) == p, auth_message="Welcome to MoodShaker! Enter a Username and Password" ).queue()