Spaces:
Sleeping
Sleeping
| from io import BytesIO | |
| import pandas as pd | |
| import numpy as np | |
| import requests | |
| import streamlit as st | |
| import easyocr | |
| import PIL | |
| from PIL import Image, ImageDraw | |
| from matplotlib import pyplot as plt | |
| import streamlit.components.v1 as components | |
| import re | |
| from streamlit import session_state | |
| # from streamlit_lottie import st_lottie | |
| import streamlit as st | |
| import os | |
| from dotenv import load_dotenv, find_dotenv | |
| # Load environment variables | |
| _ = load_dotenv(find_dotenv()) | |
| # Get OpenAI API key | |
| openai_api_key = os.getenv('OPENAI_API_KEY') | |
| # Google Drive file ID for the video | |
| video_file_id = '1miZ6Zz4lt0wxTGbrtR8IltVr_fOPX6Vr' | |
| video_url = f'https://drive.google.com/uc?export=view&id={video_file_id}' | |
| def initialize_grocery_data(): | |
| return pd.DataFrame(columns=['Name', 'Quantity', 'Additional Notes/Expiration Date']) | |
| def manually_input_items(grocery_data): | |
| return grocery_data | |
| def upload_receipt(): | |
| st.header("Upload Receipt") | |
| uploaded_file = st.file_uploader("Choose a receipt file", type=["jpg", "jpeg", "png", "pdf"]) | |
| if uploaded_file is not None: | |
| st.success("Receipt uploaded successfully!") | |
| # Add your code here for processing the uploaded receipt | |
| st.set_page_config(layout="wide") | |
| if 'clicked' not in st.session_state: | |
| st.session_state.clicked = False | |
| if 'total_groceries' not in st.session_state: | |
| st.session_state.total_groceries = {} | |
| if 'grocery_data' not in st.session_state: | |
| st.session_state.grocery_data = pd.DataFrame(columns=['Name', 'Quantity', 'Additional Notes/Expiration Date']) | |
| if 'editor_key' not in st.session_state: | |
| st.session_state.editor_key = 0 | |
| if 'manual_entry' not in st.session_state: | |
| st.session_state.manual_entry = True | |
| if 'file_uploaded' not in st.session_state: | |
| st.session_state.file_uploaded = False | |
| if 'ocr_extracted_values' not in st.session_state: | |
| session_state.ocr_extracted_values = pd.DataFrame() | |
| def click_save(): | |
| session_state.clicked = True | |
| def switch_style(): | |
| session_state.manual_entry = not session_state.manual_entry | |
| # Define the HTML and CSS styling for the title | |
| title_html = """ | |
| <html> | |
| <head> | |
| <link href='https://fonts.googleapis.com/css?family=Cedarville Cursive' rel='stylesheet'> | |
| <style> | |
| body { | |
| font-family: 'serif; | |
| font-size: 22px; | |
| text-align: center; | |
| } | |
| h1 { | |
| font-family: 'Cedarville Cursive'; | |
| font-size: 56px; | |
| display: inline-block; | |
| margin_bottom: 3px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <h1>Nom Nom!</h1> | |
| </body> | |
| </html> | |
| """ | |
| # Use st.markdown to display the title with the specified font | |
| st.markdown(title_html, unsafe_allow_html=True) | |
| caption_html = """ | |
| <div style="display: flex; justify-content: center; align-items: center; font-style: italic; font-weight: bold;"> | |
| <p>Helping College Students Manage Their Groceries</p> | |
| </div> | |
| """ | |
| st.markdown(caption_html, unsafe_allow_html=True) | |
| # Initialize or retrieve the existing dataframe to store grocery items | |
| grocery_data = initialize_grocery_data() | |
| tab1, tab2, tab3 = st.tabs(["Add Groceries", "Available Groceries", "Create recipes"]) | |
| df = pd.DataFrame() | |
| with tab1: | |
| st.button("Switch to OCR Input", on_click=switch_style) | |
| col1, col2 = st.columns([2, 1]) | |
| if session_state.manual_entry: | |
| with col1: | |
| if not session_state.clicked: | |
| st.subheader("Add Groceries - Manually Input Items") | |
| session_state.grocery_data = st.data_editor(pd.DataFrame(columns=['Name', 'Quantity', 'Additional Notes/Expiration Date']), key=session_state.editor_key, num_rows="dynamic", hide_index=True, use_container_width=True) | |
| else: | |
| session_state.editor_key += 1 | |
| with col2: | |
| file_id = '1_3FjYmWlJcY182qnLIjFPTZYj4gneUMg' | |
| base_url = 'https://drive.google.com/uc?id=' | |
| image_url = base_url + file_id | |
| response = requests.get(image_url) | |
| img = Image.open(BytesIO(response.content)) | |
| # image1 = Image.open(r'https://drive.google.com/file/d/1_3FjYmWlJcY182qnLIjFPTZYj4gneUMg/view?usp=sharing') | |
| st.image(img, width=400) | |
| st.write("---") | |
| else: | |
| with col1: | |
| st.subheader("Upload receipt instead") | |
| uploaded_file = st.file_uploader("Choose a receipt file", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file is not None: | |
| session_state.file_uploaded = True | |
| st.success("Receipt uploaded successfully!") | |
| st.write("") | |
| if session_state.file_uploaded: | |
| receipt_image = Image.open(uploaded_file) | |
| st.image(receipt_image) | |
| reader = easyocr.Reader(['en'], gpu=False) | |
| result = reader.readtext(np.array(receipt_image)) | |
| text_list = [] | |
| confidence_list = [] | |
| for idx in range(len(result)): | |
| pred_coor = result[idx][0] | |
| pred_text = result[idx][1] | |
| pred_confidence = result[idx][2] | |
| text_list.append(pred_text) | |
| confidence_list.append(pred_confidence) | |
| df = pd.DataFrame({'Text': text_list, 'Confidence': confidence_list}) | |
| with col2: | |
| if session_state.file_uploaded: | |
| st.subheader("Updated Grocery List") | |
| df = df[~df['Text'].str.contains(r'[\d]')] | |
| df['Add to List?'] = None | |
| df2 = st.data_editor(df, use_container_width=True, num_rows = 'dynamic', column_config={"Text": "Item", | |
| "Add to List?" : st.column_config.CheckboxColumn( | |
| "Add to List?", | |
| help="Select if you want to add this to the list.", | |
| default=False | |
| )}, key="OCR_DataFrame") | |
| st.write(session_state["OCR_DataFrame"]) | |
| session_state.ocr_extracted_values = df2 | |
| st.button("Press me to update Tab 2", on_click=click_save) | |
| def ingredient_html_maker(ingredient, num_ingredients, map_for_grocery): | |
| return_val = f"<div class=\"card\" style=\"background-color: #dedede; padding: 10px; margin: 5px; border-radius: 10px;\">\n" | |
| return_val += f"<h3>{ingredient}</h3>\n" # Ingredient name | |
| return_val += f"<p>Quantity: <span id='quantity_{ingredient}'>{num_ingredients}</span></p>\n" | |
| return_val += f"<button onclick=\"updateQuantity('{ingredient}', '-', {map_for_grocery})\">-</button>\n" | |
| return_val += f"<button onclick=\"updateQuantity('{ingredient}', '+', {map_for_grocery})\">+</button>\n" | |
| return_val += f"</div>\n" | |
| return return_val | |
| def list_display(total_groceries): | |
| list_html = '' | |
| with open('List.html') as list_file: | |
| list_html = list_file.read() | |
| list_html_without_end = list_html[:-6] | |
| end = list_html[-6:] | |
| final_list_html = list_html_without_end + "\n" | |
| for item in total_groceries: | |
| final_list_html += ingredient_html_maker(item, total_groceries[item], total_groceries) | |
| final_list_html += "\n" + end | |
| return components.html(final_list_html + javascript_code, height=500) | |
| with tab2: | |
| javascript_code = """ | |
| <script> | |
| function updateQuantity(ingredient, operation, grocery_data) { | |
| // Get the current quantity | |
| var quantityElement = document.getElementById('quantity_' + ingredient); | |
| var currentQuantity = parseInt(quantityElement.innerText); | |
| // Update the quantity based on the operation | |
| if (operation === '+') { | |
| currentQuantity += 1; | |
| } else if (operation === '-') { | |
| currentQuantity = Math.max(0, currentQuantity - 1); | |
| } | |
| grocery_data[ingredient] = currentQuantity; | |
| console.log(grocery_data); | |
| // Update the quantity display | |
| quantityElement.innerText = currentQuantity; | |
| } | |
| </script> | |
| """ | |
| if session_state.clicked and session_state.manual_entry: | |
| for i in range(len(session_state.grocery_data)): | |
| existing_quantity = st.session_state.total_groceries.get(session_state.grocery_data["Name"][i], 0) | |
| st.session_state.total_groceries[session_state.grocery_data["Name"][i]] = int(existing_quantity) + int(session_state.grocery_data["Quantity"][i]) | |
| list_display(st.session_state.total_groceries) | |
| session_state.clicked = False | |
| st.rerun() | |
| elif session_state.clicked and not session_state.manual_entry and session_state.file_uploaded: | |
| for idx in session_state["OCR_DataFrame"]['edited_rows']: | |
| ingredient = session_state.ocr_extracted_values['Text'].iloc[idx] | |
| existing_quantity = st.session_state.total_groceries.get(ingredient, 0) | |
| st.session_state.total_groceries[ingredient]= int(existing_quantity) + 1 | |
| list_display(st.session_state.total_groceries) | |
| session_state.clicked = False | |
| st.rerun() | |
| else: | |
| list_display(st.session_state.total_groceries) | |
| with tab3: | |
| st.write("hi") | |
| # # Create columns for layout | |
| # col1, col2 = st.columns([0.20, 0.80]) | |
| # # Column 1: Display the embedded video without controls | |
| # with col1: | |
| # video_html = f""" | |
| # <video width="100%" height="auto" autoplay muted style="margin-top: -30px;"> | |
| # <source src="{video_url}" type="video/mp4"> | |
| # Your browser does not support the video tag. | |
| # </video> | |
| # """ | |
| # st.markdown(video_html, unsafe_allow_html=True) | |
| # with col2: | |
| # st.header("NomNom Bot") | |
| # st.markdown('<style>div.Widget.row-widget.stRadio > div{flex-direction:row;}</style>', unsafe_allow_html=True) | |
| # st.caption("🍳 Your personal recipe generator!") | |
| # st.caption("Enter a cuisine and your dietary restrictions to get started :)") | |
| # with st.sidebar: | |
| # cuisine = st.text_input("Cuisine you're craving", key="cuisine") | |
| # diet_res = st.text_input("Dietary Restrictions", key="diet_res") | |
| # ingredients = { | |
| # 'Tomatoes': 3, | |
| # 'Rice': 1 | |
| # } | |
| # content_template = """ | |
| # I have scanned/entered my grocery store receipts. Here are the items and their quantity (in the form of a dictionary) I have purchased: | |
| # {ingredients}. | |
| # My dietary restrictions include {diet_res}. I am in the mood for {cuisine} recipes. Give me a detailed recipe using ONLY | |
| # the ingredients I have. I also have common pantry items like salt, pepper, olive oil, and basic spices. | |
| # Make sure to take the cuisine and dietary restrictions into consideration definitively. | |
| # Provide a recipe that aligns with the preferred cuisine given by the user. A cuisine is a style or method of cooking, especially of a particular country | |
| # or region. Use ingredients, foods, and techniques from the cuisine from that specific region. | |
| # If the user says their dietary restriction is an X allergy or allergic to X where X is any ingredient, make sure to exclude X from the recipe | |
| # since the user could die of an allergic reaction and you will be responsible. | |
| # Start your response with "Howdy, I'm the NomNom Bot!" and end by asking if the user has any follow-up questions or needs any additional resources. | |
| # """ | |
| # print("Content Template:", content_template.format(ingredients=ingredients, diet_res=diet_res, cuisine=cuisine)) | |
| # # Initialize the chat with an initial user message | |
| # if cuisine and diet_res: | |
| # if "messages" not in st.session_state: | |
| # print("Content Template:", content_template.format(ingredients=ingredients, diet_res=diet_res, cuisine=cuisine)) | |
| # st.session_state["messages"] = [ | |
| # {"role": "user", "content": content_template.format(ingredients=ingredients, diet_res=diet_res, cuisine=cuisine)}] | |
| # # Display the chat messages | |
| # for msg in st.session_state.messages[1:]: | |
| # st.chat_message(msg["role"]).write(msg["content"]) | |
| # # Generate a response for the initial user message | |
| # if len(st.session_state.messages) == 1: | |
| # client = OpenAI(api_key=openai_api_key) | |
| # response = client.chat.completions.create( | |
| # model="gpt-3.5-turbo", | |
| # messages=st.session_state.messages, | |
| # max_tokens=2048, | |
| # n=1, | |
| # stop=None, | |
| # temperature=0.5 | |
| # ) | |
| # msg = response.choices[0].message.content | |
| # st.session_state.messages.append({"role": "assistant", "content": msg}) | |
| # st.chat_message("assistant").write(msg) | |
| # # User can ask follow-up questions | |
| # if prompt := st.chat_input(): | |
| # if not openai_api_key: | |
| # st.info("API key is not valid.") | |
| # st.stop() | |
| # client = OpenAI(api_key=openai_api_key) | |
| # st.session_state.messages.append({"role": "user", "content": prompt}) | |
| # st.chat_message("user").write(prompt) | |
| # response = client.chat.completions.create( | |
| # model="gpt-3.5-turbo", | |
| # messages=st.session_state.messages, | |
| # max_tokens=2048, | |
| # n=1, | |
| # stop=None, | |
| # temperature=0.5 | |
| # ) | |
| # msg = response.choices[0].message.content | |
| # st.session_state.messages.append({"role": "assistant", "content": msg}) | |
| # st.chat_message("assistant").write(msg) | |
| st.markdown(""" | |
| <style> | |
| .stTabs [data-baseweb="tab-list"] { | |
| gap: 10px; | |
| } | |
| .stTabs [data-baseweb="tab"] { | |
| height: 50px; | |
| width: 100%; | |
| white-space: pre-wrap; | |
| background-color: #F1C0B9; | |
| border-radius: 4px 4px 0px 0px; | |
| gap: 1px; | |
| padding-top: 10px; | |
| padding-bottom: 10px; | |
| color: black; /* Added this line to set the text color */ | |
| font-weight: bold; /* Added this line to make the text bold */ | |
| } | |
| .stTabs [aria-selected="true"] { | |
| background-color: #F1C0B9; | |
| color: black; | |
| font-weight: bold; /* Added this line to make the text bold */ | |
| } | |
| </style>""", unsafe_allow_html=True) |