MealCrafter is an AI-powered platform designed to create personalized meal plans tailored to individual dietary goals and preferences. It offers a comprehensive solution for those seeking to improve their eating habits and achieve health objectives effortlessly. The platform provides customized meal plans, easy-to-follow recipes, and additional features to support users in their journey towards better health.
MealCrafter
The Web App for personalized meal planning tailored to your dietary goals
Introduction
Feature
Personalized Meal Planning
MealCrafter utilizes AI technology to generate customized meal plans based on user-specific dietary goals and preferences. These plans include breakfast, lunch, dinner, and snacks, ensuring a well-rounded approach to nutrition.
Diverse Recipe Database
Users have access to a variety of delicious and easy-to-follow recipes that align with their personalized meal plans. The platform allows for recipe regeneration, providing continuous variety and options.
Convenient Grocery List
MealCrafter generates a comprehensive grocery list organized by category and quantity, simplifying the shopping process for users.
AI-Driven Customization
The platform's AI technology takes care of the meal planning process based on user input during the onboarding process, creating tailored plans that suit individual needs.
Ongoing Support
Users receive email support to help them stay on track and overcome challenges in their health journey.
Flexible Subscription Options
MealCrafter offers both monthly and yearly subscription plans, with a discount available for annual subscriptions.
| Subscription | Price | Savings |
|---|---|---|
| Monthly | €9.9 | - |
| Yearly | €89.9 | 20% OFF |
FAQ
What does a MealCrafter subscription include?
A MealCrafter subscription provides:
- 1 personalized meal plan
- Access to 20 delicious recipes
- Ability to generate new recipes as needed
- Groceries list
- Stock list
- Email support
How does MealCrafter handle dietary restrictions?
MealCrafter allows users to input dietary restrictions and allergies during the onboarding process. The AI ensures that meal plans exclude any ingredients that users cannot consume.
Is there a free trial available?
Currently, MealCrafter does not offer a free trial. However, interested users can email [email protected] to potentially participate in a 7-day test program.
Can subscriptions be cancelled at any time?
Yes, users can cancel their subscription at any time directly from their account settings without any long-term commitments.
How can users contact customer support?
Customer support can be reached via email at [email protected] for any questions or assistance needed.
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* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.](https://static.right-ai.com/tools/2024/7/3/chromewebstore-google-com-detail-chatgpt-for-google-for-fr-pabeminldebomngnkgffiejipjjaaogi-thumbnail-1720037311.png "Get ChatGPT for Free with Google
You can now access ChatGPT, a powerful language model, for free with Google. Here's how:
Method 1: Google Colab
* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = \"Your input here\"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = \"Your input here\"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.")
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.How to Add ChatGPT to All Google Searches ===================================================== Step 1: Create a Custom Search Engine -------------------------------------- * Go to the [Google Custom Search Engine](https://cse.google.com/) website and sign in with your Google account. * Click on the "New Search Engine" button. * Fill in the required information, such as the name and description of your search engine. * Click on the "Create" button. Step 2: Add ChatGPT to the Search Engine ----------------------------------------- * In the "Setup" tab, click on the "Add" button next to "Sites to search". * Enter the following URL: `https://chat.openai.com/` * Click on the "Add" button. Step 3: Configure the Search Engine -------------------------------------- * In the "Setup" tab, click on the "Edit" button next to "Search engine keywords". * Add the following keywords: `ChatGPT` * Click on the "Save" button. Step 4: Get the Search Engine Code ------------------------------------- * In the "Setup" tab, click on the "Get code" button. * Copy the HTML code provided. Step 5: Add the Search Engine to Your Browser ------------------------------------------------ * Open your browser and go to the "Settings" or "Options" page. * Look for the "Search engine" or "Default search engine" option. * Click on the "Add" or "Manage search engines" button. * Paste the HTML code you copied earlier. * Click on the "Add" or "Save" button. You're Done! =============== Now, whenever you search on Google, ChatGPT will be included in the search results. You can also use the custom search engine URL provided by Google to search directly.
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Alchemy for ChatGPT Introduction Alchemy is a powerful framework for building and deploying large language models (LLMs) like ChatGPT. It provides a comprehensive set of tools and resources to streamline the entire LLM development lifecycle, from training to deployment and monitoring. Key Features * Modular Design: Alchemy is built with a modular architecture, allowing developers to easily customize and extend its functionality. * Fine-Tuning Capabilities: Alchemy offers robust fine-tuning capabilities, enabling users to adapt pre-trained LLMs to specific tasks and domains. * Deployment Flexibility: Alchemy supports deployment across various platforms, including cloud, on-premise, and edge devices. * Monitoring and Evaluation: Alchemy provides tools for monitoring LLM performance and evaluating their effectiveness. Benefits * Accelerated Development: Alchemy's modularity and pre-built components significantly reduce development time and effort. * Improved Accuracy: Fine-tuning capabilities allow for higher accuracy and performance on specific tasks. * Scalability and Reliability: Alchemy's deployment flexibility ensures scalability and reliability for diverse applications. * Cost-Effectiveness: Alchemy's efficient resource utilization and streamlined workflows contribute to cost savings. Use Cases Alchemy can be used in a wide range of applications, including: * Chatbots and Conversational AI: * Text Generation and Summarization: * Code Generation and Debugging: * Data Analysis and Insights: * Personalized Learning and Education: Conclusion Alchemy is a powerful and versatile framework that empowers developers to build, deploy, and manage LLMs effectively. Its comprehensive features, benefits, and diverse use cases make it an ideal choice for organizations looking to leverage the transformative potential of LLMs.
Alchemy for ChatGPT Introduction Alchemy is a powerful framework for building and deploying large language models (LLMs) like ChatGPT. It provides a comprehensive set of tools and resources to streamline the entire LLM development lifecycle, from training to deployment and monitoring. Key Features * Modular Design: Alchemy is built with a modular architecture, allowing developers to easily customize and extend its functionality. * Fine-Tuning Capabilities: Alchemy offers robust fine-tuning capabilities, enabling users to adapt pre-trained LLMs to specific tasks and domains. * Deployment Flexibility: Alchemy supports deployment across various platforms, including cloud, on-premise, and edge devices. * Monitoring and Evaluation: Alchemy provides tools for monitoring LLM performance and evaluating their effectiveness. Benefits * Accelerated Development: Alchemy's modularity and pre-built components significantly reduce development time and effort. * Improved Accuracy: Fine-tuning capabilities allow for higher accuracy and performance on specific tasks. * Scalability and Reliability: Alchemy's deployment flexibility ensures scalability and reliability for diverse applications. * Cost-Effectiveness: Alchemy's efficient resource utilization and streamlined workflows contribute to cost savings. Use Cases Alchemy can be used in a wide range of applications, including: * Chatbots and Conversational AI: * Text Generation and Summarization: * Code Generation and Debugging: * Data Analysis and Insights: * Personalized Learning and Education: Conclusion Alchemy is a powerful and versatile framework that empowers developers to build, deploy, and manage LLMs effectively. Its comprehensive features, benefits, and diverse use cases make it an ideal choice for organizations looking to leverage the transformative potential of LLMs.Unlock the full capabilities of ChatGPT.
193.90 M