Socrates is an AI-powered platform designed to help users analyze and extract information from PDF and DOCX files. It offers a secure and private way to summarize documents, answer questions, and gain insights using advanced AI models. With both free and paid options available, Socrates caters to various user needs, from casual document analysis to professional research.
Socrates - Summarize and explain PDFs or DOCXs
Get free AI-powered answers with Socrates. Socrates uses secure, local AI processing to analyze documents. It's ideal for explaining concepts and extracting answers from books, papers, reports, articles, manuals, or contracts.
Introduction
Feature
AI-Driven Document Analysis
Socrates utilizes state-of-the-art AI models to summarize and explain PDFs or DOCX files. Users can ask questions and extract information from a wide range of documents, including books, papers, reports, and articles.
Private and Secure
The platform ensures user privacy by keeping documents local and never transmitting them to external servers. This feature is particularly valuable for those dealing with sensitive or confidential information.
Free ChatGPT Integration
Users can engage in free private chats with GPT models about the content of their documents, enhancing understanding and analysis capabilities.
Local LLM Support
Socrates offers the option to use local Large Language Models (LLMs) for offline analysis, providing flexibility and additional privacy.
Customizable Experience
Users can apply custom instructions to highlighted text, search specific pages within documents, and save frequently used prompts for efficient workflow.
Flexible Pricing Options
Socrates offers both free and paid plans:
| Plan | Price | Features |
|---|---|---|
| Free | $0 | Unlimited open source model use, capped web model use |
| Paid | $9+/month | Advanced web models, GPT-4 models, unlimited cloud document processing |
GPU Acceleration
Socrates automatically utilizes GPU capabilities to enhance performance:
- nVidia GPU users can install CUDA for optimal speed
- Other GPU users benefit from automatic Vulkan-based acceleration
FAQ
What file types does Socrates support?
Socrates currently supports PDF and DOCX file formats.
Is Socrates free to use?
Yes, Socrates offers a free plan that allows users to explore all features of the product, including unlimited use of open source models and capped use of web models.
How does Socrates ensure document privacy?
Socrates keeps all documents local on the user's computer, ensuring that they never leave the device or get transmitted to external servers.
Can Socrates work offline?
Yes, Socrates supports the use of local Large Language Models (LLMs) for offline analysis, providing functionality without an internet connection.
How can I speed up the local LLM in Socrates?
For nVidia GPU users, installing CUDA will provide the fastest local LLM experience. Users with other GPUs will automatically benefit from Vulkan-based acceleration.
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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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Gemini AI for Google Gemini AI is an innovative artificial intelligence (AI) model designed to revolutionize the way Google interacts with its users. This cutting-edge technology is capable of understanding and responding to natural language inputs, making it an ideal solution for enhancing user experience on Google's platforms. Key Features: * Conversational Interface: Gemini AI enables users to interact with Google using conversational language, making it easier to find information and perform tasks. * Contextual Understanding: The AI model can understand the context of a user's query, providing more accurate and relevant results. * Personalized Experience: Gemini AI can learn a user's preferences and tailor the search results and recommendations to their individual needs. * Multitasking Capability: The AI model can handle multiple tasks simultaneously, allowing users to perform complex queries and tasks with ease. Benefits: * Enhanced User Experience: Gemini AI provides a more intuitive and user-friendly experience, making it easier for users to find what they're looking for on Google. * Improved Accuracy: The AI model's ability to understand context and nuances of language reduces the likelihood of irrelevant search results. * Increased Productivity: Gemini AI's multitasking capability and personalized experience enable users to accomplish more in less time. Potential Applications: * Google Assistant: Gemini AI can be integrated into Google Assistant, enabling users to have more natural and conversational interactions with the virtual assistant. * Google Search: The AI model can be used to improve the search engine's ability to understand complex queries and provide more accurate results. * Google Workspace: Gemini AI can be applied to Google Workspace (formerly G Suite) to enhance the productivity and collaboration capabilities of the platform.🗨️ Revolutionize Your Online Searches with Gemini AI for Google – Get Smart Answers Right Beside Google Results!
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