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ChatGPT Conversations Search

Save, search, and organize your ChatGPT conversation history.
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ChatGPT Conversations Search
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Introduction

Proompt is a Chrome extension designed to enhance the ChatGPT experience by providing a comprehensive solution for saving, searching, and organizing conversation history. This tool allows users to maintain access to their ChatGPT interactions even when offline, making it an invaluable resource for frequent ChatGPT users. Proompt offers a range of features aimed at improving the management and retrieval of conversation data, all while maintaining user privacy and data security.

Feature

Save Conversations Locally πŸ’Ύ

Proompt enables users to store all their ChatGPT conversation records on their local device. This feature ensures:

  • Offline access to conversations
  • Enhanced privacy and data control
  • Permanent record of valuable interactions

Advanced Search Functionality πŸ”

The extension incorporates a sophisticated search system:

  • Full-text search capability
  • Advanced fuzzy matching algorithm
  • Quick retrieval of old conversations using keywords

Organize Conversations πŸ“ (Upcoming Feature)

Proompt is developing an organizational system that will include:

  • Categorization of conversations into folders
  • Tagging system for easy reference
  • Improved conversation management

Free to Use

Proompt offers its features at no cost:

  • No subscription required
  • Free installation from Chrome Web Store
  • Unlimited use of all available features

Offline Accessibility

Users can access their saved conversations without an internet connection:

  • Review past interactions anytime
  • Utilize saved information in offline scenarios
  • Ensure continuous access to important data

FAQ

How do I start using Proompt?

To begin using Proompt:

  1. Install the extension from the Chrome Web Store
  2. Start saving your ChatGPT conversations
  3. Use the search and organization features as needed

Is my data used for training purposes?

No, Proompt does not collect or use your data for training purposes. Your conversations remain private and secure.

What search capabilities does Proompt offer?

Proompt provides:

  • Full-text search functionality
  • Advanced fuzzy matching algorithm
  • Keyword-based search for quick retrieval of old conversations

Are there any tips for maximizing Proompt's effectiveness?

To get the most out of Proompt:

  • Save conversations regularly
  • Utilize the search feature for efficient retrieval
  • Organize conversations using folders and tags (once available)
  • Take advantage of offline access when needed

Latest Traffic Insights

  • Monthly Visits

    193.90 M

  • Bounce Rate

    56.27%

  • Pages Per Visit

    2.71

  • Time on Site(s)

    115.91

  • Global Rank

    -

  • Country Rank

    -

Recent Visits

Traffic Sources

  • Social Media:
    0.48%
  • Paid Referrals:
    0.55%
  • Email:
    0.15%
  • Referrals:
    12.81%
  • Search Engines:
    16.21%
  • Direct:
    69.81%
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ChatGPT Keyboard Shortcuts

#Navigation

* Ctrl + β†’: Move to the next message
* Ctrl + ←: Move to the previous message
* Home: Move to the beginning of the conversation
* End: Move to the end of the conversation

#Editing

* Ctrl + A: Select all text
* Ctrl + C: Copy selected text
* Ctrl + X: Cut selected text
* Ctrl + V: Paste copied or cut text
* Ctrl + Z: Undo
* Ctrl + Y: Redo
* Ctrl + Shift + F: Format text as code

#Actions

* Enter: Send the message
* Shift + Enter: Insert a new line
* Ctrl + Shift + Enter: Send the message and insert a new line
* Esc: Cancel editing and close the message input field
* Ctrl + Shift + Space: Open the emoji picker
* Ctrl + Shift + /: Open the help menu

#Accessibility

* Ctrl + +: Increase font size
* Ctrl + -: Decrease font size
* Ctrl + 0: Reset font size to default
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ChatGPT Keyboard Shortcuts #Navigation * Ctrl + β†’: Move to the next message * Ctrl + ←: Move to the previous message * Home: Move to the beginning of the conversation * End: Move to the end of the conversation #Editing * Ctrl + A: Select all text * Ctrl + C: Copy selected text * Ctrl + X: Cut selected text * Ctrl + V: Paste copied or cut text * Ctrl + Z: Undo * Ctrl + Y: Redo * Ctrl + Shift + F: Format text as code #Actions * Enter: Send the message * Shift + Enter: Insert a new line * Ctrl + Shift + Enter: Send the message and insert a new line * Esc: Cancel editing and close the message input field * Ctrl + Shift + Space: Open the emoji picker * Ctrl + Shift + /: Open the help menu #Accessibility * Ctrl + +: Increase font size * Ctrl + -: Decrease font size * Ctrl + 0: Reset font size to default

ChatGPT Keyboard Shortcuts #Navigation * Ctrl + β†’: Move to the next message * Ctrl + ←: Move to the previous message * Home: Move to the beginning of the conversation * End: Move to the end of the conversation #Editing * Ctrl + A: Select all text * Ctrl + C: Copy selected text * Ctrl + X: Cut selected text * Ctrl + V: Paste copied or cut text * Ctrl + Z: Undo * Ctrl + Y: Redo * Ctrl + Shift + F: Format text as code #Actions * Enter: Send the message * Shift + Enter: Insert a new line * Ctrl + Shift + Enter: Send the message and insert a new line * Esc: Cancel editing and close the message input field * Ctrl + Shift + Space: Open the emoji picker * Ctrl + Shift + /: Open the help menu #Accessibility * Ctrl + +: Increase font size * Ctrl + -: Decrease font size * Ctrl + 0: Reset font size to default

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Method 1: Google Colab

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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.
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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.

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