Ponyrun is an AI-driven platform that provides access to a wide range of AI technologies for various needs. It offers capabilities such as chatbots, linguistic AI, and data analysis. Users can instruct Ponyrun's bots to browse and interact with websites, gathering and organizing insights efficiently. This versatile tool streamlines research processes, making it easier for users to create lists, enrich data, and connect with the right people.
Ponyrun
Give our bots instructions, and they will explore and engage with websites to collect and arrange useful information for you.
Introduction
Feature
AI-powered Research
Ponyrun conducts high-quality research on prospects at scale, enabling users to:
- Create comprehensive lists
- Enrich existing data
- Connect with relevant individuals
Customizable Options
- Block unwanted tweets
- Personalize research experience
- Tailor settings to specific needs
Integration with Popular Tools
Ponyrun seamlessly integrates with widely-used platforms:
- Gmail
- Netflix
- Other popular tools for easy data management
Easy Installation and Setup
- Install Ponyrun extension from Chrome Web Store
- Configure settings to customize research experience
- Begin research by instructing Ponyrun on desired tasks
Flexible Pricing Model
- Free version with limited features
- Paid subscription offering additional features and benefits
FAQ
Is Ponyrun free to use?
Ponyrun offers a free version with limited features. For access to additional features and benefits, a paid subscription is available.
How do I install Ponyrun?
You can easily install Ponyrun from the Chrome Web Store as a browser extension.
How does Ponyrun work?
Users simply tell Ponyrun what to do, and its AI-powered bots will browse websites, gather information, and organize insights based on the given instructions.
Is Ponyrun secure?
Yes, Ponyrun takes security seriously and ensures that user data is kept safe and secure throughout the research process.
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%
Related Websites
![AIScraper
This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API.
Features:
* Easy to use: Simply provide a search query and the library will return a list of product results.
* Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category.
* Efficient: The library uses asynchronous requests to speed up the scraping process.
* Reliable: The library is designed to handle rate limits and other website restrictions.
Installation:
```bash
pip install aiscraper
```
Usage:
```python
from aiscraper import AIScraper
Create an instance of the AIScraper class
scraper = AIScraper()
Perform a search for "laptops"
results = scraper.search("laptops")
Print the product titles
for result in results:
print(result["title"])
```
Documentation:
https://github.com/aiscraper/aiscraper](https://static.right-ai.com/tools/2024/7/4/chromewebstore-google-com-detail-aiscraper-mfjniiodgjhlmleaakofgijfccdgppbc-thumbnail-1720072105.png "AIScraper
This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API.
Features:
* Easy to use: Simply provide a search query and the library will return a list of product results.
* Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category.
* Efficient: The library uses asynchronous requests to speed up the scraping process.
* Reliable: The library is designed to handle rate limits and other website restrictions.
Installation:
```bash
pip install aiscraper
```
Usage:
```python
from aiscraper import AIScraper
Create an instance of the AIScraper class
scraper = AIScraper()
Perform a search for \"laptops\"
results = scraper.search(\"laptops\")
Print the product titles
for result in results:
print(result[\"title\"])
```
Documentation:
https://github.com/aiscraper/aiscraper")
AIScraper This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API. Features: * Easy to use: Simply provide a search query and the library will return a list of product results. * Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category. * Efficient: The library uses asynchronous requests to speed up the scraping process. * Reliable: The library is designed to handle rate limits and other website restrictions. Installation: ```bash pip install aiscraper ``` Usage: ```python from aiscraper import AIScraper Create an instance of the AIScraper class scraper = AIScraper() Perform a search for "laptops" results = scraper.search("laptops") Print the product titles for result in results: print(result["title"]) ``` Documentation: https://github.com/aiscraper/aiscraper
AIScraper This is a Python library for scraping data from websites that use the Amazon Interactive Search (AIS) API. Features: * Easy to use: Simply provide a search query and the library will return a list of product results. * Flexible: You can customize your scraping by specifying filters, such as price range, brand, and category. * Efficient: The library uses asynchronous requests to speed up the scraping process. * Reliable: The library is designed to handle rate limits and other website restrictions. Installation: ```bash pip install aiscraper ``` Usage: ```python from aiscraper import AIScraper Create an instance of the AIScraper class scraper = AIScraper() Perform a search for "laptops" results = scraper.search("laptops") Print the product titles for result in results: print(result["title"]) ``` Documentation: https://github.com/aiscraper/aiscraperWeb scraper, powered by AI! Collect structured data from web pages in just a few clicks! What's new 🔹Simplified data collection…
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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.
193.90 M