Save $$ on Web RAG Prompts
Experience significant cost savings when adding web content to GPT-4 prompts.
Our link compresses web content in to pure information, reducing input tokens by up to 87%.
Copy Paste Integration
Integration is as simple as copy pasting your URL: '[your-gpt-zip.link]/[original-link-to-compress]'.
This single step provides makes sure you get the information not the HTML soup for your GPT-4 prompts.
Achieve Faster Responses
Streamline your GPT-4's data processing for quicker, more accurate responses.
Our solution simplifies data complexity, enhancing both speed and performance of GPT-4 responses.
Integrate in Seconds
No matter which language you use to integrate with OpenAI API, you can start saving money within seconds with GPT-Zip.Link.Use with JavaScript
JavaScript's adaptability makes it a top choice for building interactive web applications that utilize GPT's capabilities. It allows for seamless integration of AI features into web interfaces. A straightforward modification can achieve up to 87% reduction in GPT input tokens in JavaScript integration.
// Fetch web content
const res = await fetch('https://gpt-zip.link/paid12345678/https://wikipedia.org/wiki/Twitter');
const wiki = await res.text();
// Prepare the prompt
const prompt = `Based on this content: \n${wiki}\n\n What is Twitter's new name?`;
const chatCompletion = await openai.chat.completions.create({
model: "gpt-4-1106-preview",
messages: [
{
role: "user",
content: prompt
}]
});
console.log(chatCompletion.usage.prompt_tokens);
// Only 271996 input prompt tokens// 379546 input prompt tokens
// Just saved $1.08 on GPT-4.
Use with Python
Python, known for its simplicity and readability, is extensively used in AI for its powerful libraries and ease of data handling. Its popularity in GPT integrations stems from these strengths, making complex tasks more manageable. One simple line change can see up to 87% decrease in input tokens sent to GPT in Python integration.
# Fetch web content
res = requests.get('https://gpt-zip.link/paid12345678/https://wikipedia.org/wiki/Twitter')
wiki = res.text
# Prepare the prompt
prompt = f"Based on this content: \n{wiki}\n\n What is Twitter's new name?"
# Create the chat completion
chat_completion = openai.ChatCompletion.create(
model="gpt-4-1106-preview",
messages=[{"role": "user", "content": prompt}]
)
print(chat_completion['usage']['prompt_tokens'])
# Only 271996 input prompt tokens# 379546 input prompt tokens
# Just saved $1.08 on GPT-4.
Use with PHP
PHP is integral in server-side scripting and is commonly employed for GPT implementations in web-based AI solutions. Its ease of integrating with various APIs makes it ideal for sending and processing GPT requests. A simple line change can lead to an 87% decrease in input tokens for GPT in PHP integration.
// Fetch web content
$wiki = executeCurl('https://gpt-zip.link/paid12345678/https://wikipedia.org/wiki/Twitter');
// Prepare the prompt
$prompt = "Based on this content: \n" . $wiki . "\n\n What is Twitter's new name?";
$data = [
'model' => 'gpt-4-1106-preview',
'messages' => [['role' => 'user', 'content' => $prompt]]
];
// Create the chat completion
$response = executeCurl('https://api.openai.com/v1/chat/completions', $data);
$responseData = json_decode($response, true);
echo $responseData['usage']['prompt_tokens'];
// Only 271996 input prompt tokens// 379546 input prompt tokens
// Just saved $1.08 on GPT-4.