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const axios = require('axios');
const fs = require('fs');
const path = require('path');
// helper function to help you convert your local images into base64 format
async function toB64(imgPath) {
const data = fs.readFileSync(path.resolve(imgPath));
return Buffer.from(data).toString('base64');
}
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/gemini-2.5-pro";
const data = {
"messages": [
{
"role": "user",
"content" : "tell me a joke on cats"
},
{
"role": "assistant",
"content" : "here is a joke about cats..."
},
{
"role": "user",
"content" : "now a joke on dogs"
},
]
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
An array of objects containing the role and content
Could be "user", "assistant" or "system".
A string containing the user's query or the assistant's response.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Gemini 2.5 Pro: Multimodal AI Model
Edited by Segmind Team on October 27, 2025.
What is Gemini 2.5 Pro?
Gemini 2.5 Pro, developed by Google Cloud, is a highly sophisticated AI model designed for handling complex multimodal reasoning tasks. It is powered by the Vertex AI platform, which makes it proficient and versatile for processing and interpreting a myriad of data types, such as text, code, images, audio, and video, all at once. Therefore, its ability to synthesize different data formats and provide solutions for complex cross-domain problems makes it a valuable model for developers and enterprises.
Key Features of Gemini 2.5 Pro
- Multimodal Processing: It can seamlessly handle text, code, images, audio, and video inputs
- Large Context Windows: It can support extensive input sizes for comprehensive analysis
- Google Search Integration: It can provide enhanced response grounding through search capabilities
- Code Execution: It has a built-in ability to run and analyze code
- Function Calling: It is integrated with advanced API integration capabilities
- Structured Output: It can deliver organized, formatted responses
- Flexible Input Handling: It accepts text prompts and image inputs
Best Use Cases
- Content Creation: It is an ideal model to generate and optimize blog posts, articles, and marketing copy
- Software Development: It can perform code analysis, debugging, and documentation
- Data Analysis: It can promptly process and interpret complex datasets
- Visual Projects: It can execute image analysis and visual content strategy
- Enterprise Solutions: It can carry out large-scale data processing and problem-solving
- Research: It can analyze multiple data sources and synthesize findings
Prompt Tips and Output Quality
- Provide clear, specific prompts that outline your desired outcome
- Include proper context and vivid examples to guide the model
- For visual outputs, provide text prompts with high-quality images
- Use properly structured prompts for complex queries (e.g., bullet points or numbered lists)
- Leverage multimodal capabilities by providing different input types
- Divide complex tasks into smaller, targeted prompts for more precise results
FAQs
How is Gemini 2.5 Pro different from other AI models? Gemini 2.5 Pro is integrated with advanced multimodal capabilities, Google Search integration, and robust enterprise-grade features on the Vertex AI platform, making it a much more sophisticated model when compared to other options.
What types of inputs does Gemini 2.5 Pro accept? Gemini 2.5 Pro accepts text prompts and images as primary inputs, in addition to possessing the ability to process and analyze code, audio, and video content within its responses.
Can Gemini 2.5 Pro handle enterprise-scale tasks? Yes, it is an advanced AI model designed for enterprise use cases with large context windows and the ability to process complex, multi-format datasets.
**How can I optimize my prompts to achieve better results? **** To achieve better results, provide clear and specific instructions, offer relevant context, and utilize text and image inputs (when appropriate) for your use case.
Is Gemini 2.5 Pro available through API integration? Yes, it can be accessed through Google Cloud's Vertex AI platform and supports function calling for seamless API integration.
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