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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/gpt-5";
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.
GPT-5 – Advanced AI Agent Model
What is GPT-5?
GPT-5 represents a leap toward artificial general intelligence (AGI) by functioning as an AI agent that “thinks” and builds with integrated tools. Beyond text completion, GPT-5 orchestrates web searches, code interpreters, and side-effect actions in parallel, following structured guidance to solve complex engineering tasks. While its creative writing lags slightly behind GPT-4.5, it excels at automating workflows, generating production-ready code, and navigating multi-step problem-solving environments.
Key Features
- Agent-Based Reasoning: Chains tool calls (web search, code execution, data retrieval) to accomplish end-to-end tasks without manual orchestration.
- Parallel Tool Usage: Simultaneously invokes multiple plugins or interpreters, reducing round trips and increasing throughput on complex tasks.
- Structured Guidance Compliance: Adheres to developer-provided schemas, style guides, and validation rules to produce reliable, consistent outputs.
- Software Engineering Mastery: Excels at debugging, code generation, refactoring, and writing test suites across popular languages (Python, JavaScript, Go).
- Production-Ready Output: Generates deployable microservices, CI/CD scripts, and infrastructure-as-code templates with minimal post-processing.
Best Use Cases
- Automated Coding Assistants: Scaffold APIs, write unit tests, and optimize algorithms in real time.
- Intelligent Documentation: Auto-generate SDK docs, release notes, and interactive tutorials synchronized with code changes.
- Data Analysis Workflows: Ingest datasets, run statistical models or SQL queries via the code interpreter tool, and visualize results programmatically.
- DevOps Automation: Create deployment pipelines, configure containers, and manage cloud resources through scripted agent actions.
- Research & Prototyping: Rapidly iterate on prototypes by querying external data sources and synthesizing findings.
Prompt Tips and Output Quality
- Be Specific: Clearly define objectives and expected formats. E.g., “Generate a Flask API that…”
- Leverage Tools: Mention required tools by name (
web_search,code_interpreter) in your prompt to trigger agent capabilities. - Structured Prompts: Use bullet lists, JSON schemas, or function definitions to guide GPT-5’s output format.
- Optional Image Inputs: Attach high-resolution diagrams or screenshots via the
imageparameter to enrich context for technical explanations. - Iterate & Validate: Review generated code or actions, then instruct GPT-5 to refactor or optimize based on test results.
FAQs
Q: What is GPT-5 used for?
A: Automating end-to-end software tasks—from code generation and testing to deployment—while integrating web search and data tools.
Q: How does GPT-5 differ from GPT-4.5?
A: GPT-5 prioritizes agent-based workflows and parallel tool usage, delivering production-ready code more efficiently; creative writing is slightly less polished.
Q: Can GPT-5 generate production-ready applications?
A: Yes. It scaffolds code, writes tests, configures CI/CD, and follows your structured guidance to produce deployable artifacts.
Q: Does GPT-5 support creative writing?
A: It can draft narratives, but its strength lies in technical, agent-driven problem solving rather than imaginative prose.
Q: What input formats does GPT-5 accept?
A:
- prompt (string, required): text commands or questions.
- image (file, optional): diagrams or screenshots to add visual context.
Popular Models
