AI/ML API AI technology page Top Builders

Explore the top contributors showcasing the highest number of AI/ML API AI technology page app submissions within our community.

AI/ML API

The AI/ML API offers a comprehensive suite of advanced AI functionalities designed to meet a variety of needs, including text completion, image inference, speech-to-text, and text-to-speech capabilities. The API is engineered for seamless integration, exceptional performance, and secure API key management, ensuring a smooth and reliable user experience.

General
CompanyAI/ML API
Repositoryhttps://github.com/aimlapi
Documentationhttps://docs.aimlapi.com/

Key Features

  • Inference: Effortlessly evaluate and deploy models for a range of tasks including text generation, image analysis, and more. This feature allows users to leverage the power of advanced AI to draw meaningful inferences from various data types.
  • API Key Management: Securely generate, manage, and monitor API keys to ensure the safety and integrity of interactions with the API. This feature provides robust security measures to protect data and operations.
  • Broad Model Selection: Gain access to a diverse array of models tailored to various AI applications, allowing selection of the most appropriate model for specific tasks. This extensive model library supports a wide range of functionalities to address different AI challenges.

Start building with AI/ML API

To start using the AI/ML API, follow the detailed Quickstart guide which provides step-by-step instructions to set up the development environment and initiate the first API call. This guide is designed to help users quickly familiarize themselves with the API's capabilities and start leveraging its powerful features.

Authentication

API Key Management

To use the AI/ML API, an API key is required. This key is essential for authenticating requests to the API. API keys can be easily generated and managed through the account dashboard, ensuring secure access to the API services.

Sending Your First Request

After setting up the environment and obtaining an API key, proceed to send the first request. The API documentation provides detailed instructions and examples to help craft requests and understand responses, enabling full utilization of the AI/ML API's functionalities.

Authorization: Bearer YOUR_API_KEY

curl --location --globoff 'api.aimlapi.com/chat/completions' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
    "model": "gpt-3.5-turbo",
    "messages": [
        {
            "role": "user",
            "content": "What's API?"
        },
    ],
    "max_tokens": 512,
    "stream": false,
    
}'

šŸ‘‰ Read the documentation to find out more: https://docs.aimlapi.com/

AI/ML API AI technology page Hackathon projects

Discover innovative solutions crafted with AI/ML API AI technology page, developed by our community members during our engaging hackathons.

TravelbuddyAI

TravelbuddyAI

TravelBuddyAI is a smart travel assistant web application designed to help users plan their air travel quickly, efficiently, and affordably. The main goal of this project is to simplify the flight search process and assist users with relevant travel-related information using the power of artificial intelligence and user-friendly web technologies. This application allows users to input natural language queries like ā€œWhat’s the cheapest flight from Lahore to Dubai?ā€, and it responds intelligently with helpful, personalized information such as flight options, estimated prices, and travel advice. The project aims to provide users with a smooth and engaging experience for finding the best travel routes, flight timings, and pricing, all from one simple interface. At the heart of TravelBuddyAI lies a question-answer-based system that responds to user queries using a Flask-powered backend. It interprets the user’s input and provides relevant travel recommendations. For example, users can ask about economy vs business class prices, the best time to book a flight, or compare airlines for a particular route. The frontend is developed using basic HTML, CSS, and JavaScript, ensuring a responsive and user-friendly interface. The user can type in their query in a text box and click on the ā€œAskā€ button. The application then communicates with the backend via an API and displays a response within seconds. Frontend: HTML5, CSS3, JavaScript Backend: Python with Flask API Communication: RESTful API using fetch (POST method) Cross-Origin Support: Flask-CORS to handle frontend-backend communication Templates: Jinja2 rendering for Flask

Multi-Agent Developer Tools

Multi-Agent Developer Tools

Multi-Agent AI VS Code Extension Multi-Agent AI is a comprehensive AI-powered development assistant that enhances your coding workflow by combining the capabilities of three specialized agents — all seamlessly integrated within Visual Studio Code. šŸš€ Core Agents 🧠 Coding Agent Delivers intelligent code completions, code quality analysis, performance optimization suggestions, and automated unit test generation. Supports: TypeScript, JavaScript, Python, Java, C++, C#, Go, Rust šŸ” Security Agent Performs thorough security scans, including static analysis, dependency scanning, secret detection, and compliance validation against industry standards like OWASP and PCI DSS. šŸ“„ Documentation Agent Generates various documentation types including: API docs Architectural overviews Troubleshooting guides Inline code explanations Output formats: Markdown, JSON, Plain Text šŸ”‘ Key Features ⚔ Real-time Assistance Inline code completion with contextual awareness and smart caching. šŸ›”ļø Multi-layered Analysis Identifies vulnerabilities, detects code quality issues, and provides actionable remediation suggestions. šŸ“š Intelligent Documentation Automatically generates comprehensive, context-aware documentation for your codebase. 🧭 Unified Interface Tabbed side panel for easy switching between agents. šŸ“¤ Export Capabilities Save outputs in .txt, .md, and .json formats. šŸ“Š Visual Feedback Includes color-coded status indicators, progress bars, and live updates from agents. āš™ļø Technical Integration Powered by Groq and BlackBox AI APIs Built-in error handling and retry logic Streaming response support for real-time agent interaction Configurable security rules and compliance standards Multi-provider AI backend support for enhanced stability 🧩 Setup Requirements Configure your Groq and BlackBox API keys in VS Code settings Compatible with major programming languages Fully integrated with VS Code's native UI and theme support