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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.

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,
    
}'

👉 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.

TrustTrade AI: Verifiable Autonomous Trading Agent

TrustTrade AI: Verifiable Autonomous Trading Agent

TrustTrade AI is a trust-minimized autonomous trading agent designed to operate safely in decentralized financial environments. The system combines AI-driven decision-making with on-chain verification to ensure that every trading action is transparent, explainable, and auditable. The agent analyzes real-time market data using intelligent strategies powered by a FastAPI and LangChain-based backend. It generates structured trade decisions including reasoning, confidence scores, and risk assessments. These decisions are converted into signed trade intents using EIP-712 and executed through a secure risk-controlled routing mechanism on the blockchain. To address the core challenge of trust in AI systems, TrustTrade AI integrates ERC-8004 registries for identity, reputation, and validation. Each action performed by the agent is recorded as a verifiable signal, allowing the system to build a measurable on-chain reputation based on performance, risk management, and validation quality rather than opaque outputs. Beyond execution, the platform introduces an advanced explainability layer that provides step-by-step reasoning, “why” and “why not” analysis, and confidence metrics for every trade. A replay engine allows users to trace decisions across time, while a strategy comparison and simulation engine demonstrates performance against alternative approaches. The system also includes dynamic risk intelligence, where the agent adapts its trading behavior based on drawdown, volatility, and historical outcomes. This ensures capital protection and responsible automation, moving beyond profit-only optimization. By combining AI intelligence, blockchain verification, and user-centric transparency, TrustTrade AI transforms trading agents from black-box systems into accountable financial entities. This project demonstrates a scalable foundation for deploying trustworthy autonomous agents capable of managing real capital in decentralized ecosystems.

APEX Trader Autonomous Multi-Agent Trading System

APEX Trader Autonomous Multi-Agent Trading System

APEX Trader is a production-grade autonomous AI trading system built on a multi-agent architecture where five specialized agents work in a coordinated pipeline to analyze, validate, and execute cryptocurrency trades autonomously. The system consists of five agents: the Fundamental Agent analyzes NVT ratios, exchange net flows, and fair value models; the Technical Agent processes EMA crossovers, RSI, MACD, Bollinger Bands, and volume confirmation signals; the Sentiment Agent evaluates Fear & Greed Index and social sentiment scores; the Risk Agent enforces position sizing rules, portfolio heat limits, and R:R ratio thresholds; and the Backtester Agent validates every signal against historical win rates and Sharpe ratios before approval. Each trade requires multi-agent consensus above a configurable confidence threshold (72% day trading / 78% swing trading) before execution. Both day trading (5m–15m timeframes) and swing trading (4h–1D timeframes) with dynamically adjusted parameters — risk per trade, stop-loss placement, take-profit scaling, and trailing stops — all tuned to expert-level specifications. The APEX self-learning mechanism (evaluate-agent.py) continuously trains on closed trade P&L data, adjusting confidence thresholds autonomously. A self-healing daemon runs 24/7 with automatic error recovery and cooldown logic. The real-time dashboard (built on React/Next.js at port 3201 with a FastAPI backend at port 3202) provides a fully redesigned Agent Analysis Log where every stakeholder — trader, risk manager, operator, executive — gets layered information: trade identity, agent pipeline status, per-agent reasoning, strategy prediction with entry/SL/TP targets, course of action, and contextual RSS news feed — all grouped by trade, pair, or date. The project demonstrates how agentic AI systems can move beyond single-model decision making into coordinated multi-agent architectures that are transparent, auditable, and continuously self-improving.

ATATA (Autonomous Trustless AI Trading Agents)

ATATA (Autonomous Trustless AI Trading Agents)

This project represents a sophisticated convergence of decentralized finance (DeFi) and autonomous artificial intelligence, specifically designed to bring transparency and security to the world of algorithmic trading. At its core, the platform allows users to create, deploy, and monitor AI-powered trading agents that operate directly on Kraken. Unlike traditional "black box" trading bots, this system ensures that every action taken by an agent is fully verifiable on-chain through the ERC-8004 standard. By utilizing identity, reputation, and validation registries on Base L2, the project establishes a framework for Autonomous Trustless AI Trading Agents (ATATA), where each agent's performance and intent are anchored to a unique ERC-721 NFT. The technical infrastructure is anchored by the Kraken CLI Engine, a massive powerhouse featuring 134 specialized commands that cover everything from paper trading and spot markets to futures, forex, xStocks, and earn products. To facilitate seamless AI integration, it includes a built-in MCP (Model Context Protocol) server, allowing for high-level AI orchestration and complex decision-making. To protect capital in volatile markets, the platform implements a 7-Layer Risk System. This comprehensive safety net includes mission-critical features such as position sizing, daily loss limits, circuit breakers, leverage caps, concentration limits, rate limiting, and a dead man switch. This ensures that while the AI has the autonomy to execute trades, it operates within strict, user-defined safety parameters, combining the speed of AI with the security of blockchain-based validation.