AI APIs REST API
Universal interface for AI model inference and deployment
AI APIs provides a unified REST interface for deploying and interacting with machine learning models across multiple frameworks and providers. Developers use it to integrate natural language processing, computer vision, and generative AI capabilities into applications without managing infrastructure. The API abstracts complexity while offering granular control over model parameters, making it ideal for production AI workflows.
https://api.aiapi.rest/v1
API Endpoints
| Method | Endpoint | Description |
|---|---|---|
| POST | /models/inference | Run inference on a deployed AI model with input data and parameters |
| GET | /models | List all available AI models with filtering and pagination |
| GET | /models/{modelId} | Retrieve detailed information about a specific AI model |
| POST | /models/deploy | Deploy a new AI model from supported frameworks or registries |
| DELETE | /models/{modelId} | Delete a deployed model and release its resources |
| POST | /embeddings | Generate vector embeddings from text or image inputs |
| POST | /chat/completions | Generate conversational responses using language models |
| POST | /images/generate | Create images from text prompts using generative models |
| POST | /transcriptions | Transcribe audio files to text using speech recognition models |
| POST | /classifications | Classify text or images into predefined categories |
| GET | /jobs/{jobId} | Check the status of an asynchronous inference job |
| POST | /models/{modelId}/finetune | Start a fine-tuning job for a base model with custom data |
| GET | /usage | Retrieve API usage statistics and token consumption metrics |
| POST | /batch/inference | Submit multiple inference requests for batch processing |
| GET | /models/{modelId}/metrics | Get performance metrics and latency statistics for a model |
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curl -X POST https://api.aiapi.rest/v1/models/inference \
-H 'Authorization: Bearer YOUR_API_TOKEN' \
-H 'Content-Type: application/json' \
-d '{
"model_id": "gpt-4-turbo",
"inputs": {
"prompt": "Explain quantum computing in simple terms",
"max_tokens": 150,
"temperature": 0.7
}
}'
Use AI APIs from Claude / Cursor / ChatGPT
Get a hosted MCP endpoint for AI APIs. Paste your AI APIs API key, copy back one URL, drop it into Claude Desktop, Cursor, or any AI client that supports remote MCP. Your AI calls AI APIs directly with your credentials — no local install, works on mobile.
ai_model_inference
Execute AI model inference with natural language prompts and return structured results for autonomous decision-making
ai_embedding_search
Generate embeddings and perform semantic search across vector databases to find contextually relevant information
ai_batch_processor
Process multiple AI tasks in parallel for efficient bulk operations like document analysis or image classification
ai_model_selector
Intelligently select the optimal AI model based on task requirements, latency constraints, and cost considerations
ai_finetune_manager
Manage model fine-tuning workflows including dataset preparation, training monitoring, and deployment automation
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