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ai-chat

Unify chat completions across LLM providers via an OpenAI-compatible API.

13|1|Updated Mar 22, 2026
Search Tags:#llm#streaming#vision#api gateway#function calling#chat completions#openai-compatible
One-click install
npx skills add https://github.com/AceDataCloud/Skills --skill ai-chat-acedatacloud
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-chat
Source: https://github.com/AceDataCloud/Skills/tree/main/skills/ai-chat
Command: npx skills add https://github.com/AceDataCloud/Skills --skill ai-chat-acedatacloud

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the hassle of switching between multiple LLM providers by giving you a single OpenAI-compatible chat interface that can route to 50+ model options.

Core Features & Use Cases

  • Unified OpenAI-compatible gateway: Use one endpoint for chat completions across GPT, Claude, Gemini, Kimi, Grok, and more.
  • Streaming support: Receive incremental responses using stream for lower-latency UX.
  • Function calling and vision: Run tool/function calls and handle image+text prompts on multimodal-capable models.
  • Use case: Build an app that lets users choose different model backends (e.g., “fast”, “reasoning”, “multimodal”) without changing your client code.

Quick Start

Send a chat completion request to the unified endpoint by posting your model name and messages with your AceDataCloud API token.

Frequently Asked Questions about ai-chat

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use a single OpenAI-compatible API endpoint for multiple LLM providers?▼

A unified OpenAI-compatible API gateway routes chat completion requests to 50+ models like GPT, Claude, and Gemini using one AceDataCloud base URL and API token, eliminating provider-specific integrations.

Can I build a chat UI that switches between reasoning and multimodal models without changing client code?▼

Yes, an OpenAI-compatible chat completions gateway lets your app switch model backends like reasoning or multimodal by changing the model name parameter, keeping client code unchanged.

Does the unified chat completions API support streaming responses and function calling?▼

The unified chat completions API supports streaming for lower-latency responses and tool or function calling, allowing you to build interactive agents and tool-using assistants across multiple LLM providers.

How do I handle vision inputs with image and text prompts across different LLM families?▼

Multimodal-capable models accessible through the OpenAI-compatible endpoint process image and text prompts, enabling vision workflows across different model families without altering your request structure.

What is the best way to avoid provider lock-in when building an AI assistant with multiple models?▼

Using a unified OpenAI-compatible interface prevents provider lock-in by standardizing chat completions across 50+ models, allowing seamless backend substitution without rewriting application logic.

Do I need an AceDataCloud API token to access the unified LLM gateway?▼

Yes, an AceDataCloud API token is required to authenticate requests to the unified chat completions endpoint and route prompts to your selected model backend.

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