modelslab-chat-generation

Name: modelslab-chat-generation
Availability: InStock
Author: ModelsLab

Chat with 60+ LLMs through one OpenAI-compatible endpoint.

10|1|Updated Feb 4, 2026

Search Tags:#api #llm #streaming #chat #tool-calling #json-output #modelslab

Ready to run

npx skills add https://github.com/ModelsLab/skills --skill modelslab-chat-generation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: modelslab-chat-generation
Source: https://github.com/ModelsLab/skills/tree/main/chat-generation
Command: npx skills add https://github.com/ModelsLab/skills --skill modelslab-chat-generation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Connects your applications to 60+ LLMs through ModelsLab's OpenAI-compatible chat API, simplifying model access and testing across providers.

Core Features & Use Cases

Unified API: One OpenAI-compatible endpoint to chat with multiple models (DeepSeek, Meta Llama, Gemini, Qwen, Mistral).
Streaming & Tooling: Streaming responses, function/tool calling, and support for structured outputs to fit downstream apps.
Rapid Prototyping: Compare model behaviors, swap models, and build conversational AI experiences quickly.
Use Case: Build customer-support chatbots, virtual assistants, or research dashboards that switch models without code changes.

Quick Start

Call the chat completions endpoint with a user message to start a conversation.

Frequently Asked Questions about modelslab-chat-generation

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

FAQPage Schema

How do I chat with multiple LLMs using a single OpenAI-compatible API?▼

You can chat with multiple LLMs using a single OpenAI-compatible API by connecting your application to ModelsLab's unified chat endpoint, which routes requests to over 60 different models without requiring code changes.

Can I use OpenAI SDK compatibility to swap LLM providers like DeepSeek, Llama, and Gemini?▼

OpenAI SDK compatibility allows you to swap LLM providers like DeepSeek, Llama, and Gemini by pointing your existing OpenAI SDK configuration to the unified endpoint, enabling rapid model behavior comparison and provider switching.

What's the best way to build a conversational AI app with streaming responses and function calling?▼

The best way to build a conversational AI app with streaming responses and function calling is to use a unified chat API that supports tool calling and streaming, allowing you to integrate real-time virtual assistant features quickly.

How do I get structured JSON outputs from different LLM providers without changing my code?▼

To get structured JSON outputs from different LLM providers without changing your code, you can use the unified API's structured output feature, which standardizes the response format across all 60+ supported models.

Does the ModelsLab chat API support tool calling for customer support chatbots?▼

The ModelsLab chat API supports tool calling for customer support chatbots, enabling your conversational AI to execute external functions and retrieve real-time data through a single OpenAI-compatible endpoint.

When do I need a unified chat API endpoint for model comparison dashboards?▼

You need a unified chat API endpoint for model comparison dashboards when you want to evaluate the responses of models like Qwen and Mistral side-by-side without managing multiple provider SDKs and authentication flows.