AI Providers
Last updated
Last updated
ServerAssistantAI supports a wide range of AI providers for both language models (LLMs) and embeddings.
Providers are configurable components that enable ServerAssistantAI's customizability and flexibility. They serve as the backbone of the plugin's ability to integrate with various AI services, giving server owners the power to tailor the AI assistant's capabilities to their specific needs.
ServerAssistantAI offers several ways to configure and extend its functionality through a flexible provider system for embedding models, chat models (LLMs), and question detection, including Built-in Providers (ready-to-use), Addon Providers (additional providers installed via addons), Pre-configured OpenAI-compatible Providers (built-in providers with predefined endpoint URLs), and Custom Providers with Custom Base URLs (integration with any OpenAI API-compatible service using a custom endpoint URL).
To configure a provider, simply specify its name and any required options in the config.yml
file using the following format:
Each provider has its own set of options. Some options are shared across providers, while others may have the same name but behave differently depending on the provider. The specific functionality and configuration are determined by the selected provider.
Provider | Type | Functionality | Pricing | Description |
---|---|---|---|---|
All providers that are not built-in or OpenAI variants require the installation of their respective addons, which are available for free.
With support for a diverse range of AI providers, ServerAssistantAI enables users to choose the models and services that best fit their needs and budget.
LLM & Embedding
Free & Paid
Provides access to Cohere's language and embedding models, with RAG capabilities to improve performance.
LLM & Embedding
Paid
Offers premium paid models like GPT-3.5-turbo and GPT-4.
LLM
Paid
Enables the use of Anthropic's Claude models for LLM functionality.
LLM & Embedding
Paid
Allows integration with Azure OpenAI Service for both LLM and embedding capabilities.
LLM & Embedding
Paid
Run the latest ML models with ease using DeepInfra's simple REST API.
LLM & Embedding
Paid
Fireworks.ai is a fast inference platform for serving generative AI models efficiently.
LLM
Free
Access industry-leading AI models directly on GitHub for free.
LLM & Embedding
Free & Paid
Provides access to Google's most advanced Gemini generative AI models.
LLM
Temporarily Free
Utilizes Groq's LPU (Language Processing Unit) Inference Engine for fast LLM inference.
LLM & Embedding
Free
Provides access to thousands of open-source models for free through the HuggingFace Inference API.
LLM
Paid
Kolank is an AI routing platform that connects to various models, ensuring high-quality responses.
LLM & Embedding
Self-hosted
A desktop app for running local models on your computer, supporting models from HuggingFace.
LLM & Embedding
Self-hosted
Open-source, OpenAI drop-in alternative REST API for local inferencing without a GPU.
LLM & Embedding
Paid
Integrates Mistral AI models for both LLM and embedding capabilities.
LLM & Embedding
Free & Paid
Offers reliable API access to GPT-4, Gemini 1.5, Llama 3B, and various other language and embedding models.
LLM
Paid
Harness the latest AI innovations with OctoAI's efficient, reliable, and customizable AI systems for your apps.
LLM
Self-hosted
Allows self-hosting of Ollama, a lightweight framework for running language models locally.
LLM
Self-hosted
Allows developers to run any open-source LLMs (Llama 3.1, Qwen2, Phi3 and more) or custom models.
LLM
Free & Paid
Standardized API for switching between models and providers, prioritizing price or performance.
LLM
Paid
Perplexity AI's API enables users to use Perplexity Models and Open-Source LLMs.
LLM & Embedding
Paid
Fast, cost-efficient, and scalable inference for open-source models like Llama-3.
LLM
Paid
Offers language models like Yi-1.5, delivering strong performance in instruction-following.
Custom
LLM &/or Embedding
Free or Paid
Allows integration with any OpenAI API-compatible service. Users can set up custom endpoints by specifying the base URL in the config.yml
file.