Recommended Models

ServerAssistantAI supports a wide range of language models from different providers, including premium and free options, allowing server owners to choose the model that best fits their needs. Here's what we recommend, listed from most recommended to least.

Embedding Models

Embedding models are used to convert text data into numerical representations called embeddings. These embeddings capture the semantic meaning and relationships between different pieces of text. When the documents/ directory is updated, the content is sent to the embedding API. The resulting embeddings are saved to the cache/ directory, allowing the AI to find relevant context efficiently without reprocessing or making new API requests for each query.

ServerAssistantAI only sends information to the embedding API when changes are made to the document.txt file. If no changes are detected, the plugin will use the previously cached embeddings to reduce API calls.

Large Language Models

Large Language Models (LLMs) are powerful AI models that can understand and generate human-like text based on the input they receive. In ServerAssistantAI, when a user asks a question, the system retrieves relevant cached context from the embedding API results. This context, along with the user's question, is sent to the LLM to generate accurate and context-aware responses.

All Large Language Models and Embedding Models from the HuggingFace Inference API are completely free to use!

Please note that each model may have specific requirements or considerations for optimal performance. When selecting a model, consider factors such as:

  • System prompt configuration: Different models may require adjustments to the system prompt to achieve the best results. Check the documentation provided by the model's creators for tips on prompt engineering and configuration.

  • Open-source free LLMs have a higher chance of hallucinating compared to paid models.

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