[image] Concerns over personal privacy with the AI plugin Discourse AI was built agnostic from AI providers since day one, so the admins can pick an AI provider that they trust with the data I’ve been struggling to set up Embeddings with Mistral AI, I suspect because Mistral requires a model t…

Try setting mistral-embed in the “Model name” field, that appears after you select “Provider” as OpenAI.

Thanks, that works :+1: I’m struggling to find out what would be the best tokenizer to use for this use case though. The Mixtral tokenizer is not selectable here. Do you have any suggestions?

Your post above token length according to some tokenizers: OpenAI: 45 Mixtral: 52 Gemini: 47 E5: 50 bge-large-en: 49 bge-m3: 50 mpnet: 49 Looks like Mistral-embed doesn’t differ much from the others. And since it supports a very large context window of 8k, you should be safe picking any and …

Looks like mistral-embed uses the same tokenizer as the first Mixtral model, and we already ship that anyway, so what do you think about enabling that tokenizer in the embeddings config page @Roman ?

Sure. I don’t see why not if it’s already there. This change will add it to the available options: FEATURE: Make Mixtral tokenizer available for embeddings main ← mixtral_tokenizer merged 03:01PM -…

How to implement Mistral with Embeddings

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Roman (Roman Rizzi) April 11, 2025, 2:44pm 6

Sure. I don’t see why not if it’s already there. This change will add it to the available options:

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Support for Mistral API Feature ai	1	536	December 26, 2023
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Warning of embedding `input must have less than 8192 tokens` with discourse ai Support ai	5	131	November 3, 2025
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How to implement Mistral with Embeddings

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