import{_ as t,o,c as r,ag as d}from"./chunks/framework.CvgP6Fyv.js";const p=JSON.parse('{"title":"LLM Provider and Model","description":"","frontmatter":{},"headers":[],"relativePath":"getting-started/provider-and-model.md","filePath":"getting-started/provider-and-model.md","lastUpdated":1772359263000}'),a={name:"getting-started/provider-and-model.md"};function i(n,e,l,s,g,h){return o(),r("div",null,[...e[0]||(e[0]=[d('
To use Memoh, you first need to configure at least one LLM Provider and at least one Model.
An LLM Provider represents a connection to an AI service (like OpenAI, Anthropic, or a self-hosted compatible API). It stores the base URL and authentication credentials.
https://api.openai.com/v1).A Model is a specific AI instance (like gpt-4o or text-embedding-3-small) that belongs to a Provider. Memoh distinguishes between Chat models (for conversation) and Embedding models (for memory search).
| Field | Required | Description |
|---|---|---|
| Type | Yes | chat for conversation, embedding for vector search. |
| Model ID | Yes | The exact identifier used by the provider (e.g., gpt-4o). |
| Name | No | A friendly display name (defaults to Model ID). |
| Client Type | Yes (Chat) | The API protocol: openai-responses, openai-completions, anthropic-messages, or google-generative-ai. |
| Input Modalities | Yes (Chat) | Capabilities supported: text (default), image, audio, video, file. |
| Supports Reasoning | No | Enable if the model supports internal reasoning steps (e.g., OpenAI o1). |
| Dimensions | Yes (Embed) | The vector size for embedding models (e.g., 1536). |
Now that you have configured your models, you can proceed to Create and Configure a Bot.
',20)])])}const m=t(a,[["render",i]]);export{p as __pageData,m as default};