LangBot/en/usage/models

---
title: "Configure Models (Models)"
---

## LangBot Models

LangBot Models is an official model service provided by LangBot. When you initialize a local instance with your LangBot Space account, available models will be automatically added to your instance without any configuration. You will receive a certain amount of free quota to get started quickly.

<img src="/images/zh/deploy/models/langbot_models.png" alt="langbot_models" />

For specific available models, please check [LangBot Space](https://space.langbot.app/models).

## Custom Models

You can also add models from other sources.

### LLM Model

Models will be used by pipelines to process messages. The first model you configure will be set as the model for the default pipeline.

![arch](/images/zh/deploy/models/arch.png)

You can add multiple models, and then select which model to use in the pipeline.

<img width="400px" src="/images/zh/deploy/models/model_config.png" alt="model_config" />

Enter these four parameters: `Model Name`, `Model Provider`, `Request URL`, and `API Key`, then submit.

For model capabilities, please choose according to the specific model characteristics:

- Visual Capability: Needs to be enabled to recognize images

- Function Calling: Needs to be enabled to use Agent tools in conversations

### Embedding Model

Embedding models are used to compute vector representations of messages. If you need to use knowledge bases, please configure this model.

<img width="400px" src="/images/zh/deploy/models/embedding_model.png" alt="embedding_model" />

Enter these four parameters: `Model Name`, `Model Provider`, `Request URL`, and `API Key`, then submit. After that, please configure the knowledge base to use this model.

### Using seekdb Built-in Embedding Model (Zero Configuration)
The system has integrated the official embedding model provided by seekdb, no parameters required.
- On the "Embedding Model" page, select "seekdb-built-in";
- Click "Save" to use it immediately;
- Then select this model in your knowledge base to take effect.

### Rerank Model

Rerank models re-score RAG retrieval results to significantly improve the precision of knowledge base answers. When a knowledge base returns multiple candidate documents, the rerank model uses a cross-encoder to precisely score each document's relevance to the query, selecting only the most relevant content.

Enter `Model Name` and select `Model Provider`, then submit. After that, select this model in your pipeline's "AI" configuration.

<Tip>
Rerank models are optional. Without one, knowledge base results are used in their original retrieval order. With a rerank model configured, results are re-scored and only the top-K most relevant results are kept.
</Tip>

**Supported providers and models:**

| Provider | Recommended Models | Notes |
| --- | --- | --- |
| [SiliconFlow](https://siliconflow.cn/) | `BAAI/bge-reranker-v2-m3`, `Qwen/Qwen3-Reranker-8B` | Recommended for China |
| [Jina](https://jina.ai/) | `jina-reranker-v2-base-multilingual` | Multilingual |
| [Cohere](https://cohere.com/) | `rerank-v3.5` | Industry leading |
| [Voyage AI](https://voyageai.com/) | `rerank-2.5` | |
| [GiteeAI](https://ai.gitee.com/) | `bge-reranker-v2-m3`, `Qwen3-Reranker-8B` | |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | `qwen3-rerank`, `gte-rerank` | Requires extra args, see below |
| [OpenRouter](https://openrouter.ai/) | `cohere/rerank-v3.5`, `cohere/rerank-4-pro` | Universal gateway |
| [302.AI](https://share.302.ai/SuTG99) | `jina-reranker-m0`, `qwen3-rerank` | |
| OpenAI Compatible | Any service supporting `/rerank` | Universal |

### Using Rerank Models with Aliyun Bailian

Aliyun Bailian's rerank API endpoint path differs from its LLM endpoint. You need to specify `rerank_url` in the model's **extra arguments**:

1. When adding a model, select the `Aliyun Bailian` provider
2. Enter the model name (e.g., `qwen3-rerank`)
3. Add an extra argument:
   - Key: `rerank_url`
   - Type: `string`
   - Value: `https://dashscope.aliyuncs.com/compatible-api/v1/reranks`

<Warning>
Other providers (SiliconFlow, Jina, Cohere, etc.) do not require extra arguments — they use the standard `/rerank` endpoint.
</Warning>