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1 change: 1 addition & 0 deletions components/icons/providers/index.ts
Original file line number Diff line number Diff line change
Expand Up @@ -48,5 +48,6 @@ export { default as TraefikIcon } from './traefik'
export { default as TrueFoundryIcon } from './truefoundry'
export { default as VLLMIcon } from './vllm'
export { default as VultrIcon } from './vultr'
export { default as WallyIcon } from './wally'
export { default as WolframIcon } from './wolfram'
export { default as XAIIcon } from './xai'
13 changes: 13 additions & 0 deletions components/icons/providers/wally.tsx
Original file line number Diff line number Diff line change
@@ -0,0 +1,13 @@
import React from 'react'

export default function WallyIcon({ className, ...props }: React.SVGProps<SVGSVGElement>) {
return (
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" className={className} {...props}>
<path
fill="currentColor"
fillRule="evenodd"
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/>
</svg>
)
}
Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@
"truefoundry",
"vllm",
"vultrcloudinference",
"wally",
"xai"
]
}
50 changes: 50 additions & 0 deletions content/docs/configuration/librechat_yaml/ai_endpoints/wally.mdx
Original file line number Diff line number Diff line change
@@ -0,0 +1,50 @@
---
title: Wally
icon: Wally
description: Configure Wally as a custom endpoint in LibreChat.
---

Wally serves open-weight models such as GLM-5.3 Flash, DeepSeek V4.1 Flash, Kimi K3, and MiniMax M3 through an OpenAI-compatible API that you can add to LibreChat as a custom endpoint.

## Get an API key

Create a key from [Wally](https://www.runwally.com). Add it to your `.env` file:

```bash filename=".env"
WALLY_API_KEY=your-api-key
```

## Configuration

Add the endpoint to the `custom` list under `endpoints` in your `librechat.yaml`. If your file already has an `endpoints.custom` list, paste only the `- name:` entry into it, keeping the same indentation:

```yaml filename="librechat.yaml"
endpoints:
custom:
- name: "Wally"
apiKey: "${WALLY_API_KEY}"
baseURL: "https://inference.runanywhere.ai/v1"
models:
default:
- "glm-5.3-flash"
- "deepseek-v4.1-flash"
- "deepseek-v4.1-flash-fast"
- "deepseek-v4-flash-0731"
- "deepseek-v4-pro-fast"
- "glm-5.3-fast"
- "kimi-k3"
- "minimax-m3"
fetch: true
titleConvo: true
titleModel: "glm-5.3-flash"
modelDisplayLabel: "Wally"
```

## Notes

- With `fetch: true`, LibreChat loads the model list from Wally's `/v1/models` endpoint. The `default` array is only the initial selection.
- All eight models support tool calling and work with [Agents](/docs/features/agents).
- DeepSeek V4.1 Flash, DeepSeek V4.1 Flash (Fast), and Kimi K3 also accept image input.
- Thinking streams as the model's thought process. GLM-5.3 Flash, GLM-5.3 (Fast), and MiniMax M3 always think. The DeepSeek V4.1 models and Kimi K3 think by default, and `reasoning_effort: "none"` turns it off. DeepSeek V4 Pro (Fast) and DeepSeek V4 Flash 0731 think only when `reasoning_effort` asks for it.
- `addParams` applies to every model on the endpoint, and the always-thinking models reject `reasoning_effort: "none"`. To run without thinking, add a second endpoint that lists only the DeepSeek and Kimi models and set `addParams: { reasoning_effort: "none" }` on it.
- See the [Wally API docs](https://docs.runanywhere.ai/wally-cloud/api) and [pricing](https://www.runwally.com/pricing) for model details.
2 changes: 2 additions & 0 deletions lib/icons.tsx
Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,7 @@ import {
TrueFoundryIcon,
VLLMIcon,
VultrIcon,
WallyIcon,
WolframIcon,
XAIIcon,
} from '../components/icons/providers'
Expand Down Expand Up @@ -286,6 +287,7 @@ const icons: Record<string, ReactElement> = {
TrueFoundry: <TrueFoundryIcon />,
VLLM: <VLLMIcon />,
Vultr: <VultrIcon />,
Wally: <WallyIcon />,
Wolfram: <WolframIcon />,
XAI: <XAIIcon />,
}
Expand Down