feat: add EmpirioLabs integration with ChatEmpirioLabs node

[Adam-Dalloul]

What

Adds a dedicated ChatEmpirioLabs Chat Model node and an EmpirioLabs API credential. EmpirioLabs is an OpenAI compatible inference platform that exposes frontier chat models (Qwen3.7, DeepSeek V4, GLM-5.1, Kimi K2.7 Code, MiniMax M3, and more) through a single API.

Changes

• packages/components/nodes/chatmodels/ChatEmpirioLabs/ChatEmpirioLabs.ts (new): wraps ChatOpenAI with configuration.baseURL = https://api.empiriolabs.ai/v1. Includes an asyncOptions Model Name loader (listModels) that lists chat-capable models live from GET /v1/models, with a static fallback when the catalog is unreachable. Streaming is on by default; Temperature, Max Tokens, Top P, Frequency/Presence Penalty, Timeout, Base Path, and Base Options are exposed (same surface as the existing Cerebras / OpenRouter nodes).
• packages/components/credentials/EmpirioLabsApi.credential.ts (new): single password field for the EmpirioLabs API key.
• packages/components/nodes/chatmodels/ChatEmpirioLabs/empiriolabs.svg (new): node icon.
• packages/server/src/utils/index.ts: register chatEmpirioLabs in the stream-valid Chat Models list so streaming works.

Notes

• Follows the existing aggregator integration pattern (ChatCometAPI feat: add CometAPI integration with ChatCometAPI node #5160, SambaNova Feature: Add SambaNova #4961, Cerebras Add Cerebras Node and Credential #3377).
• Authenticates with a standard Authorization: Bearer <key> (handled by ChatOpenAI from the credential). No vendor attribution / branding headers are sent.
• Model Name defaults to qwen3-7-plus; users can pick any model returned by the live catalog or type a slug.

Verification

• tsc --noEmit on packages/components: no errors from the new files (the only errors present are pre-existing missing-module errors in src/storage/* and src/utils.ts unrelated to this change).
• eslint and prettier --check pass on both new files.

Related docs

Companion documentation PR: FlowiseAI/FlowiseDocs#220

[gemini-code-assist]

Code Review

This pull request introduces support for EmpirioLabs chat models by adding the EmpirioLabsApi credential, the ChatEmpirioLabs chat model node, and its corresponding SVG icon, as well as enabling streaming support for the new node. Feedback on the implementation highlights two issues in ChatEmpirioLabs.ts: first, the listModels method should dynamically use the user-configured basepath instead of a hardcoded default URL; second, the optional temperature parameter should be parsed and assigned conditionally to prevent passing NaN to the underlying ChatOpenAI instance.

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[gemini-code-assist]

The listModels method currently queries the hardcoded DEFAULT_BASE_URL to fetch the model list. If a user configures a custom basepath (e.g., for a local proxy, a self-hosted gateway, or an alternative endpoint), the model loader will still attempt to fetch models from the default URL. This can result in fetching the wrong models or failing to fetch models entirely in restricted or air-gapped environments. We should retrieve and use the user-configured basepath from nodeData.inputs if available.

Suggested change

	async listModels(_: INodeData, __?: ICommonObject): Promise<INodeOptionsValue[]> {
	try {
	const response = await axios.get(`${DEFAULT_BASE_URL}/models`)
	async listModels(nodeData: INodeData, __?: ICommonObject): Promise<INodeOptionsValue[]> {
	try {
	const basePath = (nodeData.inputs?.basepath as string) || DEFAULT_BASE_URL
	const response = await axios.get(`${basePath}/models`)

[gemini-code-assist]

If temperature is not provided (since it is optional), parseFloat(temperature) will evaluate to NaN. Passing NaN as temperature to ChatOpenAI can cause API requests to fail or behave unexpectedly. It is safer to conditionally add temperature to the configuration object only if it is defined and not an empty string, using a loose equality check (!= null) to handle both null and undefined.

Suggested change

	const obj: ChatOpenAIFields = {
	temperature: parseFloat(temperature),
	model: modelName,
	apiKey: empirioLabsApiKey,
	openAIApiKey: empirioLabsApiKey,
	streaming: streaming ?? true
	}
	const obj: ChatOpenAIFields = {
	model: modelName,
	apiKey: empirioLabsApiKey,
	openAIApiKey: empirioLabsApiKey,
	streaming: streaming ?? true
	}
	if (temperature != null && temperature !== '') {
	obj.temperature = parseFloat(temperature)
	}

References

1. In JavaScript/TypeScript, use loose equality (== null) as a standard idiom for a 'nullish' check that covers both null and undefined.