add endpoint to HF

packages/components/nodes/chatmodels/ChatHuggingFace/ChatHuggingFace.ts

@@ -1,6 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
-import { HFInput, HuggingFaceInference } from 'langchain/llms/hf'
+import { HFInput, HuggingFaceInference } from './core'
 
 class ChatHuggingFace_ChatModels implements INode {
     label: string
@@ -71,6 +71,15 @@ class ChatHuggingFace_ChatModels implements INode {
                 description: 'Frequency Penalty parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
+            },
+            {
+                label: 'Endpoint',
+                name: 'endpoint',
+                type: 'string',
+                placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2',
+                description: 'Using your own inference endpoint',
+                optional: true,
+                additionalParams: true
             }
         ]
     }
@@ -83,6 +92,7 @@ class ChatHuggingFace_ChatModels implements INode {
         const topP = nodeData.inputs?.topP as string
         const hfTopK = nodeData.inputs?.hfTopK as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
+        const endpoint = nodeData.inputs?.endpoint as string
 
         const obj: Partial<HFInput> = {
             model,
@@ -94,6 +104,7 @@ class ChatHuggingFace_ChatModels implements INode {
         if (topP) obj.topP = parseInt(topP, 10)
         if (hfTopK) obj.topK = parseInt(hfTopK, 10)
         if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
+        if (endpoint) obj.endpoint = endpoint
 
         const huggingFace = new HuggingFaceInference(obj)
         return huggingFace