Updating of Type LLMCache to BaseCache and renaming vars for clarity

packages/components/nodes/chatmodels/AWSBedrock/AWSChatBedrock.ts

@@ -44,7 +44,7 @@ class AWSChatBedrock_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -138,7 +138,7 @@ class AWSChatBedrock_ChatModels implements INode {
         const iModel = nodeData.inputs?.model as string
         const iTemperature = nodeData.inputs?.temperature as string
         const iMax_tokens_to_sample = nodeData.inputs?.max_tokens_to_sample as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: BaseBedrockInput & BaseLLMParams = {
             region: iRegion,

packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI.ts

@@ -36,7 +36,7 @@ class AzureChatOpenAI_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -115,7 +115,7 @@ class AzureChatOpenAI_ChatModels implements INode {
         const presencePenalty = nodeData.inputs?.presencePenalty as string
         const timeout = nodeData.inputs?.timeout as string
         const streaming = nodeData.inputs?.streaming as boolean
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)

packages/components/nodes/chatmodels/Bittensor/Bittensor.ts

@@ -27,7 +27,7 @@ class Bittensor_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -42,7 +42,7 @@ class Bittensor_ChatModels implements INode {
 
     async init(nodeData: INodeData, _: string): Promise<any> {
         const system_prompt = nodeData.inputs?.system_prompt as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<BittensorInput> = {
             systemPrompt: system_prompt

packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts

@@ -35,7 +35,7 @@ class ChatAnthropic_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -143,7 +143,7 @@ class ChatAnthropic_ChatModels implements INode {
         const topP = nodeData.inputs?.topP as string
         const topK = nodeData.inputs?.topK as string
         const streaming = nodeData.inputs?.streaming as boolean
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const anthropicApiKey = getCredentialParam('anthropicApiKey', credentialData, nodeData)

packages/components/nodes/chatmodels/ChatGooglePaLM/ChatGooglePaLM.ts

@@ -34,7 +34,7 @@ class ChatGooglePaLM_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -103,7 +103,7 @@ class ChatGooglePaLM_ChatModels implements INode {
         const temperature = nodeData.inputs?.temperature as string
         const topP = nodeData.inputs?.topP as string
         const topK = nodeData.inputs?.topK as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)

packages/components/nodes/chatmodels/ChatGoogleVertexAI/ChatGoogleVertexAI.ts

@@ -38,7 +38,7 @@ class GoogleVertexAI_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -120,7 +120,7 @@ class GoogleVertexAI_ChatModels implements INode {
         const modelName = nodeData.inputs?.modelName as string
         const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
         const topP = nodeData.inputs?.topP as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: GoogleVertexAIChatInput<GoogleAuthOptions> = {
             temperature: parseFloat(temperature),

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

@@ -34,7 +34,7 @@ class ChatHuggingFace_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -109,7 +109,7 @@ class ChatHuggingFace_ChatModels implements INode {
         const hfTopK = nodeData.inputs?.hfTopK as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
         const endpoint = nodeData.inputs?.endpoint as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)

packages/components/nodes/chatmodels/ChatLocalAI/ChatLocalAI.ts

@@ -29,7 +29,7 @@ class ChatLocalAI_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -86,7 +86,7 @@ class ChatLocalAI_ChatModels implements INode {
         const topP = nodeData.inputs?.topP as string
         const timeout = nodeData.inputs?.timeout as string
         const basePath = nodeData.inputs?.basePath as string
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<OpenAIChatInput> & BaseLLMParams & { openAIApiKey?: string } = {
             temperature: parseFloat(temperature),

packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts

@@ -35,7 +35,7 @@ class ChatOpenAI_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -159,7 +159,7 @@ class ChatOpenAI_ChatModels implements INode {
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
 
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<OpenAIChatInput> & BaseLLMParams & { openAIApiKey?: string } = {
             temperature: parseFloat(temperature),

packages/components/nodes/chatmodels/ChatOpenAICustom/ChatOpenAICustom.ts

@@ -36,7 +36,7 @@ class ChatOpenAICustom_ChatModels implements INode {
             {
                 label: 'Cache',
                 name: 'cache',
-                type: 'LLMCache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -121,7 +121,7 @@ class ChatOpenAICustom_ChatModels implements INode {
         const streaming = nodeData.inputs?.streaming as boolean
         const basePath = nodeData.inputs?.basepath as string
         const baseOptions = nodeData.inputs?.baseOptions
-        const cache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)

packages/components/nodes/llms/AWSBedrock/AWSBedrock.ts

@@ -2,6 +2,8 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Inter
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { Bedrock } from 'langchain/llms/bedrock'
 import { BaseBedrockInput } from 'langchain/dist/util/bedrock'
+import { BaseCache } from 'langchain/schema'
+import { BaseLLMParams } from 'langchain/llms/base'
 
 /**
  * I had to run the following to build the component
@@ -39,6 +41,12 @@ class AWSBedrock_LLMs implements INode {
             optional: true
         }
         this.inputs = [
+            {
+                label: 'Cache',
+                name: 'cache',
+                type: 'BaseCache',
+                optional: true
+            },
             {
                 label: 'Region',
                 name: 'region',
@@ -130,8 +138,8 @@ class AWSBedrock_LLMs implements INode {
         const iModel = nodeData.inputs?.model as string
         const iTemperature = nodeData.inputs?.temperature as string
         const iMax_tokens_to_sample = nodeData.inputs?.max_tokens_to_sample as string
-
-        const obj: Partial<BaseBedrockInput> = {
+        const cache = nodeData.inputs?.cache as BaseCache
+        const obj: Partial<BaseBedrockInput> & BaseLLMParams = {
             model: iModel,
             region: iRegion,
             temperature: parseFloat(iTemperature),
@@ -157,6 +165,7 @@ class AWSBedrock_LLMs implements INode {
                 sessionToken: credentialApiSession
             }
         }
+        if (cache) obj.cache = cache
 
         const amazonBedrock = new Bedrock(obj)
         return amazonBedrock

packages/components/nodes/llms/Azure OpenAI/AzureOpenAI.ts

@@ -33,8 +33,8 @@ class AzureOpenAI_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -170,7 +170,7 @@ class AzureOpenAI_LLMs implements INode {
         const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
         const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
 
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<AzureOpenAIInput> & BaseLLMParams & Partial<OpenAIInput> = {
             temperature: parseFloat(temperature),
@@ -188,7 +188,7 @@ class AzureOpenAI_LLMs implements INode {
         if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
         if (timeout) obj.timeout = parseInt(timeout, 10)
         if (bestOf) obj.bestOf = parseInt(bestOf, 10)
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         const model = new OpenAI(obj)
         return model

packages/components/nodes/llms/Bittensor/Bittensor.ts

@@ -27,8 +27,8 @@ class Bittensor_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -52,13 +52,13 @@ class Bittensor_LLMs implements INode {
     async init(nodeData: INodeData, _: string): Promise<any> {
         const system_prompt = nodeData.inputs?.system_prompt as string
         const topResponses = Number(nodeData.inputs?.topResponses as number)
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<BittensorInput> & BaseLLMParams = {
             systemPrompt: system_prompt,
             topResponses: topResponses
         }
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         const model = new NIBittensorLLM(obj)
         return model

packages/components/nodes/llms/Cohere/Cohere.ts

@@ -33,8 +33,8 @@ class Cohere_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -92,7 +92,7 @@ class Cohere_LLMs implements INode {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
         const maxTokens = nodeData.inputs?.maxTokens as string
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const cohereApiKey = getCredentialParam('cohereApiKey', credentialData, nodeData)
 
@@ -103,7 +103,7 @@ class Cohere_LLMs implements INode {
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
         if (modelName) obj.model = modelName
         if (temperature) obj.temperature = parseFloat(temperature)
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
         const model = new Cohere(obj)
         return model
     }

packages/components/nodes/llms/GooglePaLM/GooglePaLM.ts

@@ -32,8 +32,8 @@ class GooglePaLM_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -132,7 +132,7 @@ class GooglePaLM_LLMs implements INode {
         const topP = nodeData.inputs?.topP as string
         const topK = nodeData.inputs?.topK as string
         const stopSequencesObj = nodeData.inputs?.stopSequencesObj
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
@@ -146,7 +146,7 @@ class GooglePaLM_LLMs implements INode {
         if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
         if (topP) obj.topP = parseFloat(topP)
         if (topK) obj.topK = parseFloat(topK)
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         let parsedStopSequences: any | undefined = undefined
         if (stopSequencesObj) {

packages/components/nodes/llms/GoogleVertexAI/GoogleVertexAI.ts

@@ -37,8 +37,8 @@ class GoogleVertexAI_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -127,7 +127,7 @@ class GoogleVertexAI_LLMs implements INode {
         const modelName = nodeData.inputs?.modelName as string
         const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
         const topP = nodeData.inputs?.topP as string
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<GoogleVertexAITextInput> = {
             temperature: parseFloat(temperature),
@@ -137,7 +137,7 @@ class GoogleVertexAI_LLMs implements INode {
 
         if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
         if (topP) obj.topP = parseFloat(topP)
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         const model = new GoogleVertexAI(obj)
         return model

packages/components/nodes/llms/HuggingFaceInference/HuggingFaceInference.ts

@@ -33,8 +33,8 @@ class HuggingFaceInference_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -113,7 +113,7 @@ class HuggingFaceInference_LLMs implements INode {
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
 
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<HFInput> = {
             model,
@@ -128,7 +128,7 @@ class HuggingFaceInference_LLMs implements INode {
         if (endpoint) obj.endpoint = endpoint
 
         const huggingFace = new HuggingFaceInference(obj)
-        if (llmCache) huggingFace.cache = llmCache
+        if (cache) huggingFace.cache = cache
 
         return huggingFace
     }

packages/components/nodes/llms/OpenAI/OpenAI.ts

@@ -34,8 +34,8 @@ class OpenAI_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -157,7 +157,7 @@ class OpenAI_LLMs implements INode {
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
 
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: Partial<OpenAIInput> & BaseLLMParams & { openAIApiKey?: string } = {
             temperature: parseFloat(temperature),
@@ -174,7 +174,7 @@ class OpenAI_LLMs implements INode {
         if (batchSize) obj.batchSize = parseInt(batchSize, 10)
         if (bestOf) obj.bestOf = parseInt(bestOf, 10)
 
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         let parsedBaseOptions: any | undefined = undefined
         if (baseOptions) {

packages/components/nodes/llms/Replicate/Replicate.ts

@@ -34,8 +34,8 @@ class Replicate_LLMs implements INode {
         this.inputs = [
             {
                 label: 'Cache',
-                name: 'llmCache',
-                type: 'LLMCache',
+                name: 'cache',
+                type: 'BaseCache',
                 optional: true
             },
             {
@@ -111,7 +111,7 @@ class Replicate_LLMs implements INode {
         const name = modelName.split(':')[0].split('/').pop()
         const org = modelName.split(':')[0].split('/')[0]
 
-        const llmCache = nodeData.inputs?.llmCache as BaseCache
+        const cache = nodeData.inputs?.cache as BaseCache
 
         const obj: ReplicateInput & BaseLLMParams = {
             model: `${org}/${name}:${version}`,
@@ -130,7 +130,7 @@ class Replicate_LLMs implements INode {
         }
         if (Object.keys(inputs).length) obj.input = inputs
 
-        if (llmCache) obj.cache = llmCache
+        if (cache) obj.cache = cache
 
         const model = new Replicate(obj)
         return model