Feature/Add multi query retriever (#2676)

add multi query retriever

packages/components/nodes/retrievers/MultiQueryRetriever/MultiQueryRetriever.ts

@@ -0,0 +1,83 @@
+import { PromptTemplate } from '@langchain/core/prompts'
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { MultiQueryRetriever } from 'langchain/retrievers/multi_query'
+
+const defaultPrompt = `You are an AI language model assistant. Your task is
+to generate 3 different versions of the given user
+question to retrieve relevant documents from a vector database.
+By generating multiple perspectives on the user question,
+your goal is to help the user overcome some of the limitations
+of distance-based similarity search.
+
+Provide these alternative questions separated by newlines between XML tags. For example:
+
+<questions>
+Question 1
+Question 2
+Question 3
+</questions>
+
+Original question: {question}`
+
+class MultiQueryRetriever_Retrievers implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Multi Query Retriever'
+        this.name = 'multiQueryRetriever'
+        this.version = 1.0
+        this.type = 'MultiQueryRetriever'
+        this.icon = 'multiQueryRetriever.svg'
+        this.category = 'Retrievers'
+        this.description = 'Generate multiple queries from different perspectives for a given user input query'
+        this.baseClasses = [this.type, 'BaseRetriever']
+        this.inputs = [
+            {
+                label: 'Vector Store',
+                name: 'vectorStore',
+                type: 'VectorStore'
+            },
+            {
+                label: 'Language Model',
+                name: 'model',
+                type: 'BaseLanguageModel'
+            },
+            {
+                label: 'Prompt',
+                name: 'modelPrompt',
+                description:
+                    'Prompt for the language model to generate alternative questions. Use {question} to refer to the original question',
+                type: 'string',
+                rows: 4,
+                default: defaultPrompt
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, input: string): Promise<any> {
+        const model = nodeData.inputs?.model
+        const vectorStore = nodeData.inputs?.vectorStore
+
+        let prompt = nodeData.inputs?.modelPrompt || (defaultPrompt as string)
+        prompt = prompt.replaceAll('{question}', input)
+
+        const retriever = MultiQueryRetriever.fromLLM({
+            llm: model,
+            retriever: vectorStore.asRetriever(),
+            verbose: process.env.DEBUG === 'true',
+            // @ts-ignore
+            prompt: PromptTemplate.fromTemplate(prompt)
+        })
+        return retriever
+    }
+}
+
+module.exports = { nodeClass: MultiQueryRetriever_Retrievers }

packages/components/nodes/retrievers/MultiQueryRetriever/multiQueryRetriever.svg

@@ -0,0 +1 @@
+<svg  xmlns="http://www.w3.org/2000/svg"  width="24"  height="24"  viewBox="0 0 24 24"  fill="none"  stroke="currentColor"  stroke-width="2"  stroke-linecap="round"  stroke-linejoin="round"  class="icon icon-tabler icons-tabler-outline icon-tabler-relation-one-to-many"><path stroke="none" d="M0 0h24v24H0z" fill="none"/><path d="M3 5m0 2a2 2 0 0 1 2 -2h14a2 2 0 0 1 2 2v10a2 2 0 0 1 -2 2h-14a2 2 0 0 1 -2 -2z" /><path d="M7 10h1v4" /><path d="M14 14v-4l3 4v-4" /><path d="M11 10.5l0 .01" /><path d="M11 13.5l0 .01" /></svg>