{
    "description": "A chain that automatically picks an appropriate vector store retriever from multiple different vector databases",
    "usecases": ["Documents QnA"],
    "framework": ["Langchain"],
    "nodes": [
        {
            "width": 300,
            "height": 506,
            "id": "vectorStoreRetriever_0",
            "position": {
                "x": 712.9322670298264,
                "y": 860.5462810572917
            },
            "type": "customNode",
            "data": {
                "id": "vectorStoreRetriever_0",
                "label": "Vector Store Retriever",
                "version": 1,
                "name": "vectorStoreRetriever",
                "type": "VectorStoreRetriever",
                "baseClasses": ["VectorStoreRetriever"],
                "category": "Retrievers",
                "description": "Store vector store as retriever. Used with MultiRetrievalQAChain",
                "inputParams": [
                    {
                        "label": "Retriever Name",
                        "name": "name",
                        "type": "string",
                        "placeholder": "netflix movies",
                        "id": "vectorStoreRetriever_0-input-name-string"
                    },
                    {
                        "label": "Retriever Description",
                        "name": "description",
                        "type": "string",
                        "rows": 3,
                        "description": "Description of when to use the vector store retriever",
                        "placeholder": "Good for answering questions about netflix movies",
                        "id": "vectorStoreRetriever_0-input-description-string"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Vector Store",
                        "name": "vectorStore",
                        "type": "VectorStore",
                        "id": "vectorStoreRetriever_0-input-vectorStore-VectorStore"
                    }
                ],
                "inputs": {
                    "vectorStore": "{{supabase_0.data.instance}}",
                    "name": "aqua teen",
                    "description": "Good for answering questions about Aqua Teen Hunger Force theme song"
                },
                "outputAnchors": [
                    {
                        "id": "vectorStoreRetriever_0-output-vectorStoreRetriever-VectorStoreRetriever",
                        "name": "vectorStoreRetriever",
                        "label": "VectorStoreRetriever",
                        "type": "VectorStoreRetriever"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 712.9322670298264,
                "y": 860.5462810572917
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 429,
            "id": "multiRetrievalQAChain_0",
            "position": {
                "x": 1563.0150452201099,
                "y": 460.78375893303934
            },
            "type": "customNode",
            "data": {
                "id": "multiRetrievalQAChain_0",
                "label": "Multi Retrieval QA Chain",
                "version": 2,
                "name": "multiRetrievalQAChain",
                "type": "MultiRetrievalQAChain",
                "baseClasses": ["MultiRetrievalQAChain", "MultiRouteChain", "BaseChain", "BaseLangChain"],
                "category": "Chains",
                "description": "QA Chain that automatically picks an appropriate vector store from multiple retrievers",
                "inputParams": [
                    {
                        "label": "Return Source Documents",
                        "name": "returnSourceDocuments",
                        "type": "boolean",
                        "optional": true
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Language Model",
                        "name": "model",
                        "type": "BaseLanguageModel",
                        "id": "multiRetrievalQAChain_0-input-model-BaseLanguageModel"
                    },
                    {
                        "label": "Vector Store Retriever",
                        "name": "vectorStoreRetriever",
                        "type": "VectorStoreRetriever",
                        "list": true,
                        "id": "multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever"
                    },
                    {
                        "label": "Input Moderation",
                        "description": "Detect text that could generate harmful output and prevent it from being sent to the language model",
                        "name": "inputModeration",
                        "type": "Moderation",
                        "optional": true,
                        "list": true,
                        "id": "multiRetrievalQAChain_0-input-inputModeration-Moderation"
                    }
                ],
                "inputs": {
                    "inputModeration": "",
                    "model": "{{chatOpenAI_0.data.instance}}",
                    "vectorStoreRetriever": [
                        "{{vectorStoreRetriever_0.data.instance}}",
                        "{{vectorStoreRetriever_1.data.instance}}",
                        "{{vectorStoreRetriever_2.data.instance}}"
                    ]
                },
                "outputAnchors": [
                    {
                        "id": "multiRetrievalQAChain_0-output-multiRetrievalQAChain-MultiRetrievalQAChain|MultiRouteChain|BaseChain|BaseLangChain",
                        "name": "multiRetrievalQAChain",
                        "label": "MultiRetrievalQAChain",
                        "type": "MultiRetrievalQAChain | MultiRouteChain | BaseChain | BaseLangChain"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 1563.0150452201099,
                "y": 460.78375893303934
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 506,
            "id": "vectorStoreRetriever_1",
            "position": {
                "x": 711.4902931206071,
                "y": 315.2414600651632
            },
            "type": "customNode",
            "data": {
                "id": "vectorStoreRetriever_1",
                "label": "Vector Store Retriever",
                "version": 1,
                "name": "vectorStoreRetriever",
                "type": "VectorStoreRetriever",
                "baseClasses": ["VectorStoreRetriever"],
                "category": "Retrievers",
                "description": "Store vector store as retriever. Used with MultiRetrievalQAChain",
                "inputParams": [
                    {
                        "label": "Retriever Name",
                        "name": "name",
                        "type": "string",
                        "placeholder": "netflix movies",
                        "id": "vectorStoreRetriever_1-input-name-string"
                    },
                    {
                        "label": "Retriever Description",
                        "name": "description",
                        "type": "string",
                        "rows": 3,
                        "description": "Description of when to use the vector store retriever",
                        "placeholder": "Good for answering questions about netflix movies",
                        "id": "vectorStoreRetriever_1-input-description-string"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Vector Store",
                        "name": "vectorStore",
                        "type": "VectorStore",
                        "id": "vectorStoreRetriever_1-input-vectorStore-VectorStore"
                    }
                ],
                "inputs": {
                    "vectorStore": "{{chroma_0.data.instance}}",
                    "name": "mst3k",
                    "description": "Good for answering questions about Mystery Science Theater 3000 theme song"
                },
                "outputAnchors": [
                    {
                        "id": "vectorStoreRetriever_1-output-vectorStoreRetriever-VectorStoreRetriever",
                        "name": "vectorStoreRetriever",
                        "label": "VectorStoreRetriever",
                        "type": "VectorStoreRetriever"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 711.4902931206071,
                "y": 315.2414600651632
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 506,
            "id": "vectorStoreRetriever_2",
            "position": {
                "x": 706.0716220151372,
                "y": -217.51566869136752
            },
            "type": "customNode",
            "data": {
                "id": "vectorStoreRetriever_2",
                "label": "Vector Store Retriever",
                "version": 1,
                "name": "vectorStoreRetriever",
                "type": "VectorStoreRetriever",
                "baseClasses": ["VectorStoreRetriever"],
                "category": "Retrievers",
                "description": "Store vector store as retriever. Used with MultiRetrievalQAChain",
                "inputParams": [
                    {
                        "label": "Retriever Name",
                        "name": "name",
                        "type": "string",
                        "placeholder": "netflix movies",
                        "id": "vectorStoreRetriever_2-input-name-string"
                    },
                    {
                        "label": "Retriever Description",
                        "name": "description",
                        "type": "string",
                        "rows": 3,
                        "description": "Description of when to use the vector store retriever",
                        "placeholder": "Good for answering questions about netflix movies",
                        "id": "vectorStoreRetriever_2-input-description-string"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Vector Store",
                        "name": "vectorStore",
                        "type": "VectorStore",
                        "id": "vectorStoreRetriever_2-input-vectorStore-VectorStore"
                    }
                ],
                "inputs": {
                    "vectorStore": "{{pinecone_0.data.instance}}",
                    "name": "animaniacs",
                    "description": "Good for answering questions about Animaniacs theme song"
                },
                "outputAnchors": [
                    {
                        "id": "vectorStoreRetriever_2-output-vectorStoreRetriever-VectorStoreRetriever",
                        "name": "vectorStoreRetriever",
                        "label": "VectorStoreRetriever",
                        "type": "VectorStoreRetriever"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 706.0716220151372,
                "y": -217.51566869136752
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 424,
            "id": "openAIEmbeddings_0",
            "position": {
                "x": -212.46977797044045,
                "y": 252.45726960585722
            },
            "type": "customNode",
            "data": {
                "id": "openAIEmbeddings_0",
                "label": "OpenAI Embeddings",
                "version": 4,
                "name": "openAIEmbeddings",
                "type": "OpenAIEmbeddings",
                "baseClasses": ["OpenAIEmbeddings", "Embeddings"],
                "category": "Embeddings",
                "description": "OpenAI API to generate embeddings for a given text",
                "inputParams": [
                    {
                        "label": "Connect Credential",
                        "name": "credential",
                        "type": "credential",
                        "credentialNames": ["openAIApi"],
                        "id": "openAIEmbeddings_0-input-credential-credential"
                    },
                    {
                        "label": "Model Name",
                        "name": "modelName",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "default": "text-embedding-ada-002",
                        "id": "openAIEmbeddings_0-input-modelName-asyncOptions"
                    },
                    {
                        "label": "Strip New Lines",
                        "name": "stripNewLines",
                        "type": "boolean",
                        "optional": true,
                        "additionalParams": true,
                        "id": "openAIEmbeddings_0-input-stripNewLines-boolean"
                    },
                    {
                        "label": "Batch Size",
                        "name": "batchSize",
                        "type": "number",
                        "optional": true,
                        "additionalParams": true,
                        "id": "openAIEmbeddings_0-input-batchSize-number"
                    },
                    {
                        "label": "Timeout",
                        "name": "timeout",
                        "type": "number",
                        "optional": true,
                        "additionalParams": true,
                        "id": "openAIEmbeddings_0-input-timeout-number"
                    },
                    {
                        "label": "BasePath",
                        "name": "basepath",
                        "type": "string",
                        "optional": true,
                        "additionalParams": true,
                        "id": "openAIEmbeddings_0-input-basepath-string"
                    },
                    {
                        "label": "Dimensions",
                        "name": "dimensions",
                        "type": "number",
                        "optional": true,
                        "additionalParams": true,
                        "id": "openAIEmbeddings_0-input-dimensions-number"
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "modelName": "text-embedding-ada-002",
                    "stripNewLines": "",
                    "batchSize": "",
                    "timeout": "",
                    "basepath": "",
                    "dimensions": ""
                },
                "outputAnchors": [
                    {
                        "id": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
                        "name": "openAIEmbeddings",
                        "label": "OpenAIEmbeddings",
                        "description": "OpenAI API to generate embeddings for a given text",
                        "type": "OpenAIEmbeddings | Embeddings"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": -212.46977797044045,
                "y": 252.45726960585722
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 670,
            "id": "chatOpenAI_0",
            "position": {
                "x": 1166.929741805626,
                "y": -297.9691758089252
            },
            "type": "customNode",
            "data": {
                "id": "chatOpenAI_0",
                "label": "ChatOpenAI",
                "version": 6,
                "name": "chatOpenAI",
                "type": "ChatOpenAI",
                "baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "Runnable"],
                "category": "Chat Models",
                "description": "Wrapper around OpenAI large language models that use the Chat endpoint",
                "inputParams": [
                    {
                        "label": "Connect Credential",
                        "name": "credential",
                        "type": "credential",
                        "credentialNames": ["openAIApi"],
                        "id": "chatOpenAI_0-input-credential-credential"
                    },
                    {
                        "label": "Model Name",
                        "name": "modelName",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "default": "gpt-3.5-turbo",
                        "id": "chatOpenAI_0-input-modelName-options"
                    },
                    {
                        "label": "Temperature",
                        "name": "temperature",
                        "type": "number",
                        "step": 0.1,
                        "default": 0.9,
                        "optional": true,
                        "id": "chatOpenAI_0-input-temperature-number"
                    },
                    {
                        "label": "Max Tokens",
                        "name": "maxTokens",
                        "type": "number",
                        "step": 1,
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-maxTokens-number"
                    },
                    {
                        "label": "Top Probability",
                        "name": "topP",
                        "type": "number",
                        "step": 0.1,
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-topP-number"
                    },
                    {
                        "label": "Frequency Penalty",
                        "name": "frequencyPenalty",
                        "type": "number",
                        "step": 0.1,
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-frequencyPenalty-number"
                    },
                    {
                        "label": "Presence Penalty",
                        "name": "presencePenalty",
                        "type": "number",
                        "step": 0.1,
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-presencePenalty-number"
                    },
                    {
                        "label": "Timeout",
                        "name": "timeout",
                        "type": "number",
                        "step": 1,
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-timeout-number"
                    },
                    {
                        "label": "BasePath",
                        "name": "basepath",
                        "type": "string",
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-basepath-string"
                    },
                    {
                        "label": "BaseOptions",
                        "name": "baseOptions",
                        "type": "json",
                        "optional": true,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-baseOptions-json"
                    },
                    {
                        "label": "Allow Image Uploads",
                        "name": "allowImageUploads",
                        "type": "boolean",
                        "description": "Automatically uses gpt-4-vision-preview when image is being uploaded from chat. Only works with LLMChain, Conversation Chain, ReAct Agent, and Conversational Agent",
                        "default": false,
                        "optional": true,
                        "id": "chatOpenAI_0-input-allowImageUploads-boolean"
                    },
                    {
                        "label": "Image Resolution",
                        "description": "This parameter controls the resolution in which the model views the image.",
                        "name": "imageResolution",
                        "type": "options",
                        "options": [
                            {
                                "label": "Low",
                                "name": "low"
                            },
                            {
                                "label": "High",
                                "name": "high"
                            },
                            {
                                "label": "Auto",
                                "name": "auto"
                            }
                        ],
                        "default": "low",
                        "optional": false,
                        "additionalParams": true,
                        "id": "chatOpenAI_0-input-imageResolution-options"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Cache",
                        "name": "cache",
                        "type": "BaseCache",
                        "optional": true,
                        "id": "chatOpenAI_0-input-cache-BaseCache"
                    }
                ],
                "inputs": {
                    "cache": "",
                    "modelName": "gpt-3.5-turbo",
                    "temperature": 0.9,
                    "maxTokens": "",
                    "topP": "",
                    "frequencyPenalty": "",
                    "presencePenalty": "",
                    "timeout": "",
                    "basepath": "",
                    "baseOptions": "",
                    "allowImageUploads": true,
                    "imageResolution": "low"
                },
                "outputAnchors": [
                    {
                        "id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
                        "name": "chatOpenAI",
                        "label": "ChatOpenAI",
                        "type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 1166.929741805626,
                "y": -297.9691758089252
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 606,
            "id": "pinecone_0",
            "position": {
                "x": 268.04147939086755,
                "y": -407.5681206851249
            },
            "type": "customNode",
            "data": {
                "id": "pinecone_0",
                "label": "Pinecone",
                "version": 3,
                "name": "pinecone",
                "type": "Pinecone",
                "baseClasses": ["Pinecone", "VectorStoreRetriever", "BaseRetriever"],
                "category": "Vector Stores",
                "description": "Upsert embedded data and perform similarity or mmr search using Pinecone, a leading fully managed hosted vector database",
                "inputParams": [
                    {
                        "label": "Connect Credential",
                        "name": "credential",
                        "type": "credential",
                        "credentialNames": ["pineconeApi"],
                        "id": "pinecone_0-input-credential-credential"
                    },
                    {
                        "label": "Pinecone Index",
                        "name": "pineconeIndex",
                        "type": "string",
                        "id": "pinecone_0-input-pineconeIndex-string"
                    },
                    {
                        "label": "Pinecone Namespace",
                        "name": "pineconeNamespace",
                        "type": "string",
                        "placeholder": "my-first-namespace",
                        "additionalParams": true,
                        "optional": true,
                        "id": "pinecone_0-input-pineconeNamespace-string"
                    },
                    {
                        "label": "Pinecone Metadata Filter",
                        "name": "pineconeMetadataFilter",
                        "type": "json",
                        "optional": true,
                        "additionalParams": true,
                        "id": "pinecone_0-input-pineconeMetadataFilter-json"
                    },
                    {
                        "label": "Top K",
                        "name": "topK",
                        "description": "Number of top results to fetch. Default to 4",
                        "placeholder": "4",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "pinecone_0-input-topK-number"
                    },
                    {
                        "label": "Search Type",
                        "name": "searchType",
                        "type": "options",
                        "default": "similarity",
                        "options": [
                            {
                                "label": "Similarity",
                                "name": "similarity"
                            },
                            {
                                "label": "Max Marginal Relevance",
                                "name": "mmr"
                            }
                        ],
                        "additionalParams": true,
                        "optional": true,
                        "id": "pinecone_0-input-searchType-options"
                    },
                    {
                        "label": "Fetch K (for MMR Search)",
                        "name": "fetchK",
                        "description": "Number of initial documents to fetch for MMR reranking. Default to 20. Used only when the search type is MMR",
                        "placeholder": "20",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "pinecone_0-input-fetchK-number"
                    },
                    {
                        "label": "Lambda (for MMR Search)",
                        "name": "lambda",
                        "description": "Number between 0 and 1 that determines the degree of diversity among the results, where 0 corresponds to maximum diversity and 1 to minimum diversity. Used only when the search type is MMR",
                        "placeholder": "0.5",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "pinecone_0-input-lambda-number"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Document",
                        "name": "document",
                        "type": "Document",
                        "list": true,
                        "optional": true,
                        "id": "pinecone_0-input-document-Document"
                    },
                    {
                        "label": "Embeddings",
                        "name": "embeddings",
                        "type": "Embeddings",
                        "id": "pinecone_0-input-embeddings-Embeddings"
                    },
                    {
                        "label": "Record Manager",
                        "name": "recordManager",
                        "type": "RecordManager",
                        "description": "Keep track of the record to prevent duplication",
                        "optional": true,
                        "id": "pinecone_0-input-recordManager-RecordManager"
                    }
                ],
                "inputs": {
                    "document": "",
                    "embeddings": "{{openAIEmbeddings_0.data.instance}}",
                    "recordManager": "",
                    "pineconeIndex": "",
                    "pineconeNamespace": "",
                    "pineconeMetadataFilter": "",
                    "topK": "",
                    "searchType": "similarity",
                    "fetchK": "",
                    "lambda": ""
                },
                "outputAnchors": [
                    {
                        "name": "output",
                        "label": "Output",
                        "type": "options",
                        "description": "",
                        "options": [
                            {
                                "id": "pinecone_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
                                "name": "retriever",
                                "label": "Pinecone Retriever",
                                "description": "",
                                "type": "Pinecone | VectorStoreRetriever | BaseRetriever"
                            },
                            {
                                "id": "pinecone_0-output-vectorStore-Pinecone|VectorStore",
                                "name": "vectorStore",
                                "label": "Pinecone Vector Store",
                                "description": "",
                                "type": "Pinecone | VectorStore"
                            }
                        ],
                        "default": "retriever"
                    }
                ],
                "outputs": {
                    "output": "vectorStore"
                },
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 268.04147939086755,
                "y": -407.5681206851249
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 704,
            "id": "chroma_0",
            "position": {
                "x": 271.26687710753146,
                "y": 240.7980496352519
            },
            "type": "customNode",
            "data": {
                "id": "chroma_0",
                "label": "Chroma",
                "version": 2,
                "name": "chroma",
                "type": "Chroma",
                "baseClasses": ["Chroma", "VectorStoreRetriever", "BaseRetriever"],
                "category": "Vector Stores",
                "description": "Upsert embedded data and perform similarity search upon query using Chroma, an open-source embedding database",
                "inputParams": [
                    {
                        "label": "Connect Credential",
                        "name": "credential",
                        "type": "credential",
                        "description": "Only needed if you have chroma on cloud services with X-Api-key",
                        "optional": true,
                        "credentialNames": ["chromaApi"],
                        "id": "chroma_0-input-credential-credential"
                    },
                    {
                        "label": "Collection Name",
                        "name": "collectionName",
                        "type": "string",
                        "id": "chroma_0-input-collectionName-string"
                    },
                    {
                        "label": "Chroma URL",
                        "name": "chromaURL",
                        "type": "string",
                        "optional": true,
                        "id": "chroma_0-input-chromaURL-string"
                    },
                    {
                        "label": "Chroma Metadata Filter",
                        "name": "chromaMetadataFilter",
                        "type": "json",
                        "optional": true,
                        "additionalParams": true,
                        "id": "chroma_0-input-chromaMetadataFilter-json"
                    },
                    {
                        "label": "Top K",
                        "name": "topK",
                        "description": "Number of top results to fetch. Default to 4",
                        "placeholder": "4",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "chroma_0-input-topK-number"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Document",
                        "name": "document",
                        "type": "Document",
                        "list": true,
                        "optional": true,
                        "id": "chroma_0-input-document-Document"
                    },
                    {
                        "label": "Embeddings",
                        "name": "embeddings",
                        "type": "Embeddings",
                        "id": "chroma_0-input-embeddings-Embeddings"
                    },
                    {
                        "label": "Record Manager",
                        "name": "recordManager",
                        "type": "RecordManager",
                        "description": "Keep track of the record to prevent duplication",
                        "optional": true,
                        "id": "chroma_0-input-recordManager-RecordManager"
                    }
                ],
                "inputs": {
                    "document": "",
                    "embeddings": "{{openAIEmbeddings_0.data.instance}}",
                    "recordManager": "",
                    "collectionName": "",
                    "chromaURL": "",
                    "chromaMetadataFilter": "",
                    "topK": ""
                },
                "outputAnchors": [
                    {
                        "name": "output",
                        "label": "Output",
                        "type": "options",
                        "description": "",
                        "options": [
                            {
                                "id": "chroma_0-output-retriever-Chroma|VectorStoreRetriever|BaseRetriever",
                                "name": "retriever",
                                "label": "Chroma Retriever",
                                "description": "",
                                "type": "Chroma | VectorStoreRetriever | BaseRetriever"
                            },
                            {
                                "id": "chroma_0-output-vectorStore-Chroma|VectorStore",
                                "name": "vectorStore",
                                "label": "Chroma Vector Store",
                                "description": "",
                                "type": "Chroma | VectorStore"
                            }
                        ],
                        "default": "retriever"
                    }
                ],
                "outputs": {
                    "output": "vectorStore"
                },
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 271.26687710753146,
                "y": 240.7980496352519
            },
            "dragging": false
        },
        {
            "width": 300,
            "height": 803,
            "id": "supabase_0",
            "position": {
                "x": 274.75982285806055,
                "y": 982.5186034037372
            },
            "type": "customNode",
            "data": {
                "id": "supabase_0",
                "label": "Supabase",
                "version": 4,
                "name": "supabase",
                "type": "Supabase",
                "baseClasses": ["Supabase", "VectorStoreRetriever", "BaseRetriever"],
                "category": "Vector Stores",
                "description": "Upsert embedded data and perform similarity or mmr search upon query using Supabase via pgvector extension",
                "inputParams": [
                    {
                        "label": "Connect Credential",
                        "name": "credential",
                        "type": "credential",
                        "credentialNames": ["supabaseApi"],
                        "id": "supabase_0-input-credential-credential"
                    },
                    {
                        "label": "Supabase Project URL",
                        "name": "supabaseProjUrl",
                        "type": "string",
                        "id": "supabase_0-input-supabaseProjUrl-string"
                    },
                    {
                        "label": "Table Name",
                        "name": "tableName",
                        "type": "string",
                        "id": "supabase_0-input-tableName-string"
                    },
                    {
                        "label": "Query Name",
                        "name": "queryName",
                        "type": "string",
                        "id": "supabase_0-input-queryName-string"
                    },
                    {
                        "label": "Supabase Metadata Filter",
                        "name": "supabaseMetadataFilter",
                        "type": "json",
                        "optional": true,
                        "additionalParams": true,
                        "id": "supabase_0-input-supabaseMetadataFilter-json"
                    },
                    {
                        "label": "Supabase RPC Filter",
                        "name": "supabaseRPCFilter",
                        "type": "string",
                        "rows": 4,
                        "placeholder": "filter(\"metadata->a::int\", \"gt\", 5)\n.filter(\"metadata->c::int\", \"gt\", 7)\n.filter(\"metadata->>stuff\", \"eq\", \"right\");",
                        "description": "Query builder-style filtering. If this is set, will override the metadata filter. Refer <a href=\"https://js.langchain.com/v0.1/docs/integrations/vectorstores/supabase/#metadata-query-builder-filtering\" target=\"_blank\">here</a> for more information",
                        "optional": true,
                        "additionalParams": true,
                        "id": "supabase_0-input-supabaseRPCFilter-string"
                    },
                    {
                        "label": "Top K",
                        "name": "topK",
                        "description": "Number of top results to fetch. Default to 4",
                        "placeholder": "4",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "supabase_0-input-topK-number"
                    },
                    {
                        "label": "Search Type",
                        "name": "searchType",
                        "type": "options",
                        "default": "similarity",
                        "options": [
                            {
                                "label": "Similarity",
                                "name": "similarity"
                            },
                            {
                                "label": "Max Marginal Relevance",
                                "name": "mmr"
                            }
                        ],
                        "additionalParams": true,
                        "optional": true,
                        "id": "supabase_0-input-searchType-options"
                    },
                    {
                        "label": "Fetch K (for MMR Search)",
                        "name": "fetchK",
                        "description": "Number of initial documents to fetch for MMR reranking. Default to 20. Used only when the search type is MMR",
                        "placeholder": "20",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "supabase_0-input-fetchK-number"
                    },
                    {
                        "label": "Lambda (for MMR Search)",
                        "name": "lambda",
                        "description": "Number between 0 and 1 that determines the degree of diversity among the results, where 0 corresponds to maximum diversity and 1 to minimum diversity. Used only when the search type is MMR",
                        "placeholder": "0.5",
                        "type": "number",
                        "additionalParams": true,
                        "optional": true,
                        "id": "supabase_0-input-lambda-number"
                    }
                ],
                "inputAnchors": [
                    {
                        "label": "Document",
                        "name": "document",
                        "type": "Document",
                        "list": true,
                        "optional": true,
                        "id": "supabase_0-input-document-Document"
                    },
                    {
                        "label": "Embeddings",
                        "name": "embeddings",
                        "type": "Embeddings",
                        "id": "supabase_0-input-embeddings-Embeddings"
                    },
                    {
                        "label": "Record Manager",
                        "name": "recordManager",
                        "type": "RecordManager",
                        "description": "Keep track of the record to prevent duplication",
                        "optional": true,
                        "id": "supabase_0-input-recordManager-RecordManager"
                    }
                ],
                "inputs": {
                    "document": "",
                    "embeddings": "{{openAIEmbeddings_0.data.instance}}",
                    "recordManager": "",
                    "supabaseProjUrl": "",
                    "tableName": "",
                    "queryName": "",
                    "supabaseMetadataFilter": "",
                    "supabaseRPCFilter": "",
                    "topK": "",
                    "searchType": "similarity",
                    "fetchK": "",
                    "lambda": ""
                },
                "outputAnchors": [
                    {
                        "name": "output",
                        "label": "Output",
                        "type": "options",
                        "description": "",
                        "options": [
                            {
                                "id": "supabase_0-output-retriever-Supabase|VectorStoreRetriever|BaseRetriever",
                                "name": "retriever",
                                "label": "Supabase Retriever",
                                "description": "",
                                "type": "Supabase | VectorStoreRetriever | BaseRetriever"
                            },
                            {
                                "id": "supabase_0-output-vectorStore-Supabase|VectorStore",
                                "name": "vectorStore",
                                "label": "Supabase Vector Store",
                                "description": "",
                                "type": "Supabase | VectorStore"
                            }
                        ],
                        "default": "retriever"
                    }
                ],
                "outputs": {
                    "output": "vectorStore"
                },
                "selected": false
            },
            "selected": false,
            "positionAbsolute": {
                "x": 274.75982285806055,
                "y": 982.5186034037372
            },
            "dragging": false
        },
        {
            "id": "stickyNote_0",
            "position": {
                "x": 1564.4709721348295,
                "y": 121.26040803337389
            },
            "type": "stickyNote",
            "data": {
                "id": "stickyNote_0",
                "label": "Sticky Note",
                "version": 2,
                "name": "stickyNote",
                "type": "StickyNote",
                "baseClasses": ["StickyNote"],
                "tags": ["Utilities"],
                "category": "Utilities",
                "description": "Add a sticky note",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNote_0-input-note-string"
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "Multi Retrieval QA Chain is able to pick which Vector Store Retriever to use based on user question.\n\nHowever it comes with the restriction for not being able to resume follow up conversations because there isn't any memory.\n\nIt is suitable for LLM which doesn't have function calling support.\n\nOtherwise, it is recommended to use Multiple Documents QnA template which uses Tool Agent"
                },
                "outputAnchors": [
                    {
                        "id": "stickyNote_0-output-stickyNote-StickyNote",
                        "name": "stickyNote",
                        "label": "StickyNote",
                        "description": "Add a sticky note",
                        "type": "StickyNote"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "width": 300,
            "height": 324,
            "selected": false,
            "positionAbsolute": {
                "x": 1564.4709721348295,
                "y": 121.26040803337389
            },
            "dragging": false
        }
    ],
    "edges": [
        {
            "source": "vectorStoreRetriever_0",
            "sourceHandle": "vectorStoreRetriever_0-output-vectorStoreRetriever-VectorStoreRetriever",
            "target": "multiRetrievalQAChain_0",
            "targetHandle": "multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "type": "buttonedge",
            "id": "vectorStoreRetriever_0-vectorStoreRetriever_0-output-vectorStoreRetriever-VectorStoreRetriever-multiRetrievalQAChain_0-multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "data": {
                "label": ""
            }
        },
        {
            "source": "vectorStoreRetriever_1",
            "sourceHandle": "vectorStoreRetriever_1-output-vectorStoreRetriever-VectorStoreRetriever",
            "target": "multiRetrievalQAChain_0",
            "targetHandle": "multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "type": "buttonedge",
            "id": "vectorStoreRetriever_1-vectorStoreRetriever_1-output-vectorStoreRetriever-VectorStoreRetriever-multiRetrievalQAChain_0-multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "data": {
                "label": ""
            }
        },
        {
            "source": "vectorStoreRetriever_2",
            "sourceHandle": "vectorStoreRetriever_2-output-vectorStoreRetriever-VectorStoreRetriever",
            "target": "multiRetrievalQAChain_0",
            "targetHandle": "multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "type": "buttonedge",
            "id": "vectorStoreRetriever_2-vectorStoreRetriever_2-output-vectorStoreRetriever-VectorStoreRetriever-multiRetrievalQAChain_0-multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever",
            "data": {
                "label": ""
            }
        },
        {
            "source": "chatOpenAI_0",
            "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
            "target": "multiRetrievalQAChain_0",
            "targetHandle": "multiRetrievalQAChain_0-input-model-BaseLanguageModel",
            "type": "buttonedge",
            "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-multiRetrievalQAChain_0-multiRetrievalQAChain_0-input-model-BaseLanguageModel",
            "data": {
                "label": ""
            }
        },
        {
            "source": "pinecone_0",
            "sourceHandle": "pinecone_0-output-vectorStore-Pinecone|VectorStore",
            "target": "vectorStoreRetriever_2",
            "targetHandle": "vectorStoreRetriever_2-input-vectorStore-VectorStore",
            "type": "buttonedge",
            "id": "pinecone_0-pinecone_0-output-vectorStore-Pinecone|VectorStore-vectorStoreRetriever_2-vectorStoreRetriever_2-input-vectorStore-VectorStore",
            "data": {
                "label": ""
            }
        },
        {
            "source": "chroma_0",
            "sourceHandle": "chroma_0-output-vectorStore-Chroma|VectorStore",
            "target": "vectorStoreRetriever_1",
            "targetHandle": "vectorStoreRetriever_1-input-vectorStore-VectorStore",
            "type": "buttonedge",
            "id": "chroma_0-chroma_0-output-vectorStore-Chroma|VectorStore-vectorStoreRetriever_1-vectorStoreRetriever_1-input-vectorStore-VectorStore",
            "data": {
                "label": ""
            }
        },
        {
            "source": "supabase_0",
            "sourceHandle": "supabase_0-output-vectorStore-Supabase|VectorStore",
            "target": "vectorStoreRetriever_0",
            "targetHandle": "vectorStoreRetriever_0-input-vectorStore-VectorStore",
            "type": "buttonedge",
            "id": "supabase_0-supabase_0-output-vectorStore-Supabase|VectorStore-vectorStoreRetriever_0-vectorStoreRetriever_0-input-vectorStore-VectorStore",
            "data": {
                "label": ""
            }
        },
        {
            "source": "openAIEmbeddings_0",
            "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
            "target": "supabase_0",
            "targetHandle": "supabase_0-input-embeddings-Embeddings",
            "type": "buttonedge",
            "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-supabase_0-supabase_0-input-embeddings-Embeddings",
            "data": {
                "label": ""
            }
        },
        {
            "source": "openAIEmbeddings_0",
            "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
            "target": "chroma_0",
            "targetHandle": "chroma_0-input-embeddings-Embeddings",
            "type": "buttonedge",
            "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-chroma_0-chroma_0-input-embeddings-Embeddings",
            "data": {
                "label": ""
            }
        },
        {
            "source": "openAIEmbeddings_0",
            "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
            "target": "pinecone_0",
            "targetHandle": "pinecone_0-input-embeddings-Embeddings",
            "type": "buttonedge",
            "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pinecone_0-pinecone_0-input-embeddings-Embeddings",
            "data": {
                "label": ""
            }
        }
    ]
}
