{
"description": "Using Vectara for Retrieval Augmented Generation (RAG) to answer questions from documents",
"usecases": ["Documents QnA"],
"framework": ["Langchain"],
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"name": "vectaraQAChain",
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"baseClasses": ["VectaraQAChain", "BaseChain", "Runnable"],
"category": "Chains",
"description": "QA chain for Vectara",
"inputParams": [
{
"label": "Summarizer Prompt Name",
"name": "summarizerPromptName",
"description": "Summarize the results fetched from Vectara. Read more",
"type": "options",
"options": [
{
"label": "vectara-summary-ext-v1.2.0 (gpt-3.5-turbo)",
"name": "vectara-summary-ext-v1.2.0"
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"label": "vectara-experimental-summary-ext-2023-10-23-small (gpt-3.5-turbo)",
"name": "vectara-experimental-summary-ext-2023-10-23-small",
"description": "In beta, available to both Growth and Scale Vectara users"
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{
"label": "vectara-summary-ext-v1.3.0 (gpt-4.0)",
"name": "vectara-summary-ext-v1.3.0",
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{
"label": "vectara-experimental-summary-ext-2023-10-23-med (gpt-4.0)",
"name": "vectara-experimental-summary-ext-2023-10-23-med",
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"id": "vectaraQAChain_0-input-summarizerPromptName-options"
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{
"label": "Response Language",
"name": "responseLang",
"description": "Return the response in specific language. If not selected, Vectara will automatically detects the language. Read more",
"type": "options",
"options": [
{
"label": "English",
"name": "eng"
},
{
"label": "German",
"name": "deu"
},
{
"label": "French",
"name": "fra"
},
{
"label": "Chinese",
"name": "zho"
},
{
"label": "Korean",
"name": "kor"
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{
"label": "Arabic",
"name": "ara"
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{
"label": "Russian",
"name": "rus"
},
{
"label": "Thai",
"name": "tha"
},
{
"label": "Dutch",
"name": "nld"
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{
"label": "Italian",
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{
"label": "Portuguese",
"name": "por"
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{
"label": "Spanish",
"name": "spa"
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{
"label": "Japanese",
"name": "jpn"
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{
"label": "Polish",
"name": "pol"
},
{
"label": "Turkish",
"name": "tur"
},
{
"label": "Vietnamese",
"name": "vie"
},
{
"label": "Indonesian",
"name": "ind"
},
{
"label": "Czech",
"name": "ces"
},
{
"label": "Ukrainian",
"name": "ukr"
},
{
"label": "Greek",
"name": "ell"
},
{
"label": "Hebrew",
"name": "heb"
},
{
"label": "Farsi/Persian",
"name": "fas"
},
{
"label": "Hindi",
"name": "hin"
},
{
"label": "Urdu",
"name": "urd"
},
{
"label": "Swedish",
"name": "swe"
},
{
"label": "Bengali",
"name": "ben"
},
{
"label": "Malay",
"name": "msa"
},
{
"label": "Romanian",
"name": "ron"
}
],
"optional": true,
"default": "eng",
"id": "vectaraQAChain_0-input-responseLang-options"
},
{
"label": "Max Summarized Results",
"name": "maxSummarizedResults",
"description": "Maximum results used to build the summarized response",
"type": "number",
"default": 7,
"id": "vectaraQAChain_0-input-maxSummarizedResults-number"
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"name": "vectaraStore",
"type": "VectorStore",
"id": "vectaraQAChain_0-input-vectaraStore-VectorStore"
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{
"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": "vectaraQAChain_0-input-inputModeration-Moderation"
}
],
"inputs": {
"inputModeration": "",
"vectaraStore": "{{vectara_1.data.instance}}",
"summarizerPromptName": "vectara-experimental-summary-ext-2023-10-23-small",
"responseLang": "eng",
"maxSummarizedResults": 7
},
"outputAnchors": [
{
"id": "vectaraQAChain_0-output-vectaraQAChain-VectaraQAChain|BaseChain|Runnable",
"name": "vectaraQAChain",
"label": "VectaraQAChain",
"type": "VectaraQAChain | BaseChain | Runnable"
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"outputs": {},
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"id": "vectara_1",
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"type": "customNode",
"data": {
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"label": "Vectara",
"version": 2,
"name": "vectara",
"type": "Vectara",
"baseClasses": ["Vectara", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "Upsert embedded data and perform similarity search upon query using Vectara, a LLM-powered search-as-a-service",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["vectaraApi"],
"id": "vectara_1-input-credential-credential"
},
{
"label": "File",
"name": "file",
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"optional": true,
"id": "vectara_1-input-file-file"
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{
"label": "Metadata Filter",
"name": "filter",
"description": "Filter to apply to Vectara metadata. Refer to the documentation on how to use Vectara filters with Flowise.",
"type": "string",
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-filter-string"
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{
"label": "Sentences Before",
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"type": "number",
"default": 2,
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-sentencesBefore-number"
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{
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"default": 2,
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-sentencesAfter-number"
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{
"label": "Lambda",
"name": "lambda",
"description": "Enable hybrid search to improve retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.A value of 0.0 means that only neural search is used, while a value of 1.0 means that only keyword-based search is used. Defaults to 0.0 (neural only).",
"default": 0,
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-lambda-number"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Defaults to 5",
"placeholder": "5",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-topK-number"
},
{
"label": "MMR K",
"name": "mmrK",
"description": "Number of top results to fetch for MMR. Defaults to 50",
"placeholder": "50",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-mmrK-number"
},
{
"label": "MMR diversity bias",
"name": "mmrDiversityBias",
"step": 0.1,
"description": "The diversity bias to use for MMR. This is a value between 0.0 and 1.0Values closer to 1.0 optimize for the most diverse results.Defaults to 0 (MMR disabled)",
"placeholder": "0.0",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectara_1-input-mmrDiversityBias-number"
}
],
"inputAnchors": [
{
"label": "Document",
"name": "document",
"type": "Document",
"list": true,
"optional": true,
"id": "vectara_1-input-document-Document"
}
],
"inputs": {
"document": "",
"filter": "",
"sentencesBefore": 2,
"sentencesAfter": 2,
"lambda": "",
"topK": "",
"mmrK": "",
"mmrDiversityBias": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "vectara_1-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Vectara Retriever",
"type": "Vectara | VectorStoreRetriever | BaseRetriever"
},
{
"id": "vectara_1-output-vectorStore-Vectara|VectorStore",
"name": "vectorStore",
"label": "Vectara Vector Store",
"type": "Vectara | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": {
"output": "vectorStore"
},
"selected": false
},
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"edges": [
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"sourceHandle": "vectara_1-output-vectorStore-Vectara|VectorStore",
"target": "vectaraQAChain_0",
"targetHandle": "vectaraQAChain_0-input-vectaraStore-VectorStore",
"type": "buttonedge",
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}