Flowise
398 строк · 17.6 Кб
1{2"description": "QA chain for Vectara",3"categories": "Vectara QA Chain,Vectara,Langchain",4"framework": "Langchain",5"nodes": [6{7"width": 300,8"height": 520,9"id": "vectaraQAChain_0",10"position": {11"x": 740.28434119739,12"y": 164.9326144684159813},14"type": "customNode",15"data": {16"id": "vectaraQAChain_0",17"label": "Vectara QA Chain",18"version": 2,19"name": "vectaraQAChain",20"type": "VectaraQAChain",21"baseClasses": ["VectaraQAChain", "BaseChain", "Runnable"],22"category": "Chains",23"description": "QA chain for Vectara",24"inputParams": [25{26"label": "Summarizer Prompt Name",27"name": "summarizerPromptName",28"description": "Summarize the results fetched from Vectara. Read <a target=\"_blank\" href=\"https://docs.vectara.com/docs/learn/grounded-generation/select-a-summarizer\">more</a>",29"type": "options",30"options": [31{32"label": "vectara-summary-ext-v1.2.0 (gpt-3.5-turbo)",33"name": "vectara-summary-ext-v1.2.0"34},35{36"label": "vectara-experimental-summary-ext-2023-10-23-small (gpt-3.5-turbo)",37"name": "vectara-experimental-summary-ext-2023-10-23-small",38"description": "In beta, available to both Growth and Scale Vectara users"39},40{41"label": "vectara-summary-ext-v1.3.0 (gpt-4.0)",42"name": "vectara-summary-ext-v1.3.0",43"description": "Only available to paying Scale Vectara users"44},45{46"label": "vectara-experimental-summary-ext-2023-10-23-med (gpt-4.0)",47"name": "vectara-experimental-summary-ext-2023-10-23-med",48"description": "In beta, only available to paying Scale Vectara users"49}50],51"default": "vectara-summary-ext-v1.2.0",52"id": "vectaraQAChain_0-input-summarizerPromptName-options"53},54{55"label": "Response Language",56"name": "responseLang",57"description": "Return the response in specific language. If not selected, Vectara will automatically detects the language. Read <a target=\"_blank\" href=\"https://docs.vectara.com/docs/learn/grounded-generation/grounded-generation-response-languages\">more</a>",58"type": "options",59"options": [60{61"label": "English",62"name": "eng"63},64{65"label": "German",66"name": "deu"67},68{69"label": "French",70"name": "fra"71},72{73"label": "Chinese",74"name": "zho"75},76{77"label": "Korean",78"name": "kor"79},80{81"label": "Arabic",82"name": "ara"83},84{85"label": "Russian",86"name": "rus"87},88{89"label": "Thai",90"name": "tha"91},92{93"label": "Dutch",94"name": "nld"95},96{97"label": "Italian",98"name": "ita"99},100{101"label": "Portuguese",102"name": "por"103},104{105"label": "Spanish",106"name": "spa"107},108{109"label": "Japanese",110"name": "jpn"111},112{113"label": "Polish",114"name": "pol"115},116{117"label": "Turkish",118"name": "tur"119},120{121"label": "Vietnamese",122"name": "vie"123},124{125"label": "Indonesian",126"name": "ind"127},128{129"label": "Czech",130"name": "ces"131},132{133"label": "Ukrainian",134"name": "ukr"135},136{137"label": "Greek",138"name": "ell"139},140{141"label": "Hebrew",142"name": "heb"143},144{145"label": "Farsi/Persian",146"name": "fas"147},148{149"label": "Hindi",150"name": "hin"151},152{153"label": "Urdu",154"name": "urd"155},156{157"label": "Swedish",158"name": "swe"159},160{161"label": "Bengali",162"name": "ben"163},164{165"label": "Malay",166"name": "msa"167},168{169"label": "Romanian",170"name": "ron"171}172],173"optional": true,174"default": "eng",175"id": "vectaraQAChain_0-input-responseLang-options"176},177{178"label": "Max Summarized Results",179"name": "maxSummarizedResults",180"description": "Maximum results used to build the summarized response",181"type": "number",182"default": 7,183"id": "vectaraQAChain_0-input-maxSummarizedResults-number"184}185],186"inputAnchors": [187{188"label": "Vectara Store",189"name": "vectaraStore",190"type": "VectorStore",191"id": "vectaraQAChain_0-input-vectaraStore-VectorStore"192},193{194"label": "Input Moderation",195"description": "Detect text that could generate harmful output and prevent it from being sent to the language model",196"name": "inputModeration",197"type": "Moderation",198"optional": true,199"list": true,200"id": "vectaraQAChain_0-input-inputModeration-Moderation"201}202],203"inputs": {204"inputModeration": "",205"vectaraStore": "{{vectara_1.data.instance}}",206"summarizerPromptName": "vectara-experimental-summary-ext-2023-10-23-small",207"responseLang": "eng",208"maxSummarizedResults": 7209},210"outputAnchors": [211{212"id": "vectaraQAChain_0-output-vectaraQAChain-VectaraQAChain|BaseChain|Runnable",213"name": "vectaraQAChain",214"label": "VectaraQAChain",215"type": "VectaraQAChain | BaseChain | Runnable"216}217],218"outputs": {},219"selected": false220},221"selected": false,222"positionAbsolute": {223"x": 740.28434119739,224"y": 164.93261446841598225},226"dragging": false227},228{229"width": 300,230"height": 536,231"id": "vectara_1",232"position": {233"x": 139.43135627266395,234"y": 189.3685569634871235},236"type": "customNode",237"data": {238"id": "vectara_1",239"label": "Vectara",240"version": 2,241"name": "vectara",242"type": "Vectara",243"baseClasses": ["Vectara", "VectorStoreRetriever", "BaseRetriever"],244"category": "Vector Stores",245"description": "Upsert embedded data and perform similarity search upon query using Vectara, a LLM-powered search-as-a-service",246"inputParams": [247{248"label": "Connect Credential",249"name": "credential",250"type": "credential",251"credentialNames": ["vectaraApi"],252"id": "vectara_1-input-credential-credential"253},254{255"label": "File",256"name": "file",257"description": "File to upload to Vectara. Supported file types: https://docs.vectara.com/docs/api-reference/indexing-apis/file-upload/file-upload-filetypes",258"type": "file",259"optional": true,260"id": "vectara_1-input-file-file"261},262{263"label": "Metadata Filter",264"name": "filter",265"description": "Filter to apply to Vectara metadata. Refer to the <a target=\"_blank\" href=\"https://docs.flowiseai.com/vector-stores/vectara\">documentation</a> on how to use Vectara filters with Flowise.",266"type": "string",267"additionalParams": true,268"optional": true,269"id": "vectara_1-input-filter-string"270},271{272"label": "Sentences Before",273"name": "sentencesBefore",274"description": "Number of sentences to fetch before the matched sentence. Defaults to 2.",275"type": "number",276"default": 2,277"additionalParams": true,278"optional": true,279"id": "vectara_1-input-sentencesBefore-number"280},281{282"label": "Sentences After",283"name": "sentencesAfter",284"description": "Number of sentences to fetch after the matched sentence. Defaults to 2.",285"type": "number",286"default": 2,287"additionalParams": true,288"optional": true,289"id": "vectara_1-input-sentencesAfter-number"290},291{292"label": "Lambda",293"name": "lambda",294"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).",295"default": 0,296"type": "number",297"additionalParams": true,298"optional": true,299"id": "vectara_1-input-lambda-number"300},301{302"label": "Top K",303"name": "topK",304"description": "Number of top results to fetch. Defaults to 5",305"placeholder": "5",306"type": "number",307"additionalParams": true,308"optional": true,309"id": "vectara_1-input-topK-number"310},311{312"label": "MMR K",313"name": "mmrK",314"description": "Number of top results to fetch for MMR. Defaults to 50",315"placeholder": "50",316"type": "number",317"additionalParams": true,318"optional": true,319"id": "vectara_1-input-mmrK-number"320},321{322"label": "MMR diversity bias",323"name": "mmrDiversityBias",324"step": 0.1,325"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)",326"placeholder": "0.0",327"type": "number",328"additionalParams": true,329"optional": true,330"id": "vectara_1-input-mmrDiversityBias-number"331}332],333"inputAnchors": [334{335"label": "Document",336"name": "document",337"type": "Document",338"list": true,339"optional": true,340"id": "vectara_1-input-document-Document"341}342],343"inputs": {344"document": "",345"filter": "",346"sentencesBefore": 2,347"sentencesAfter": 2,348"lambda": "",349"topK": "",350"mmrK": "",351"mmrDiversityBias": ""352},353"outputAnchors": [354{355"name": "output",356"label": "Output",357"type": "options",358"options": [359{360"id": "vectara_1-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",361"name": "retriever",362"label": "Vectara Retriever",363"type": "Vectara | VectorStoreRetriever | BaseRetriever"364},365{366"id": "vectara_1-output-vectorStore-Vectara|VectorStore",367"name": "vectorStore",368"label": "Vectara Vector Store",369"type": "Vectara | VectorStore"370}371],372"default": "retriever"373}374],375"outputs": {376"output": "vectorStore"377},378"selected": false379},380"positionAbsolute": {381"x": 139.43135627266395,382"y": 189.3685569634871383},384"selected": false,385"dragging": false386}387],388"edges": [389{390"source": "vectara_1",391"sourceHandle": "vectara_1-output-vectorStore-Vectara|VectorStore",392"target": "vectaraQAChain_0",393"targetHandle": "vectaraQAChain_0-input-vectaraStore-VectorStore",394"type": "buttonedge",395"id": "vectara_1-vectara_1-output-vectorStore-Vectara|VectorStore-vectaraQAChain_0-vectaraQAChain_0-input-vectaraStore-VectorStore"396}397]398}399