Upload existing templates
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{
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"description": "A simple LLM chain that uses Vectara to enable conversations with existing documents",
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"nodes": [
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{
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"width": 300,
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"height": 357,
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"id": "vectaraExistingIndex_0",
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"position": { "x": 465.7428816308626, "y": 241.80234144183515 },
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"type": "customNode",
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"data": {
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"id": "vectaraExistingIndex_0",
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"label": "Vectara Load Existing Index",
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"version": 1,
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"name": "vectaraExistingIndex",
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"type": "Vectara",
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"baseClasses": ["Vectara", "VectorStoreRetriever", "BaseRetriever"],
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"category": "Vector Stores",
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"description": "Load existing index from Vectara (i.e: Document has been upserted)",
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"inputParams": [
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{
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"label": "Connect Credential",
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"name": "credential",
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"type": "credential",
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"credentialNames": ["vectaraApi"],
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"id": "vectaraExistingIndex_0-input-credential-credential"
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},
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{
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"label": "Vectara Metadata Filter",
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"name": "filter",
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"type": "json",
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"additionalParams": true,
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"optional": true,
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"id": "vectaraExistingIndex_0-input-filter-json"
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},
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{
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"label": "Lambda",
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"name": "lambda",
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"type": "number",
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"additionalParams": true,
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"optional": true,
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"id": "vectaraExistingIndex_0-input-lambda-number"
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},
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{
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"label": "Top K",
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"name": "topK",
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"description": "Number of top results to fetch. Defaults to 4",
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"placeholder": "4",
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"type": "number",
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"additionalParams": true,
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"optional": true,
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"id": "vectaraExistingIndex_0-input-topK-number"
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}
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],
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"inputAnchors": [],
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"inputs": { "filter": "", "lambda": "", "topK": "" },
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"outputAnchors": [
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{
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"name": "output",
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"label": "Output",
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"type": "options",
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"options": [
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{
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"id": "vectaraExistingIndex_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
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"name": "retriever",
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"label": "Vectara Retriever",
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"type": "Vectara | VectorStoreRetriever | BaseRetriever"
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},
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{
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"id": "vectaraExistingIndex_0-output-vectorStore-Vectara|VectorStore",
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"name": "vectorStore",
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"label": "Vectara Vector Store",
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"type": "Vectara | VectorStore"
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}
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],
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"default": "retriever"
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}
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],
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"outputs": { "output": "retriever" },
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"selected": false
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},
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"selected": false,
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"dragging": false,
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"positionAbsolute": { "x": 465.7428816308626, "y": 241.80234144183515 }
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},
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{
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"width": 300,
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"height": 525,
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"id": "chatOpenAI_0",
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"position": { "x": 899.9419397673153, "y": 202.43889985803958 },
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"type": "customNode",
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"data": {
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"id": "chatOpenAI_0",
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"label": "ChatOpenAI",
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"version": 1,
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"name": "chatOpenAI",
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"type": "ChatOpenAI",
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"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
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"category": "Chat Models",
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"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
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"inputParams": [
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{
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"label": "Connect Credential",
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"name": "credential",
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"type": "credential",
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"credentialNames": ["openAIApi"],
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"id": "chatOpenAI_0-input-credential-credential"
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},
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{
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"label": "Model Name",
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"name": "modelName",
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"type": "options",
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"options": [
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{ "label": "gpt-4", "name": "gpt-4" },
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{ "label": "gpt-4-0613", "name": "gpt-4-0613" },
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{ "label": "gpt-4-32k", "name": "gpt-4-32k" },
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{ "label": "gpt-4-32k-0613", "name": "gpt-4-32k-0613" },
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{ "label": "gpt-3.5-turbo", "name": "gpt-3.5-turbo" },
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{ "label": "gpt-3.5-turbo-0613", "name": "gpt-3.5-turbo-0613" },
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{ "label": "gpt-3.5-turbo-16k", "name": "gpt-3.5-turbo-16k" },
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{
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"label": "gpt-3.5-turbo-16k-0613",
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"name": "gpt-3.5-turbo-16k-0613"
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}
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],
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"default": "gpt-3.5-turbo",
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"optional": true,
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"id": "chatOpenAI_0-input-modelName-options"
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},
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{
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"label": "Temperature",
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"name": "temperature",
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"type": "number",
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"step": 0.1,
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"default": 0.9,
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"optional": true,
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"id": "chatOpenAI_0-input-temperature-number"
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},
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{
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"label": "Max Tokens",
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"name": "maxTokens",
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"type": "number",
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"step": 1,
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-maxTokens-number"
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},
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{
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"label": "Top Probability",
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"name": "topP",
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"type": "number",
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"step": 0.1,
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-topP-number"
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},
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{
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"label": "Frequency Penalty",
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"name": "frequencyPenalty",
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"type": "number",
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"step": 0.1,
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-frequencyPenalty-number"
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},
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{
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"label": "Presence Penalty",
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"name": "presencePenalty",
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"type": "number",
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"step": 0.1,
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-presencePenalty-number"
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},
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{
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"label": "Timeout",
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"name": "timeout",
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"type": "number",
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"step": 1,
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-timeout-number"
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},
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{
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"label": "BasePath",
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"name": "basepath",
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"type": "string",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-basepath-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"modelName": "gpt-3.5-turbo",
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"temperature": 0.9,
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"maxTokens": "",
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"topP": "",
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"frequencyPenalty": "",
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"presencePenalty": "",
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"timeout": "",
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"basepath": ""
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},
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"outputAnchors": [
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{
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"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
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"name": "chatOpenAI",
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"label": "ChatOpenAI",
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"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel"
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}
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],
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"outputs": {},
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"selected": false
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},
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"selected": false,
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"positionAbsolute": { "x": 899.9419397673153, "y": 202.43889985803958 },
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"dragging": false
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},
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{
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"width": 300,
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"height": 481,
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"id": "conversationalRetrievalQAChain_0",
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"position": { "x": 1290.3534883720931, "y": 376.49186046511625 },
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"type": "customNode",
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"data": {
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"id": "conversationalRetrievalQAChain_0",
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"label": "Conversational Retrieval QA Chain",
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"version": 1,
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"name": "conversationalRetrievalQAChain",
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"type": "ConversationalRetrievalQAChain",
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"baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"],
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"category": "Chains",
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"description": "Document QA - built on RetrievalQAChain to provide a chat history component",
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"inputParams": [
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{
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"label": "Return Source Documents",
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"name": "returnSourceDocuments",
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"type": "boolean",
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"optional": true,
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"id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean"
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},
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{
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"label": "System Message",
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"name": "systemMessagePrompt",
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"type": "string",
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"rows": 4,
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"additionalParams": true,
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"optional": true,
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"placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.",
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"id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string"
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},
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{
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"label": "Chain Option",
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"name": "chainOption",
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"type": "options",
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"options": [
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{
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"label": "MapReduceDocumentsChain",
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"name": "map_reduce",
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"description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time"
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},
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{
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"label": "RefineDocumentsChain",
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"name": "refine",
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"description": "Suitable for QA tasks over a large number of documents."
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},
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{
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"label": "StuffDocumentsChain",
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"name": "stuff",
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"description": "Suitable for QA tasks over a small number of documents."
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}
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],
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"additionalParams": true,
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"optional": true,
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"id": "conversationalRetrievalQAChain_0-input-chainOption-options"
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}
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],
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"inputAnchors": [
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{
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"label": "Language Model",
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"name": "model",
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"type": "BaseLanguageModel",
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"id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel"
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},
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{
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"label": "Vector Store Retriever",
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"name": "vectorStoreRetriever",
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"type": "BaseRetriever",
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"id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
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},
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{
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"label": "Memory",
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"name": "memory",
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"type": "BaseMemory",
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"optional": true,
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"description": "If left empty, a default BufferMemory will be used",
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"id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
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}
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],
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"inputs": {
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"model": "{{chatOpenAI_0.data.instance}}",
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"vectorStoreRetriever": "{{vectaraExistingIndex_0.data.instance}}",
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"memory": "",
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"returnSourceDocuments": "",
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"systemMessagePrompt": "",
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"chainOption": ""
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},
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"outputAnchors": [
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{
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"id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain",
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"name": "conversationalRetrievalQAChain",
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"label": "ConversationalRetrievalQAChain",
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"type": "ConversationalRetrievalQAChain | BaseChain"
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}
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],
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"outputs": {},
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"selected": false
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},
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"positionAbsolute": { "x": 1290.3534883720931, "y": 376.49186046511625 },
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"selected": false
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}
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],
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"edges": [
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{
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"source": "chatOpenAI_0",
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"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
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"target": "conversationalRetrievalQAChain_0",
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"targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
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"type": "buttonedge",
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"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
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"data": { "label": "" }
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},
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{
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"source": "vectaraExistingIndex_0",
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"sourceHandle": "vectaraExistingIndex_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
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"target": "conversationalRetrievalQAChain_0",
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"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
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"type": "buttonedge",
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"id": "vectaraExistingIndex_0-vectaraExistingIndex_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
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"data": { "label": "" }
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}
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]
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}
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@ -1,5 +1,5 @@
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{
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"description": "A simple LLM chain that uses Vectara to enable conversations with documents",
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"description": "A simple LLM chain that uses Vectara to enable conversations with uploaded documents",
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"nodes": [
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{
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"width": 300,
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