mirror of https://github.com/FlowiseAI/Flowise.git
1235 lines
56 KiB
JSON
1235 lines
56 KiB
JSON
{
|
|
"description": "Breaks down query into sub questions for each relevant data source, then combine into final response",
|
|
"usecases": ["SQL"],
|
|
"framework": ["LlamaIndex"],
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|
"nodes": [
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{
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"width": 300,
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"height": 749,
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"id": "compactrefineLlamaIndex_0",
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"position": {
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"x": -443.9012456561584,
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"y": 826.6100190232154
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},
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"type": "customNode",
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"data": {
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"id": "compactrefineLlamaIndex_0",
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"label": "Compact and Refine",
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|
"version": 1,
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|
"name": "compactrefineLlamaIndex",
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|
"type": "CompactRefine",
|
|
"baseClasses": ["CompactRefine", "ResponseSynthesizer"],
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|
"tags": ["LlamaIndex"],
|
|
"category": "Response Synthesizer",
|
|
"description": "CompactRefine is a slight variation of Refine that first compacts the text chunks into the smallest possible number of chunks.",
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|
"inputParams": [
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{
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"label": "Refine Prompt",
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"name": "refinePrompt",
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"type": "string",
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"rows": 4,
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"default": "The original query is as follows: {query}\nWe have provided an existing answer: {existingAnswer}\nWe have the opportunity to refine the existing answer (only if needed) with some more context below.\n------------\n{context}\n------------\nGiven the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer.\nRefined Answer:",
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"warning": "Prompt can contains no variables, or up to 3 variables. Variables must be {existingAnswer}, {context} and {query}",
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"optional": true,
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"id": "compactrefineLlamaIndex_0-input-refinePrompt-string"
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},
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{
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"label": "Text QA Prompt",
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"name": "textQAPrompt",
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|
"type": "string",
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"rows": 4,
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"default": "Context information is below.\n---------------------\n{context}\n---------------------\nGiven the context information and not prior knowledge, answer the query.\nQuery: {query}\nAnswer:",
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|
"warning": "Prompt can contains no variables, or up to 2 variables. Variables must be {context} and {query}",
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"optional": true,
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"id": "compactrefineLlamaIndex_0-input-textQAPrompt-string"
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|
}
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],
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"inputAnchors": [],
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"inputs": {
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"refinePrompt": "A user has selected a set of SEC filing documents and has asked a question about them.\nThe SEC documents have the following titles:\n- Apple Inc (APPL) FORM 10K 2022\n- Tesla Inc (TSLA) FORM 10K 2022\nThe original query is as follows: {query}\nWe have provided an existing answer: {existingAnswer}\nWe have the opportunity to refine the existing answer (only if needed) with some more context below.\n------------\n{context}\n------------\nGiven the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer.\nRefined Answer:",
|
|
"textQAPrompt": "A user has selected a set of SEC filing documents and has asked a question about them.\nThe SEC documents have the following titles:\n- Apple Inc (APPL) FORM 10K 2022\n- Tesla Inc (TSLA) FORM 10K 2022\nContext information is below.\n---------------------\n{context}\n---------------------\nGiven the context information and not prior knowledge, answer the query.\nQuery: {query}\nAnswer:"
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},
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"outputAnchors": [
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{
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|
"id": "compactrefineLlamaIndex_0-output-compactrefineLlamaIndex-CompactRefine|ResponseSynthesizer",
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|
"name": "compactrefineLlamaIndex",
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|
"label": "CompactRefine",
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|
"type": "CompactRefine | ResponseSynthesizer"
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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": {
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"x": -443.9012456561584,
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"y": 826.6100190232154
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},
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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": 611,
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"id": "pineconeLlamaIndex_0",
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"position": {
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"x": 35.45798119088212,
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"y": -132.1789597307308
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},
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"type": "customNode",
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"data": {
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"id": "pineconeLlamaIndex_0",
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"label": "Pinecone",
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"version": 1,
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"name": "pineconeLlamaIndex",
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"type": "Pinecone",
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|
"baseClasses": ["Pinecone", "VectorIndexRetriever"],
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|
"tags": ["LlamaIndex"],
|
|
"category": "Vector Stores",
|
|
"description": "Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database",
|
|
"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": ["pineconeApi"],
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"id": "pineconeLlamaIndex_0-input-credential-credential"
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},
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{
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"label": "Pinecone Index",
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"name": "pineconeIndex",
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|
"type": "string",
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|
"id": "pineconeLlamaIndex_0-input-pineconeIndex-string"
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},
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{
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"label": "Pinecone Namespace",
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"name": "pineconeNamespace",
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"type": "string",
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"placeholder": "my-first-namespace",
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"additionalParams": true,
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"optional": true,
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"id": "pineconeLlamaIndex_0-input-pineconeNamespace-string"
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},
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{
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"label": "Pinecone Metadata Filter",
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"name": "pineconeMetadataFilter",
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"type": "json",
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"optional": true,
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|
"additionalParams": true,
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"id": "pineconeLlamaIndex_0-input-pineconeMetadataFilter-json"
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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. Default 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": "pineconeLlamaIndex_0-input-topK-number"
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}
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],
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"inputAnchors": [
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{
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"label": "Document",
|
|
"name": "document",
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|
"type": "Document",
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"list": true,
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|
"optional": true,
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|
"id": "pineconeLlamaIndex_0-input-document-Document"
|
|
},
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|
{
|
|
"label": "Chat Model",
|
|
"name": "model",
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|
"type": "BaseChatModel_LlamaIndex",
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"id": "pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex"
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|
},
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{
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"label": "Embeddings",
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"name": "embeddings",
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"type": "BaseEmbedding_LlamaIndex",
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"id": "pineconeLlamaIndex_0-input-embeddings-BaseEmbedding_LlamaIndex"
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}
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],
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"inputs": {
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"document": [],
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"model": "{{chatOpenAI_LlamaIndex_0.data.instance}}",
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"embeddings": "{{openAIEmbedding_LlamaIndex_0.data.instance}}",
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"pineconeIndex": "flowiseindex",
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"pineconeNamespace": "pinecone-form10k",
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"pineconeMetadataFilter": "{\"source\":\"tesla\"}",
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"topK": ""
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},
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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": "pineconeLlamaIndex_0-output-retriever-Pinecone|VectorIndexRetriever",
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"name": "retriever",
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"label": "Pinecone Retriever",
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"type": "Pinecone | VectorIndexRetriever"
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},
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{
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"id": "pineconeLlamaIndex_0-output-vectorStore-Pinecone|VectorStoreIndex",
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|
"name": "vectorStore",
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|
"label": "Pinecone Vector Store Index",
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"type": "Pinecone | VectorStoreIndex"
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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": {
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"output": "retriever"
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},
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"selected": false
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},
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"selected": false,
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"positionAbsolute": {
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"x": 35.45798119088212,
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"y": -132.1789597307308
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},
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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": 529,
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"id": "chatOpenAI_LlamaIndex_0",
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"position": {
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"x": -455.232655468177,
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"y": -711.0080711676725
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},
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"type": "customNode",
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"data": {
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"id": "chatOpenAI_LlamaIndex_0",
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"label": "ChatOpenAI",
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"version": 2.0,
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"name": "chatOpenAI_LlamaIndex",
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"type": "ChatOpenAI",
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|
"baseClasses": ["ChatOpenAI", "BaseChatModel_LlamaIndex", "BaseLLM"],
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|
"tags": ["LlamaIndex"],
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|
"category": "Chat Models",
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|
"description": "Wrapper around OpenAI Chat LLM specific for LlamaIndex",
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|
"inputParams": [
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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_LlamaIndex_0-input-credential-credential"
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},
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{
|
|
"label": "Model Name",
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"name": "modelName",
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|
"type": "asyncOptions",
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"loadMethod": "listModels",
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|
"default": "gpt-3.5-turbo",
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"id": "chatOpenAI_LlamaIndex_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_LlamaIndex_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_LlamaIndex_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_LlamaIndex_0-input-topP-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_LlamaIndex_0-input-timeout-number"
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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-16k",
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|
"temperature": "0",
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|
"maxTokens": "",
|
|
"topP": "",
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|
"timeout": ""
|
|
},
|
|
"outputAnchors": [
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|
{
|
|
"id": "chatOpenAI_LlamaIndex_0-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM",
|
|
"name": "chatOpenAI_LlamaIndex",
|
|
"label": "ChatOpenAI",
|
|
"type": "ChatOpenAI | BaseChatModel_LlamaIndex | BaseLLM"
|
|
}
|
|
],
|
|
"outputs": {},
|
|
"selected": false
|
|
},
|
|
"selected": false,
|
|
"positionAbsolute": {
|
|
"x": -455.232655468177,
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"y": -711.0080711676725
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},
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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": 334,
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"id": "openAIEmbedding_LlamaIndex_0",
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"position": {
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"x": -451.0082548287243,
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"y": -127.15143353229783
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},
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"type": "customNode",
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"data": {
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"id": "openAIEmbedding_LlamaIndex_0",
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"label": "OpenAI Embedding",
|
|
"version": 2,
|
|
"name": "openAIEmbedding_LlamaIndex",
|
|
"type": "OpenAIEmbedding",
|
|
"baseClasses": ["OpenAIEmbedding", "BaseEmbedding_LlamaIndex", "BaseEmbedding"],
|
|
"tags": ["LlamaIndex"],
|
|
"category": "Embeddings",
|
|
"description": "OpenAI Embedding specific for LlamaIndex",
|
|
"inputParams": [
|
|
{
|
|
"label": "Connect Credential",
|
|
"name": "credential",
|
|
"type": "credential",
|
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"credentialNames": ["openAIApi"],
|
|
"id": "openAIEmbedding_LlamaIndex_0-input-credential-credential"
|
|
},
|
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{
|
|
"label": "Model Name",
|
|
"name": "modelName",
|
|
"type": "asyncOptions",
|
|
"loadMethod": "listModels",
|
|
"default": "text-embedding-ada-002",
|
|
"id": "openAIEmbedding_LlamaIndex_0-input-modelName-options"
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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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"optional": true,
|
|
"additionalParams": true,
|
|
"id": "openAIEmbedding_LlamaIndex_0-input-timeout-number"
|
|
},
|
|
{
|
|
"label": "BasePath",
|
|
"name": "basepath",
|
|
"type": "string",
|
|
"optional": true,
|
|
"additionalParams": true,
|
|
"id": "openAIEmbedding_LlamaIndex_0-input-basepath-string"
|
|
}
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],
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"inputAnchors": [],
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"inputs": {
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"timeout": "",
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"basepath": "",
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"modelName": "text-embedding-ada-002"
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},
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"outputAnchors": [
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{
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"id": "openAIEmbedding_LlamaIndex_0-output-openAIEmbedding_LlamaIndex-OpenAIEmbedding|BaseEmbedding_LlamaIndex|BaseEmbedding",
|
|
"name": "openAIEmbedding_LlamaIndex",
|
|
"label": "OpenAIEmbedding",
|
|
"type": "OpenAIEmbedding | BaseEmbedding_LlamaIndex | BaseEmbedding"
|
|
}
|
|
],
|
|
"outputs": {},
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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": {
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"x": -451.0082548287243,
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"y": -127.15143353229783
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}
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},
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{
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"width": 300,
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"height": 611,
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"id": "pineconeLlamaIndex_1",
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"position": {
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"x": 43.95604951980056,
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"y": -783.0024679245387
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},
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"type": "customNode",
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"data": {
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"id": "pineconeLlamaIndex_1",
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"label": "Pinecone",
|
|
"version": 1,
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|
"name": "pineconeLlamaIndex",
|
|
"type": "Pinecone",
|
|
"baseClasses": ["Pinecone", "VectorIndexRetriever"],
|
|
"tags": ["LlamaIndex"],
|
|
"category": "Vector Stores",
|
|
"description": "Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database",
|
|
"inputParams": [
|
|
{
|
|
"label": "Connect Credential",
|
|
"name": "credential",
|
|
"type": "credential",
|
|
"credentialNames": ["pineconeApi"],
|
|
"id": "pineconeLlamaIndex_1-input-credential-credential"
|
|
},
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|
{
|
|
"label": "Pinecone Index",
|
|
"name": "pineconeIndex",
|
|
"type": "string",
|
|
"id": "pineconeLlamaIndex_1-input-pineconeIndex-string"
|
|
},
|
|
{
|
|
"label": "Pinecone Namespace",
|
|
"name": "pineconeNamespace",
|
|
"type": "string",
|
|
"placeholder": "my-first-namespace",
|
|
"additionalParams": true,
|
|
"optional": true,
|
|
"id": "pineconeLlamaIndex_1-input-pineconeNamespace-string"
|
|
},
|
|
{
|
|
"label": "Pinecone Metadata Filter",
|
|
"name": "pineconeMetadataFilter",
|
|
"type": "json",
|
|
"optional": true,
|
|
"additionalParams": true,
|
|
"id": "pineconeLlamaIndex_1-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": "pineconeLlamaIndex_1-input-topK-number"
|
|
}
|
|
],
|
|
"inputAnchors": [
|
|
{
|
|
"label": "Document",
|
|
"name": "document",
|
|
"type": "Document",
|
|
"list": true,
|
|
"optional": true,
|
|
"id": "pineconeLlamaIndex_1-input-document-Document"
|
|
},
|
|
{
|
|
"label": "Chat Model",
|
|
"name": "model",
|
|
"type": "BaseChatModel_LlamaIndex",
|
|
"id": "pineconeLlamaIndex_1-input-model-BaseChatModel_LlamaIndex"
|
|
},
|
|
{
|
|
"label": "Embeddings",
|
|
"name": "embeddings",
|
|
"type": "BaseEmbedding_LlamaIndex",
|
|
"id": "pineconeLlamaIndex_1-input-embeddings-BaseEmbedding_LlamaIndex"
|
|
}
|
|
],
|
|
"inputs": {
|
|
"document": [],
|
|
"model": "{{chatOpenAI_LlamaIndex_0.data.instance}}",
|
|
"embeddings": "{{openAIEmbedding_LlamaIndex_0.data.instance}}",
|
|
"pineconeIndex": "flowiseindex",
|
|
"pineconeNamespace": "pinecone-form10k",
|
|
"pineconeMetadataFilter": "{\"source\":\"apple\"}",
|
|
"topK": ""
|
|
},
|
|
"outputAnchors": [
|
|
{
|
|
"name": "output",
|
|
"label": "Output",
|
|
"type": "options",
|
|
"options": [
|
|
{
|
|
"id": "pineconeLlamaIndex_1-output-retriever-Pinecone|VectorIndexRetriever",
|
|
"name": "retriever",
|
|
"label": "Pinecone Retriever",
|
|
"type": "Pinecone | VectorIndexRetriever"
|
|
},
|
|
{
|
|
"id": "pineconeLlamaIndex_1-output-vectorStore-Pinecone|VectorStoreIndex",
|
|
"name": "vectorStore",
|
|
"label": "Pinecone Vector Store Index",
|
|
"type": "Pinecone | VectorStoreIndex"
|
|
}
|
|
],
|
|
"default": "retriever"
|
|
}
|
|
],
|
|
"outputs": {
|
|
"output": "retriever"
|
|
},
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"selected": false
|
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},
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"selected": false,
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"positionAbsolute": {
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"x": 43.95604951980056,
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"y": -783.0024679245387
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},
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"dragging": false
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},
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{
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"name": "subQuestionQueryEngine",
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"label": "SubQuestionQueryEngine",
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"description": "Breaks complex query into sub questions for each relevant data source, then gather all the intermediate reponses and synthesizes a final response",
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"type": "SubQuestionQueryEngine | BaseQueryEngine"
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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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"x": 1204.489328490966,
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"width": 300,
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"data": {
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"label": "Sticky Note",
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"version": 1,
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"name": "stickyNote",
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"type": "StickyNote",
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"baseClasses": ["StickyNote"],
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"category": "Utilities",
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"description": "Add a sticky note",
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"inputParams": [
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{
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"label": "",
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"name": "note",
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"type": "string",
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"rows": 1,
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"placeholder": "Type something here",
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"optional": true,
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"id": "stickyNote_0-input-note-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"note": "Break questions into subqueries, then retrieve corresponding context using queryengine tools"
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},
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"outputAnchors": [
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{
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"id": "stickyNote_0-output-stickyNote-StickyNote",
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"name": "stickyNote",
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"label": "StickyNote",
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"description": "Add a sticky note",
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"type": "StickyNote"
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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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"width": 300,
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"type": "stickyNote",
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"data": {
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"id": "stickyNote_1",
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"label": "Sticky Note",
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"version": 1,
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"name": "stickyNote",
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"type": "StickyNote",
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"baseClasses": ["StickyNote"],
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"category": "Utilities",
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"description": "Add a sticky note",
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"inputParams": [
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{
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"label": "",
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"name": "note",
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"type": "string",
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"rows": 1,
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"placeholder": "Type something here",
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"optional": true,
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"id": "stickyNote_1-input-note-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"note": "Query previously upserted documents with corresponding metadata key value pair - \n{ source: \"<company>\"}"
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},
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"outputAnchors": [
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{
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"id": "stickyNote_1-output-stickyNote-StickyNote",
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"name": "stickyNote",
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"label": "StickyNote",
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"description": "Add a sticky note",
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"type": "StickyNote"
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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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}
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],
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"edges": [
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{
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"source": "chatOpenAI_LlamaIndex_0",
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"sourceHandle": "chatOpenAI_LlamaIndex_0-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM",
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"target": "pineconeLlamaIndex_1",
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"targetHandle": "pineconeLlamaIndex_1-input-model-BaseChatModel_LlamaIndex",
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"id": "chatOpenAI_LlamaIndex_0-chatOpenAI_LlamaIndex_0-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM-pineconeLlamaIndex_1-pineconeLlamaIndex_1-input-model-BaseChatModel_LlamaIndex"
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"source": "openAIEmbedding_LlamaIndex_0",
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"target": "pineconeLlamaIndex_0",
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},
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{
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"source": "chatOpenAI_LlamaIndex_0",
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"sourceHandle": "chatOpenAI_LlamaIndex_0-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM",
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"target": "pineconeLlamaIndex_0",
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"targetHandle": "pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex",
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"type": "buttonedge",
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"id": "chatOpenAI_LlamaIndex_0-chatOpenAI_LlamaIndex_0-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM-pineconeLlamaIndex_0-pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex"
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},
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{
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"source": "pineconeLlamaIndex_1",
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"sourceHandle": "pineconeLlamaIndex_1-output-retriever-Pinecone|VectorIndexRetriever",
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"target": "queryEngine_0",
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"targetHandle": "queryEngine_0-input-vectorStoreRetriever-VectorIndexRetriever",
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"type": "buttonedge",
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"id": "pineconeLlamaIndex_1-pineconeLlamaIndex_1-output-retriever-Pinecone|VectorIndexRetriever-queryEngine_0-queryEngine_0-input-vectorStoreRetriever-VectorIndexRetriever"
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},
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{
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"source": "queryEngine_0",
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{
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"source": "pineconeLlamaIndex_0",
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"sourceHandle": "pineconeLlamaIndex_0-output-retriever-Pinecone|VectorIndexRetriever",
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},
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{
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"source": "queryEngine_1",
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"sourceHandle": "queryEngine_1-output-queryEngine-QueryEngine|BaseQueryEngine",
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"target": "queryEngineToolLlamaIndex_1",
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"targetHandle": "queryEngineToolLlamaIndex_1-input-baseQueryEngine-BaseQueryEngine",
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},
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{
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"source": "queryEngineToolLlamaIndex_2",
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"sourceHandle": "queryEngineToolLlamaIndex_2-output-queryEngineToolLlamaIndex-QueryEngineTool",
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"target": "subQuestionQueryEngine_0",
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"targetHandle": "subQuestionQueryEngine_0-input-queryEngineTools-QueryEngineTool",
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"id": "queryEngineToolLlamaIndex_2-queryEngineToolLlamaIndex_2-output-queryEngineToolLlamaIndex-QueryEngineTool-subQuestionQueryEngine_0-subQuestionQueryEngine_0-input-queryEngineTools-QueryEngineTool"
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},
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{
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"source": "queryEngineToolLlamaIndex_1",
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"sourceHandle": "queryEngineToolLlamaIndex_1-output-queryEngineToolLlamaIndex-QueryEngineTool",
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"target": "subQuestionQueryEngine_0",
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"targetHandle": "subQuestionQueryEngine_0-input-queryEngineTools-QueryEngineTool",
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"id": "queryEngineToolLlamaIndex_1-queryEngineToolLlamaIndex_1-output-queryEngineToolLlamaIndex-QueryEngineTool-subQuestionQueryEngine_0-subQuestionQueryEngine_0-input-queryEngineTools-QueryEngineTool"
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},
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{
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"source": "chatOpenAI_LlamaIndex_1",
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"sourceHandle": "chatOpenAI_LlamaIndex_1-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM",
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"target": "subQuestionQueryEngine_0",
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"id": "chatOpenAI_LlamaIndex_1-chatOpenAI_LlamaIndex_1-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex|BaseLLM-subQuestionQueryEngine_0-subQuestionQueryEngine_0-input-model-BaseChatModel_LlamaIndex"
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},
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{
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"source": "openAIEmbedding_LlamaIndex_1",
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"sourceHandle": "openAIEmbedding_LlamaIndex_1-output-openAIEmbedding_LlamaIndex-OpenAIEmbedding|BaseEmbedding_LlamaIndex|BaseEmbedding",
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},
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{
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"source": "compactrefineLlamaIndex_0",
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]
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}
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