mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-28 21:00:58 +03:00
add if else node and logic
This commit is contained in:
Henry
File diff suppressed because it is too large
Load Diff
@@ -7,8 +7,8 @@
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"height": 511,
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"id": "promptTemplate_0",
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"position": {
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"x": 638.5481508577102,
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"y": 84.0454315632386
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"x": 384.84394025989127,
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"y": 61.21205260943492
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},
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"type": "customNode",
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"data": {
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@@ -57,8 +57,8 @@
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"selected": false,
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"positionAbsolute": {
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"y": 84.0454315632386
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"x": 384.84394025989127,
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"y": 61.21205260943492
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"dragging": false
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@@ -67,8 +67,8 @@
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"height": 507,
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"id": "llmChain_0",
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"position": {
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"x": 1095.1973126620626,
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"y": -83.98379829183628
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"y": -127.11351409346554
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"type": "customNode",
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"data": {
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@@ -156,8 +156,8 @@
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"selected": false,
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"positionAbsolute": {
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"x": 770.4559230968546,
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"y": -127.11351409346554
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"dragging": false
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@@ -166,8 +166,8 @@
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"height": 574,
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"id": "chatOpenAI_0",
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"position": {
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"x": 636.5762708317321,
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"y": -543.3151550847003
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"x": 372.72389181000057,
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"y": -561.0744498265477
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},
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"type": "customNode",
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"data": {
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@@ -346,8 +346,8 @@
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},
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"selected": false,
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"positionAbsolute": {
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"x": 636.5762708317321,
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"y": -543.3151550847003
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"x": 372.72389181000057,
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"y": -561.0744498265477
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"dragging": false
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},
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@@ -645,8 +645,8 @@
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"height": 669,
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"id": "customFunction_2",
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"position": {
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"x": -152.63957160907668,
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"y": -212.74538890862547
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"x": -395.18079694059173,
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"y": -222.8935573325382
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},
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"type": "customNode",
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"data": {
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@@ -687,7 +687,7 @@
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"inputs": {
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"functionInputVariables": "",
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"functionName": "Get SQL Schema Prompt",
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"javascriptFunction": "const HOST = 'singlestore-host';\nconst USER = 'admin';\nconst PASSWORD = 'mypassword';\nconst DATABASE = 'mydb';\nconst TABLE = 'samples';\nconst mysql = require('mysql2/promise');\n\nlet sqlSchemaPrompt;\n\n/**\n * Ideal prompt contains schema info and examples\n * Follows best practices as specified form https://arxiv.org/abs/2204.00498\n * =========================================\n * CREATE TABLE samples (firstName varchar NOT NULL, lastName varchar)\n * SELECT * FROM samples LIMIT 3\n * firstName lastName\n * Stephen Tyler\n * Jack McGinnis\n * Steven Repici\n * =========================================\n*/\nfunction getSQLPrompt() {\n return new Promise(async (resolve, reject) => {\n \n const singleStoreConnection = mysql.createPool({\n host: HOST,\n user: USER,\n password: PASSWORD,\n database: DATABASE,\n });\n\n // Get schema info\n const [schemaInfo] = await singleStoreConnection.execute(\n `SELECT * FROM INFORMATION_SCHEMA.COLUMNS WHERE table_name = \"${TABLE}\"`\n );\n\n const createColumns = [];\n const columnNames = [];\n\n for (const schemaData of schemaInfo) {\n columnNames.push(`${schemaData['COLUMN_NAME']}`);\n createColumns.push(`${schemaData['COLUMN_NAME']} ${schemaData['COLUMN_TYPE']} ${schemaData['IS_NULLABLE'] === 'NO' ? 'NOT NULL' : ''}`);\n }\n\n const sqlCreateTableQuery = `CREATE TABLE samples (${createColumns.join(', ')})`;\n const sqlSelectTableQuery = `SELECT * FROM samples LIMIT 3`;\n\n // Get first 3 rows\n const [rows] = await singleStoreConnection.execute(\n sqlSelectTableQuery,\n );\n \n const allValues = [];\n for (const row of rows) {\n const rowValues = [];\n for (const colName in row) {\n rowValues.push(row[colName]);\n }\n allValues.push(rowValues.join(' '));\n }\n\n sqlSchemaPrompt = sqlCreateTableQuery + '\\n' + sqlSelectTableQuery + '\\n' + columnNames.join(' ') + '\\n' + allValues.join('\\n');\n \n resolve();\n });\n}\n\nasync function main() {\n await getSQLPrompt();\n}\n\nawait main();\n\nreturn sqlSchemaPrompt;"
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"javascriptFunction": "const HOST = 'singlestore-host.com';\nconst USER = 'admin';\nconst PASSWORD = 'mypassword';\nconst DATABASE = 'mydb';\nconst TABLE = 'samples';\nconst mysql = require('mysql2/promise');\n\nlet sqlSchemaPrompt;\n\n/**\n * Ideal prompt contains schema info and examples\n * Follows best practices as specified form https://arxiv.org/abs/2204.00498\n * =========================================\n * CREATE TABLE samples (firstName varchar NOT NULL, lastName varchar)\n * SELECT * FROM samples LIMIT 3\n * firstName lastName\n * Stephen Tyler\n * Jack McGinnis\n * Steven Repici\n * =========================================\n*/\nfunction getSQLPrompt() {\n return new Promise(async (resolve, reject) => {\n try {\n const singleStoreConnection = mysql.createPool({\n host: HOST,\n user: USER,\n password: PASSWORD,\n database: DATABASE,\n });\n \n // Get schema info\n const [schemaInfo] = await singleStoreConnection.execute(\n `SELECT * FROM INFORMATION_SCHEMA.COLUMNS WHERE table_name = \"${TABLE}\"`\n );\n \n const createColumns = [];\n const columnNames = [];\n \n for (const schemaData of schemaInfo) {\n columnNames.push(`${schemaData['COLUMN_NAME']}`);\n createColumns.push(`${schemaData['COLUMN_NAME']} ${schemaData['COLUMN_TYPE']} ${schemaData['IS_NULLABLE'] === 'NO' ? 'NOT NULL' : ''}`);\n }\n \n const sqlCreateTableQuery = `CREATE TABLE samples (${createColumns.join(', ')})`;\n const sqlSelectTableQuery = `SELECT * FROM samples LIMIT 3`;\n \n // Get first 3 rows\n const [rows] = await singleStoreConnection.execute(\n sqlSelectTableQuery,\n );\n \n const allValues = [];\n for (const row of rows) {\n const rowValues = [];\n for (const colName in row) {\n rowValues.push(row[colName]);\n }\n allValues.push(rowValues.join(' '));\n }\n \n sqlSchemaPrompt = sqlCreateTableQuery + '\\n' + sqlSelectTableQuery + '\\n' + columnNames.join(' ') + '\\n' + allValues.join('\\n');\n \n resolve();\n } catch (e) {\n console.error(e);\n return reject(e);\n }\n });\n}\n\nasync function main() {\n await getSQLPrompt();\n}\n\nawait main();\n\nreturn sqlSchemaPrompt;"
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},
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"outputAnchors": [
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{
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@@ -712,8 +712,8 @@
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},
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"selected": false,
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"positionAbsolute": {
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"x": -152.63957160907668,
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"y": -212.74538890862547
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"x": -395.18079694059173,
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"y": -222.8935573325382
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},
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"dragging": false
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},
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@@ -764,7 +764,7 @@
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"inputs": {
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"functionInputVariables": "{\"sqlQuery\":\"{{setVariable_1.data.instance}}\"}",
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"functionName": "Run SQL Query",
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"javascriptFunction": "const HOST = 'singlestore-host';\nconst USER = 'admin';\nconst PASSWORD = 'mypassword';\nconst DATABASE = 'mydb';\nconst TABLE = 'samples';\nconst mysql = require('mysql2/promise');\n\nlet result;\n\nfunction getSQLResult() {\n return new Promise(async (resolve, reject) => {\n \n const singleStoreConnection = mysql.createPool({\n host: HOST,\n user: USER,\n password: PASSWORD,\n database: DATABASE,\n });\n \n const [rows] = await singleStoreConnection.execute(\n $sqlQuery\n );\n\n result = JSON.stringify(rows)\n \n resolve();\n });\n}\n\nasync function main() {\n await getSQLResult();\n}\n\nawait main();\n\nreturn result;"
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"javascriptFunction": "const HOST = 'singlestore-host.com';\nconst USER = 'admin';\nconst PASSWORD = 'mypassword';\nconst DATABASE = 'mydb';\nconst TABLE = 'samples';\nconst mysql = require('mysql2/promise');\n\nlet result;\n\nfunction getSQLResult() {\n return new Promise(async (resolve, reject) => {\n try {\n const singleStoreConnection = mysql.createPool({\n host: HOST,\n user: USER,\n password: PASSWORD,\n database: DATABASE,\n });\n \n const [rows] = await singleStoreConnection.execute(\n $sqlQuery\n );\n \n result = JSON.stringify(rows)\n \n resolve();\n } catch (e) {\n console.error(e);\n return reject(e);\n }\n });\n}\n\nasync function main() {\n await getSQLResult();\n}\n\nawait main();\n\nreturn result;"
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},
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"outputAnchors": [
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{
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@@ -859,8 +859,8 @@
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"height": 355,
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"id": "setVariable_0",
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"position": {
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"x": 247.02296459986826,
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"y": -60.27462140472403
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"x": 18.689175061831122,
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"y": -62.81166351070223
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},
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"type": "customNode",
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"data": {
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@@ -918,8 +918,8 @@
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},
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"selected": false,
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"positionAbsolute": {
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"x": 247.02296459986826,
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"y": -60.27462140472403
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"x": 18.689175061831122,
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"y": -62.81166351070223
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"dragging": false
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},
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@@ -1046,8 +1046,8 @@
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"height": 355,
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"id": "setVariable_1",
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"position": {
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"x": 1482.8091395089693,
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"y": -33.943355212355016
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"x": 1516.338224315744,
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"y": -133.6986023683283
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},
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"type": "customNode",
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"data": {
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@@ -1079,7 +1079,7 @@
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}
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],
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"inputs": {
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"input": ["{{llmChain_0.data.instance}}"],
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"input": ["{{ifElseFunction_0.data.instance}}"],
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"variableName": "sqlQuery"
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},
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"outputAnchors": [
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@@ -1105,8 +1105,454 @@
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},
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"selected": false,
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"positionAbsolute": {
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"x": 1482.8091395089693,
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"y": -33.943355212355016
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"x": 1516.338224315744,
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"y": -133.6986023683283
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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": 755,
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"id": "ifElseFunction_0",
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"position": {
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"x": 1147.8020838770517,
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"y": -237.39478763322148
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},
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"type": "customNode",
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"data": {
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"id": "ifElseFunction_0",
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"label": "IfElse Function",
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"version": 1,
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"name": "ifElseFunction",
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"type": "IfElseFunction",
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"baseClasses": ["IfElseFunction", "Utilities"],
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"category": "Utilities",
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"description": "Split flows based on If Else javascript functions",
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"inputParams": [
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{
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"label": "Input Variables",
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"name": "functionInputVariables",
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"description": "Input variables can be used in the function with prefix $. For example: $var",
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"type": "json",
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"optional": true,
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"acceptVariable": true,
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"list": true,
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"id": "ifElseFunction_0-input-functionInputVariables-json"
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},
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{
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"label": "IfElse Name",
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"name": "functionName",
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"type": "string",
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"optional": true,
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"placeholder": "If Condition Match",
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"id": "ifElseFunction_0-input-functionName-string"
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},
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{
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"label": "If Function",
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"name": "ifFunction",
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"description": "Function must return a value",
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"type": "code",
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"rows": 2,
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"default": "if (\"hello\" == \"hello\") {\n return true;\n}",
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"id": "ifElseFunction_0-input-ifFunction-code"
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},
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{
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"label": "Else Function",
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"name": "elseFunction",
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"description": "Function must return a value",
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"type": "code",
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"rows": 2,
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"default": "return false;",
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"id": "ifElseFunction_0-input-elseFunction-code"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"functionInputVariables": "{\"sqlQuery\":\"{{llmChain_0.data.instance}}\"}",
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"functionName": "IF SQL Query contains SELECT and WHERE",
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"ifFunction": "const sqlQuery = $sqlQuery.trim();\n\nif (sqlQuery.includes(\"SELECT\") && sqlQuery.includes(\"WHERE\")) {\n return sqlQuery;\n}",
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"elseFunction": "return $sqlQuery;"
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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": "ifElseFunction_0-output-returnTrue-string|number|boolean|json|array",
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"name": "returnTrue",
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"label": "True",
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"type": "string | number | boolean | json | array"
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},
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{
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"id": "ifElseFunction_0-output-returnFalse-string|number|boolean|json|array",
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"name": "returnFalse",
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"label": "False",
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"type": "string | number | boolean | json | array"
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}
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],
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"default": "returnTrue"
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}
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],
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"outputs": {
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"output": "returnTrue"
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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": 1147.8020838770517,
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"y": -237.39478763322148
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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": 511,
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"id": "promptTemplate_2",
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"position": {
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"x": 1530.0647779039386,
|
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"y": 944.9904482583751
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},
|
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"type": "customNode",
|
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"data": {
|
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"id": "promptTemplate_2",
|
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"label": "Prompt Template",
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"version": 1,
|
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"name": "promptTemplate",
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"type": "PromptTemplate",
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"baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate", "Runnable"],
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"category": "Prompts",
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"description": "Schema to represent a basic prompt for an LLM",
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"inputParams": [
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{
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"label": "Template",
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"name": "template",
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"type": "string",
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"rows": 4,
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"placeholder": "What is a good name for a company that makes {product}?",
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"id": "promptTemplate_2-input-template-string"
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},
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{
|
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"label": "Format Prompt Values",
|
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"name": "promptValues",
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"type": "json",
|
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"optional": true,
|
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"acceptVariable": true,
|
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"list": true,
|
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"id": "promptTemplate_2-input-promptValues-json"
|
||||
}
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],
|
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"inputAnchors": [],
|
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"inputs": {
|
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"template": "Politely say \"I'm not able to answer query\"",
|
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"promptValues": "{\"schema\":\"{{setVariable_0.data.instance}}\",\"question\":\"{{question}}\"}"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "promptTemplate_2-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
|
||||
"name": "promptTemplate",
|
||||
"label": "PromptTemplate",
|
||||
"type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate | Runnable"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
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"positionAbsolute": {
|
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"x": 1530.0647779039386,
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"y": 944.9904482583751
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"width": 300,
|
||||
"height": 574,
|
||||
"id": "chatOpenAI_2",
|
||||
"position": {
|
||||
"x": 1537.0307928738125,
|
||||
"y": 330.7727229610632
|
||||
},
|
||||
"type": "customNode",
|
||||
"data": {
|
||||
"id": "chatOpenAI_2",
|
||||
"label": "ChatOpenAI",
|
||||
"version": 2,
|
||||
"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_2-input-credential-credential"
|
||||
},
|
||||
{
|
||||
"label": "Model Name",
|
||||
"name": "modelName",
|
||||
"type": "options",
|
||||
"options": [
|
||||
{
|
||||
"label": "gpt-4",
|
||||
"name": "gpt-4"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-1106-preview",
|
||||
"name": "gpt-4-1106-preview"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-vision-preview",
|
||||
"name": "gpt-4-vision-preview"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-0613",
|
||||
"name": "gpt-4-0613"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-32k",
|
||||
"name": "gpt-4-32k"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-32k-0613",
|
||||
"name": "gpt-4-32k-0613"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo",
|
||||
"name": "gpt-3.5-turbo"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo-1106",
|
||||
"name": "gpt-3.5-turbo-1106"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo-0613",
|
||||
"name": "gpt-3.5-turbo-0613"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo-16k",
|
||||
"name": "gpt-3.5-turbo-16k"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo-16k-0613",
|
||||
"name": "gpt-3.5-turbo-16k-0613"
|
||||
}
|
||||
],
|
||||
"default": "gpt-3.5-turbo",
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_2-input-modelName-options"
|
||||
},
|
||||
{
|
||||
"label": "Temperature",
|
||||
"name": "temperature",
|
||||
"type": "number",
|
||||
"step": 0.1,
|
||||
"default": 0.9,
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_2-input-temperature-number"
|
||||
},
|
||||
{
|
||||
"label": "Max Tokens",
|
||||
"name": "maxTokens",
|
||||
"type": "number",
|
||||
"step": 1,
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-maxTokens-number"
|
||||
},
|
||||
{
|
||||
"label": "Top Probability",
|
||||
"name": "topP",
|
||||
"type": "number",
|
||||
"step": 0.1,
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-topP-number"
|
||||
},
|
||||
{
|
||||
"label": "Frequency Penalty",
|
||||
"name": "frequencyPenalty",
|
||||
"type": "number",
|
||||
"step": 0.1,
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-frequencyPenalty-number"
|
||||
},
|
||||
{
|
||||
"label": "Presence Penalty",
|
||||
"name": "presencePenalty",
|
||||
"type": "number",
|
||||
"step": 0.1,
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-presencePenalty-number"
|
||||
},
|
||||
{
|
||||
"label": "Timeout",
|
||||
"name": "timeout",
|
||||
"type": "number",
|
||||
"step": 1,
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-timeout-number"
|
||||
},
|
||||
{
|
||||
"label": "BasePath",
|
||||
"name": "basepath",
|
||||
"type": "string",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-basepath-string"
|
||||
},
|
||||
{
|
||||
"label": "BaseOptions",
|
||||
"name": "baseOptions",
|
||||
"type": "json",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_2-input-baseOptions-json"
|
||||
}
|
||||
],
|
||||
"inputAnchors": [
|
||||
{
|
||||
"label": "Cache",
|
||||
"name": "cache",
|
||||
"type": "BaseCache",
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_2-input-cache-BaseCache"
|
||||
}
|
||||
],
|
||||
"inputs": {
|
||||
"cache": "",
|
||||
"modelName": "gpt-3.5-turbo-16k",
|
||||
"temperature": "0.7",
|
||||
"maxTokens": "",
|
||||
"topP": "",
|
||||
"frequencyPenalty": "",
|
||||
"presencePenalty": "",
|
||||
"timeout": "",
|
||||
"basepath": "",
|
||||
"baseOptions": ""
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "chatOpenAI_2-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
|
||||
"name": "chatOpenAI",
|
||||
"label": "ChatOpenAI",
|
||||
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 1537.0307928738125,
|
||||
"y": 330.7727229610632
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"width": 300,
|
||||
"height": 507,
|
||||
"id": "llmChain_2",
|
||||
"position": {
|
||||
"x": 2077.2866807477812,
|
||||
"y": 958.6594167386253
|
||||
},
|
||||
"type": "customNode",
|
||||
"data": {
|
||||
"id": "llmChain_2",
|
||||
"label": "LLM Chain",
|
||||
"version": 3,
|
||||
"name": "llmChain",
|
||||
"type": "LLMChain",
|
||||
"baseClasses": ["LLMChain", "BaseChain", "Runnable"],
|
||||
"category": "Chains",
|
||||
"description": "Chain to run queries against LLMs",
|
||||
"inputParams": [
|
||||
{
|
||||
"label": "Chain Name",
|
||||
"name": "chainName",
|
||||
"type": "string",
|
||||
"placeholder": "Name Your Chain",
|
||||
"optional": true,
|
||||
"id": "llmChain_2-input-chainName-string"
|
||||
}
|
||||
],
|
||||
"inputAnchors": [
|
||||
{
|
||||
"label": "Language Model",
|
||||
"name": "model",
|
||||
"type": "BaseLanguageModel",
|
||||
"id": "llmChain_2-input-model-BaseLanguageModel"
|
||||
},
|
||||
{
|
||||
"label": "Prompt",
|
||||
"name": "prompt",
|
||||
"type": "BasePromptTemplate",
|
||||
"id": "llmChain_2-input-prompt-BasePromptTemplate"
|
||||
},
|
||||
{
|
||||
"label": "Output Parser",
|
||||
"name": "outputParser",
|
||||
"type": "BaseLLMOutputParser",
|
||||
"optional": true,
|
||||
"id": "llmChain_2-input-outputParser-BaseLLMOutputParser"
|
||||
},
|
||||
{
|
||||
"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": "llmChain_2-input-inputModeration-Moderation"
|
||||
}
|
||||
],
|
||||
"inputs": {
|
||||
"model": "{{chatOpenAI_2.data.instance}}",
|
||||
"prompt": "{{promptTemplate_2.data.instance}}",
|
||||
"outputParser": "",
|
||||
"inputModeration": "",
|
||||
"chainName": "Fallback Chain"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"name": "output",
|
||||
"label": "Output",
|
||||
"type": "options",
|
||||
"options": [
|
||||
{
|
||||
"id": "llmChain_2-output-llmChain-LLMChain|BaseChain|Runnable",
|
||||
"name": "llmChain",
|
||||
"label": "LLM Chain",
|
||||
"type": "LLMChain | BaseChain | Runnable"
|
||||
},
|
||||
{
|
||||
"id": "llmChain_2-output-outputPrediction-string|json",
|
||||
"name": "outputPrediction",
|
||||
"label": "Output Prediction",
|
||||
"type": "string | json"
|
||||
}
|
||||
],
|
||||
"default": "llmChain"
|
||||
}
|
||||
],
|
||||
"outputs": {
|
||||
"output": "llmChain"
|
||||
},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 2077.2866807477812,
|
||||
"y": 958.6594167386253
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
@@ -1211,17 +1657,6 @@
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "llmChain_0",
|
||||
"sourceHandle": "llmChain_0-output-outputPrediction-string|json",
|
||||
"target": "setVariable_1",
|
||||
"targetHandle": "setVariable_1-input-input-string | number | boolean | json | array",
|
||||
"type": "buttonedge",
|
||||
"id": "llmChain_0-llmChain_0-output-outputPrediction-string|json-setVariable_1-setVariable_1-input-input-string | number | boolean | json | array",
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "setVariable_1",
|
||||
"sourceHandle": "setVariable_1-output-output-string|number|boolean|json|array",
|
||||
@@ -1232,6 +1667,46 @@
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "llmChain_0",
|
||||
"sourceHandle": "llmChain_0-output-outputPrediction-string|json",
|
||||
"target": "ifElseFunction_0",
|
||||
"targetHandle": "ifElseFunction_0-input-functionInputVariables-json",
|
||||
"type": "buttonedge",
|
||||
"id": "llmChain_0-llmChain_0-output-outputPrediction-string|json-ifElseFunction_0-ifElseFunction_0-input-functionInputVariables-json"
|
||||
},
|
||||
{
|
||||
"source": "ifElseFunction_0",
|
||||
"sourceHandle": "ifElseFunction_0-output-returnTrue-string|number|boolean|json|array",
|
||||
"target": "setVariable_1",
|
||||
"targetHandle": "setVariable_1-input-input-string | number | boolean | json | array",
|
||||
"type": "buttonedge",
|
||||
"id": "ifElseFunction_0-ifElseFunction_0-output-returnTrue-string|number|boolean|json|array-setVariable_1-setVariable_1-input-input-string | number | boolean | json | array"
|
||||
},
|
||||
{
|
||||
"source": "ifElseFunction_0",
|
||||
"sourceHandle": "ifElseFunction_0-output-returnFalse-string|number|boolean|json|array",
|
||||
"target": "promptTemplate_2",
|
||||
"targetHandle": "promptTemplate_2-input-promptValues-json",
|
||||
"type": "buttonedge",
|
||||
"id": "ifElseFunction_0-ifElseFunction_0-output-returnFalse-string|number|boolean|json|array-promptTemplate_2-promptTemplate_2-input-promptValues-json"
|
||||
},
|
||||
{
|
||||
"source": "chatOpenAI_2",
|
||||
"sourceHandle": "chatOpenAI_2-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
|
||||
"target": "llmChain_2",
|
||||
"targetHandle": "llmChain_2-input-model-BaseLanguageModel",
|
||||
"type": "buttonedge",
|
||||
"id": "chatOpenAI_2-chatOpenAI_2-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-llmChain_2-llmChain_2-input-model-BaseLanguageModel"
|
||||
},
|
||||
{
|
||||
"source": "promptTemplate_2",
|
||||
"sourceHandle": "promptTemplate_2-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
|
||||
"target": "llmChain_2",
|
||||
"targetHandle": "llmChain_2-input-prompt-BasePromptTemplate",
|
||||
"type": "buttonedge",
|
||||
"id": "promptTemplate_2-promptTemplate_2-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable-llmChain_2-llmChain_2-input-prompt-BasePromptTemplate"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user