{
"meta": {
"instanceId": "97d44c78f314fab340d7a5edaf7e2c274a7fbb8a7cd138f53cc742341e706fe7"
},
"nodes": [
{
"id": "fa4f8fd6-3272-4a93-8547-32d13873bbc1",
"name": "Submit batch",
"type": "n8n-nodes-base.httpRequest",
"position": [
180,
40
],
"parameters": {
"url": "https:\/\/api.anthropic.com\/v1\/messages\/batches",
"method": "POST",
"options": [],
"jsonBody": "={ \"requests\": {{ JSON.stringify($json.requests) }} }",
"sendBody": true,
"sendQuery": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"queryParameters": {
"parameters": [
[]
]
},
"headerParameters": {
"parameters": [
{
"name": "anthropic-version",
"value": "={{ $json[\"anthropic-version\"] }}"
}
]
},
"nodeCredentialType": "anthropicApi"
},
"credentials": {
"anthropicApi": {
"id": "ub0zN7IP2V83OeTf",
"name": "Anthropic account"
}
},
"typeVersion": 4.20000000000000017763568394002504646778106689453125
},
{
"id": "2916dc85-829d-491a-a7a8-de79d5356a53",
"name": "Check batch status",
"type": "n8n-nodes-base.httpRequest",
"position": [
840,
115
],
"parameters": {
"url": "=https:\/\/api.anthropic.com\/v1\/messages\/batches\/{{ $json.id }}",
"options": [],
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "anthropic-version",
"value": "={{ $('When Executed by Another Workflow').item.json[\"anthropic-version\"] }}"
}
]
},
"nodeCredentialType": "anthropicApi"
},
"credentials": {
"anthropicApi": {
"id": "ub0zN7IP2V83OeTf",
"name": "Anthropic account"
}
},
"typeVersion": 4.20000000000000017763568394002504646778106689453125
},
{
"id": "1552ec92-2f18-42f6-b67f-b6f131012b3c",
"name": "When Executed by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-40,
40
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "anthropic-version"
},
{
"name": "requests",
"type": "array"
}
]
}
},
"typeVersion": 1.100000000000000088817841970012523233890533447265625
},
{
"id": "4bd40f02-caf1-419d-8261-a149cd51a534",
"name": "Get results",
"type": "n8n-nodes-base.httpRequest",
"position": [
620,
-160
],
"parameters": {
"url": "={{ $json.results_url }}",
"options": [],
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "anthropic-version",
"value": "={{ $('When Executed by Another Workflow').item.json[\"anthropic-version\"] }}"
}
]
},
"nodeCredentialType": "anthropicApi"
},
"credentials": {
"anthropicApi": {
"id": "ub0zN7IP2V83OeTf",
"name": "Anthropic account"
}
},
"typeVersion": 4.20000000000000017763568394002504646778106689453125
},
{
"id": "5df366af-a54d-4594-a1ab-7a9df968101e",
"name": "Parse response",
"type": "n8n-nodes-base.code",
"notes": "JSONL separated by newlines",
"position": [
840,
-160
],
"parameters": {
"jsCode": "for (const item of $input.all()) {\n if (item.json && item.json.data) {\n \/\/ Split the string into individual JSON objects\n const jsonStrings = item.json.data.split('\\n');\n\n \/\/ Parse each JSON string and store them in an array\n const parsedData = jsonStrings.filter(str => str.trim() !== '').map(str => JSON.parse(str));\n\n \/\/ Replace the original json with the parsed array.\n item.json.parsed = parsedData;\n }\n}\n\nreturn $input.all();"
},
"notesInFlow": true,
"typeVersion": 2
},
{
"id": "68aa4ee2-e925-4e30-a7ab-317d8df4d9bc",
"name": "If ended processing",
"type": "n8n-nodes-base.if",
"position": [
400,
40
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "9494c5a3-d093-49c5-837f-99cd700a2f13",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.processing_status }}",
"rightValue": "ended"
}
]
}
},
"typeVersion": 2.20000000000000017763568394002504646778106689453125
},
{
"id": "2b974e3b-495b-48af-8080-c7913d7a2ba8",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-200,
-720
],
"parameters": {
"width": 1060,
"height": 520,
"content": "### This workflow automates sending batched prompts to Claude using the Anthropic API. It submits multiple prompts at once and retrieves the results.\n\n#### How to use\n\nCall this workflow with array of `requests`\n\n```json\n{\n \"anthropic-version\": \"2023-06-01\",\n \"requests\": [\n {\n \"custom_id\": \"first-prompt-in-my-batch\",\n \"params\": {\n \"max_tokens\": 100,\n \"messages\": [\n {\n \"content\": \"Hey Claude, tell me a short fun fact about video games!\",\n \"role\": \"user\"\n }\n ],\n \"model\": \"claude-3-5-haiku-20241022\"\n }\n }\n ]\n}\n```\n"
},
"typeVersion": 1
},
{
"id": "928a30b5-5d90-4648-a82e-e4f1a01e47a5",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1200,
-720
],
"parameters": {
"width": 980,
"height": 600,
"content": "#### Results\n\nThis workflow returns an array of results with custom_ids.\n\n```json\n[\n {\n \"custom_id\": \"first-prompt-in-my-batch\",\n \"result\": {\n \"message\": {\n \"content\": [\n {\n \"text\": \"Did you know that the classic video game Tetris was...\",\n \"type\": \"text\"\n }\n ],\n \"id\": \"msg_01AiLiVZT18XnoBD4r2w9x2t\",\n \"model\": \"claude-3-5-haiku-20241022\",\n \"role\": \"assistant\",\n \"stop_reason\": \"end_turn\",\n \"stop_sequence\": null,\n \"type\": \"message\",\n \"usage\": {\n \"cache_creation_input_tokens\": 0,\n \"cache_read_input_tokens\": 0,\n \"input_tokens\": 45,\n \"output_tokens\": 83\n }\n },\n \"type\": \"succeeded\"\n }\n }\n]\n```"
},
"typeVersion": 1
},
{
"id": "5dcb554e-32df-4883-b5a1-b40305756201",
"name": "Batch Status Poll Interval",
"type": "n8n-nodes-base.wait",
"position": [
620,
40
],
"webhookId": "7efafe72-063a-45c6-8775-fcec14e1d263",
"parameters": {
"amount": 10
},
"typeVersion": 1.100000000000000088817841970012523233890533447265625
},
{
"id": "c25cfde5-ab83-4e5a-a66f-8cc9f23a01f6",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-160,
325
],
"parameters": {
"color": 4,
"width": 340,
"height": 620,
"content": "# Usage example"
},
"typeVersion": 1
},
{
"id": "6062ca7c-aa08-4805-9c96-65e5be8a38fd",
"name": "Run example",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-40,
625
],
"parameters": [],
"typeVersion": 1
},
{
"id": "9878729a-123d-4460-a582-691ca8cedf98",
"name": "One query example",
"type": "n8n-nodes-base.set",
"position": [
634,
775
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "1ea47ba2-64be-4d69-b3db-3447cde71645",
"name": "query",
"type": "string",
"value": "Hey Claude, tell me a short fun fact about bees!"
}
]
}
},
"typeVersion": 3.399999999999999911182158029987476766109466552734375
},
{
"id": "df06c209-8b6a-4b6d-8045-230ebdfcfbad",
"name": "Delete original properties",
"type": "n8n-nodes-base.set",
"position": [
1528,
775
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "d238d62b-2e91-4242-b509-8cfc698d2252",
"name": "custom_id",
"type": "string",
"value": "={{ $json.custom_id }}"
},
{
"id": "21e07c09-92e3-41e7-8335-64653722e7e9",
"name": "params",
"type": "object",
"value": "={{ $json.params }}"
}
]
}
},
"typeVersion": 3.399999999999999911182158029987476766109466552734375
},
{
"id": "f66d6a89-ee33-4494-9476-46f408976b29",
"name": "Construct 'requests' array",
"type": "n8n-nodes-base.aggregate",
"position": [
1968,
625
],
"parameters": {
"options": [],
"aggregate": "aggregateAllItemData",
"destinationFieldName": "requests"
},
"typeVersion": 1
},
{
"id": "0f9eb605-d629-4cb7-b9cb-39702d201567",
"name": "Set desired 'anthropic-version'",
"type": "n8n-nodes-base.set",
"notes": "2023-06-01",
"position": [
2188,
625
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "9f9e94a0-304b-487a-8762-d74421ef4cc0",
"name": "anthropic-version",
"type": "string",
"value": "2023-06-01"
}
]
},
"includeOtherFields": true
},
"notesInFlow": true,
"typeVersion": 3.399999999999999911182158029987476766109466552734375
},
{
"id": "f71f261c-f4ad-4c9f-bd72-42ab386a65e1",
"name": "Execute Workflow 'Process Multiple Prompts in Parallel with Anthropic Claude Batch API'",
"type": "n8n-nodes-base.executeWorkflow",
"notes": "See above",
"position": [
2408,
625
],
"parameters": {
"options": {
"waitForSubWorkflow": true
},
"workflowId": {
"__rl": true,
"mode": "list",
"value": "xQU4byMGhgFxnTIH",
"cachedResultName": "Process Multiple Prompts in Parallel with Anthropic Claude Batch API"
},
"workflowInputs": {
"value": {
"requests": "={{ $json.requests }}",
"anthropic-version": "={{ $json['anthropic-version'] }}"
},
"schema": [
{
"id": "anthropic-version",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "anthropic-version",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "requests",
"type": "array",
"display": true,
"removed": false,
"required": false,
"displayName": "requests",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"requests"
],
"attemptToConvertTypes": true,
"convertFieldsToString": true
}
},
"notesInFlow": true,
"typeVersion": 1.1999999999999999555910790149937383830547332763671875
},
{
"id": "bd27c1a6-572c-420d-84ab-4d8b7d14311b",
"name": "Build batch 'request' object for single query",
"type": "n8n-nodes-base.code",
"position": [
1308,
775
],
"parameters": {
"jsCode": "\/\/ Loop over input items and modify them to match the response example, then return input.all()\nfor (const item of $input.all()) {\n item.json.params = {\n max_tokens: item.json.max_tokens,\n messages: [\n {\n content: item.json.query,\n role: \"user\"\n }\n ],\n model: item.json.model\n };\n}\n\nreturn $input.all();\n"
},
"typeVersion": 2
},
{
"id": "fa342231-ea94-43ab-8808-18c8d04fdaf8",
"name": "Simple Memory Store",
"type": "@n8n\/n8n-nodes-langchain.memoryBufferWindow",
"position": [
644,
595
],
"parameters": {
"sessionKey": "\"Process Multiple Prompts in Parallel with Anthropic Claude Batch API example\"",
"sessionIdType": "customKey"
},
"typeVersion": 1.3000000000000000444089209850062616169452667236328125
},
{
"id": "67047fe6-8658-45ba-be61-52cf6115f4e4",
"name": "Fill Chat Memory with example data",
"type": "@n8n\/n8n-nodes-langchain.memoryManager",
"position": [
556,
375
],
"parameters": {
"mode": "insert",
"messages": {
"messageValues": [
{
"message": "You are a helpful AI assistant"
},
{
"type": "user",
"message": "Hey Claude, tell me a short fun fact about video games!"
},
{
"type": "ai",
"message": "short fun fact about video games!"
},
{
"type": "user",
"message": "No, an actual fun fact"
}
]
}
},
"typeVersion": 1.100000000000000088817841970012523233890533447265625
},
{
"id": "dbb295b8-01fd-445f-ab66-948442b6c71d",
"name": "Build batch 'request' object from Chat Memory and execution data",
"type": "n8n-nodes-base.code",
"position": [
1528,
475
],
"parameters": {
"jsCode": "const output = [];\n\nfor (const item of $input.all()) {\n const inputMessages = item.json.messages;\n const customId = item.json.custom_id;\n const model = item.json.model;\n const maxTokens = item.json.max_tokens;\n\n if (inputMessages && inputMessages.length > 0) {\n let systemMessageContent = undefined;\n const transformedMessages = [];\n\n \/\/ Process each message entry in sequence\n for (const messageObj of inputMessages) {\n \/\/ Extract system message if present\n if ('system' in messageObj) {\n systemMessageContent = messageObj.system;\n }\n \n \/\/ Process human and AI messages in the order they appear in the object keys\n \/\/ We need to determine what order the keys appear in the original object\n const keys = Object.keys(messageObj);\n \n for (const key of keys) {\n if (key === 'human') {\n transformedMessages.push({\n role: \"user\",\n content: messageObj.human\n });\n } else if (key === 'ai') {\n transformedMessages.push({\n role: \"assistant\",\n content: messageObj.ai\n });\n }\n \/\/ Skip 'system' as we already processed it\n }\n }\n\n const params = {\n model: model,\n max_tokens: maxTokens,\n messages: transformedMessages\n };\n\n if (systemMessageContent !== undefined) {\n params.system = systemMessageContent;\n }\n\n output.push({\n custom_id: customId,\n params: params\n });\n }\n}\n\nreturn output;"
},
"typeVersion": 2
},
{
"id": "f9edb335-c33d-45fc-8f9b-12d7f37cc23e",
"name": "Load Chat Memory Data",
"type": "@n8n\/n8n-nodes-langchain.memoryManager",
"position": [
932,
475
],
"parameters": {
"options": []
},
"typeVersion": 1.100000000000000088817841970012523233890533447265625
},
{
"id": "22399660-ebe5-4838-bad3-c542d6d921a3",
"name": "First Prompt Result",
"type": "n8n-nodes-base.executionData",
"position": [
2848,
525
],
"parameters": {
"dataToSave": {
"values": [
{
"key": "assistant_response",
"value": "={{ $json.result.message.content[0].text }}"
}
]
}
},
"typeVersion": 1
},
{
"id": "0e7f44f4-c931-4e0f-aebc-1b8f0327647f",
"name": "Second Prompt Result",
"type": "n8n-nodes-base.executionData",
"position": [
2848,
725
],
"parameters": {
"dataToSave": {
"values": [
{
"key": "assistant_response",
"value": "={{ $json.result.message.content[0].text }}"
}
]
}
},
"typeVersion": 1
},
{
"id": "e42b01e0-8fc5-42e1-aa45-aa85477e766b",
"name": "Split Out Parsed Results",
"type": "n8n-nodes-base.splitOut",
"position": [
1060,
-160
],
"parameters": {
"options": [],
"fieldToSplitOut": "parsed"
},
"typeVersion": 1
},
{
"id": "343676b9-f147-4981-b555-8af570374e8c",
"name": "Filter Second Prompt Results",
"type": "n8n-nodes-base.filter",
"position": [
2628,
725
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "9e4b3524-7066-46cc-a365-8d23d08c1bda",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.custom_id }}",
"rightValue": "={{ $('Append execution data for single query example').item.json.custom_id }}"
}
]
}
},
"typeVersion": 2.20000000000000017763568394002504646778106689453125
},
{
"id": "c9f5f366-27c4-4401-965b-67c314036fb6",
"name": "Filter First Prompt Results",
"type": "n8n-nodes-base.filter",
"position": [
2628,
525
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "9e4b3524-7066-46cc-a365-8d23d08c1bda",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.custom_id }}",
"rightValue": "={{ $('Append execution data for chat memory example').item.json.custom_id }}"
}
]
}
},
"typeVersion": 2.20000000000000017763568394002504646778106689453125
},
{
"id": "0a5b9c3d-665b-4e35-be9e-c8297314969d",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
110,
-100
],
"parameters": {
"height": 300,
"content": "## Submit batch request to Anthropic"
},
"typeVersion": 1
},
{
"id": "f19813a5-f669-45dd-a446-947a30b02b09",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
350,
-5
],
"parameters": {
"width": 640,
"height": 300,
"content": "## Loop until processing status is 'ended'"
},
"typeVersion": 1
},
{
"id": "9f424fce-5610-4b85-9be6-4c2c403002db",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
500,
-200
],
"parameters": {
"width": 280,
"height": 180,
"content": "### Retrieve Message Batch Results\n\n[User guide](https:\/\/docs.anthropic.com\/en\/docs\/build-with-claude\/batch-processing)"
},
"typeVersion": 1
},
{
"id": "b87673b1-f08d-4c51-8ee5-4d54557cb382",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
380
],
"parameters": {
"color": 5,
"width": 820,
"height": 340,
"content": "# Example usage with Chat History Node"
},
"typeVersion": 1
},
{
"id": "d6d8ac02-7005-40a1-9950-9517e98e315c",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
180,
720
],
"parameters": {
"width": 1540,
"height": 220,
"content": "# Example usage with single query string"
},
"typeVersion": 1
},
{
"id": "0d63deb0-dece-4502-9020-d67c1f194466",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
180,
320
],
"parameters": {
"color": 3,
"width": 660,
"height": 400,
"content": "# Environment setup\nFor Chat History Node"
},
"typeVersion": 1
},
{
"id": "cab94e09-6b84-4a38-b854-670241744db5",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
2120,
800
],
"parameters": {
"height": 220,
"content": "## anthropic-version\n\n[Documentation](https:\/\/docs.anthropic.com\/en\/api\/versioning)\n\nWhen making API requests, you must send an anthropic-version request header. For example, anthropic-version: `2023-06-01` (latest supported version)"
},
"typeVersion": 1
},
{
"id": "ab0a51a1-3c84-4a88-968b-fd46ab07de85",
"name": "Sticky Note10",
"type": "n8n-nodes-base.stickyNote",
"position": [
2560,
400
],
"parameters": {
"color": 5,
"width": 480,
"height": 300,
"content": "# Example usage with Chat History Node (result)"
},
"typeVersion": 1
},
{
"id": "d91b9be7-ef32-48d6-b880-cab0e99ba9bc",
"name": "Sticky Note11",
"type": "n8n-nodes-base.stickyNote",
"position": [
2560,
700
],
"parameters": {
"width": 480,
"height": 300,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n# Example usage with single query string (result)"
},
"typeVersion": 1
},
{
"id": "341811e9-6677-42d9-be28-c388dbf68101",
"name": "Join two example requests into array",
"type": "n8n-nodes-base.merge",
"position": [
1748,
625
],
"parameters": [],
"typeVersion": 3.100000000000000088817841970012523233890533447265625
},
{
"id": "45a09f05-7610-4b0a-ab7f-0094c4b3f318",
"name": "Append execution data for single query example",
"type": "n8n-nodes-base.set",
"notes": "custom_id, model and max tokens",
"position": [
1010,
775
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "8276602f-689f-45c2-bce0-5df8500912b6",
"name": "custom_id",
"type": "string",
"value": "second-prompt-in-my-batch"
},
{
"id": "2c513dc2-d8cb-4ba3-b3c1-ea79517b9434",
"name": "model",
"type": "string",
"value": "claude-3-5-haiku-20241022"
},
{
"id": "b052140b-1152-4327-9c5a-5030b78990b7",
"name": "max_tokens",
"type": "number",
"value": 100
}
]
},
"includeOtherFields": true
},
"notesInFlow": true,
"typeVersion": 3.399999999999999911182158029987476766109466552734375
},
{
"id": "c4e35349-840c-4c81-852c-0d8cd9331364",
"name": "Append execution data for chat memory example",
"type": "n8n-nodes-base.set",
"notes": "custom_id, model and max tokens",
"position": [
1308,
475
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "8276602f-689f-45c2-bce0-5df8500912b6",
"name": "custom_id",
"type": "string",
"value": "first-prompt-in-my-batch"
},
{
"id": "2c513dc2-d8cb-4ba3-b3c1-ea79517b9434",
"name": "model",
"type": "string",
"value": "claude-3-5-haiku-20241022"
},
{
"id": "b052140b-1152-4327-9c5a-5030b78990b7",
"name": "max_tokens",
"type": "number",
"value": 100
}
]
},
"includeOtherFields": true
},
"notesInFlow": true,
"typeVersion": 3.399999999999999911182158029987476766109466552734375
},
{
"id": "058aedb1-fdfe-4edc-8d51-3b93ec7d232d",
"name": "Truncate Chat Memory",
"type": "@n8n\/n8n-nodes-langchain.memoryManager",
"notes": "ensure clean state",
"position": [
180,
475
],
"parameters": {
"mode": "delete",
"deleteMode": "all"
},
"notesInFlow": true,
"typeVersion": 1.100000000000000088817841970012523233890533447265625
}
],
"pinData": [],
"connections": {
"Get results": {
"main": [
[
{
"node": "Parse response",
"type": "main",
"index": 0
}
]
]
},
"Run example": {
"main": [
[
{
"node": "One query example",
"type": "main",
"index": 0
},
{
"node": "Truncate Chat Memory",
"type": "main",
"index": 0
}
]
]
},
"Submit batch": {
"main": [
[
{
"node": "If ended processing",
"type": "main",
"index": 0
}
]
]
},
"Parse response": {
"main": [
[
{
"node": "Split Out Parsed Results",
"type": "main",
"index": 0
}
]
]
},
"One query example": {
"main": [
[
{
"node": "Append execution data for single query example",
"type": "main",
"index": 0
}
]
]
},
"Check batch status": {
"main": [
[
{
"node": "If ended processing",
"type": "main",
"index": 0
}
]
]
},
"If ended processing": {
"main": [
[
{
"node": "Get results",
"type": "main",
"index": 0
}
],
[
{
"node": "Batch Status Poll Interval",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory Store": {
"ai_memory": [
[
{
"node": "Load Chat Memory Data",
"type": "ai_memory",
"index": 0
},
{
"node": "Fill Chat Memory with example data",
"type": "ai_memory",
"index": 0
},
{
"node": "Truncate Chat Memory",
"type": "ai_memory",
"index": 0
}
]
]
},
"Truncate Chat Memory": {
"main": [
[
{
"node": "Fill Chat Memory with example data",
"type": "main",
"index": 0
}
]
]
},
"Load Chat Memory Data": {
"main": [
[
{
"node": "Append execution data for chat memory example",
"type": "main",
"index": 0
}
]
]
},
"Batch Status Poll Interval": {
"main": [
[
{
"node": "Check batch status",
"type": "main",
"index": 0
}
]
]
},
"Construct 'requests' array": {
"main": [
[
{
"node": "Set desired 'anthropic-version'",
"type": "main",
"index": 0
}
]
]
},
"Delete original properties": {
"main": [
[
{
"node": "Join two example requests into array",
"type": "main",
"index": 1
}
]
]
},
"Filter First Prompt Results": {
"main": [
[
{
"node": "First Prompt Result",
"type": "main",
"index": 0
}
]
]
},
"Filter Second Prompt Results": {
"main": [
[
{
"node": "Second Prompt Result",
"type": "main",
"index": 0
}
]
]
},
"Set desired 'anthropic-version'": {
"main": [
[
{
"node": "Execute Workflow 'Process Multiple Prompts in Parallel with Anthropic Claude Batch API'",
"type": "main",
"index": 0
}
]
]
},
"When Executed by Another Workflow": {
"main": [
[
{
"node": "Submit batch",
"type": "main",
"index": 0
}
]
]
},
"Fill Chat Memory with example data": {
"main": [
[
{
"node": "Load Chat Memory Data",
"type": "main",
"index": 0
}
]
]
},
"Join two example requests into array": {
"main": [
[
{
"node": "Construct 'requests' array",
"type": "main",
"index": 0
}
]
]
},
"Append execution data for chat memory example": {
"main": [
[
{
"node": "Build batch 'request' object from Chat Memory and execution data",
"type": "main",
"index": 0
}
]
]
},
"Build batch 'request' object for single query": {
"main": [
[
{
"node": "Delete original properties",
"type": "main",
"index": 0
}
]
]
},
"Append execution data for single query example": {
"main": [
[
{
"node": "Build batch 'request' object for single query",
"type": "main",
"index": 0
}
]
]
},
"Build batch 'request' object from Chat Memory and execution data": {
"main": [
[
{
"node": "Join two example requests into array",
"type": "main",
"index": 0
}
]
]
},
"Execute Workflow 'Process Multiple Prompts in Parallel with Anthropic Claude Batch API'": {
"main": [
[
{
"node": "Filter First Prompt Results",
"type": "main",
"index": 0
},
{
"node": "Filter Second Prompt Results",
"type": "main",
"index": 0
}
]
]
}
}
}
