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Darmowy szablon automatyzacji

Monity przetwarzania wsadowego z interfejsem API Anthropic Claude

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27 dni temu
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bloków

Funkcjonalność i zastosowanie

Ten szablon automatyzacji zapewnia wydajne rozwiązanie do wysyłania wielu zapytań do modeli Claude od Anthropic w ramach jednego zbiorczego żądania. Wykorzystuje endpoint API Batch (/v1/messages/batches) w celu optymalizacji procesu i zwraca wyniki jako osobne pozycje.

Dla kogo jest to rozwiązanie

Szablon został zaprojektowany dla:

  • Programistów, analityków danych i badaczy potrzebujących przetwarzać duże ilości tekstu przy użyciu modeli Claude
  • Twórców treści generujących wiele materiałów jednocześnie (np. podsumowania, Q&A)
  • Użytkowników n8n chcących zautomatyzować interakcje z API Anthropic
  • Osób potrzebujących wykonywać masowe zadania generowania lub analizy tekstu

Rozwiązywane problemy

Workflow rozwiązuje następujące problemy:

  • Grupowanie wielu zapytań w jedno żądanie API
  • Znaczne skrócenie czasu przetwarzania w porównaniu do sekwencyjnego wysyłania
  • Systematyczne zarządzanie dużymi ilościami zapytań
  • Gotowa do użycia struktura n8n dla zbiorczych interakcji
  • Strukturalizowane wyniki jako osobne pozycje

Przykłady zastosowań

Ta automatyzacja znajduje zastosowanie w wielu scenariuszach biznesowych i badawczych. Oto konkretne przypadki użycia:

  • Masowe generowanie opisów produktów dla sklepów internetowych
  • Tworzenie spersonalizowanych odpowiedzi na często zadawane pytania
  • Analiza sentymentu dla wielu opinii klientów jednocześnie
  • Automatyczne streszczanie artykułów lub dokumentów
  • Generowanie kreatywnych tekstów na różne tematy
  • Testowanie różnych wersji promptów w badaniach nad AI
  • Ekstrakcja kluczowych informacji z wielu dokumentów

Działanie głównego workflow

(Wyzwalane przez węzeł 'When Executed by Another Workflow')

  1. Odbiera dane wejściowe: wersja API i tablica żądań
  2. Wysyła zadanie wsadowe do endpointu /v1/messages/batches
  3. Czeka i sprawdza status przetwarzania w pętli
  4. Pobiera wyniki po zakończeniu przetwarzania
  5. Parsuje wyniki w formacie JSON Lines
  6. Rozdziela wyniki na osobne pozycje wyjściowe

Wymagania wstępne

  • Aktywna instancja n8n
  • Konto Anthropic API z dostępem do modeli Claude
  • Klucz API Anthropic
  • Podstawowa znajomość n8n i struktur JSON
  • Zrozumienie struktury API Batch od Anthropic

Konfiguracja

  1. Zaimportuj szablon do swojej instancji n8n
  2. Skonfiguruj poświadczenia API Anthropic
  3. Przypisz poświadczenia do trzech węzłów HTTP Request
  4. Przejrzyj format danych wejściowych
  5. Aktywuj workflow

Dostosowywanie

Możesz dostosować workflow poprzez:

  • Zmianę źródła danych wejściowych
  • Dostosowanie parametrów modelu w tablicy requests
  • Modyfikację interwału sprawdzania statusu
  • Dostosowanie logiki parsowania wyników
  • Rozszerzenie obsługi błędów
  • Dodanie własnego przetwarzania wyników

Przykładowe użycie

Szablon zawiera oddzielną gałąź demonstracyjną pokazującą:

  • Tworzenie obiektu żądania z prostego ciągu znaków
  • Tworzenie żądania z wykorzystaniem węzłów Langchain Chat Memory
  • Łączenie przykładów i wywoływanie głównej logiki przetwarzania

Uwagi

  • API pozwala na przetwarzanie do 100 000 żądań w partii
  • Korzystanie z API wiąże się z kosztami naliczanymi za tokeny
  • Czas przetwarzania zależy od złożoności promptów i obciążenia API
  • Zawsze podawaj nagłówek anthropic-version w żądaniach

   Skopiuj kod szablonu   
{"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":4.2},{"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":4.2},{"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":1.1},{"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":4.2},{"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 objectsn const jsonStrings = item.json.data.split('\n');nn // Parse each JSON string and store them in an arrayn const parsedData = jsonStrings.filter(str => str.trim() !== '').map(str => JSON.parse(str));nn // Replace the original json with the parsed array.n item.json.parsed = parsedData;n }n}nnreturn $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":2.2},{"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.nn#### How to usennCall this workflow with array of `requests`nn```jsonn{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":"#### ResultsnnThis workflow returns an array of results with custom_ids.nn```jsonn[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": 83n }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":1.1},{"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":3.4},{"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":3.4},{"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":3.4},{"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":1.2},{"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.modeln };n}nnreturn $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":1.3},{"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":1.1},{"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 = [];nnfor (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;nn if (inputMessages && inputMessages.length > 0) {n let systemMessageContent = undefined;n const transformedMessages = [];nn // Process each message entry in sequencen for (const messageObj of inputMessages) {n // Extract system message if presentn if ('system' in messageObj) {n systemMessageContent = messageObj.system;n }n n // Process human and AI messages in the order they appear in the object keysn // We need to determine what order the keys appear in the original objectn 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.humann });n } else if (key === 'ai') {n transformedMessages.push({n role: "assistant",n content: messageObj.ain });n }n // Skip 'system' as we already processed itn }n }nn const params = {n model: model,n max_tokens: maxTokens,n messages: transformedMessagesn };nn if (systemMessageContent !== undefined) {n params.system = systemMessageContent;n }nn output.push({n custom_id: customId,n params: paramsn });n }n}nnreturn 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":1.1},{"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":2.2},{"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":2.2},{"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 Resultsnn[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 setupnFor 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-versionnn[Documentation](https://docs.anthropic.com/en/api/versioning)nnWhen 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":"nnnnnnnnnnnnnnn# 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":3.1},{"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":3.4},{"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":3.4},{"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":1.1}],"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}]]}}}
  • API
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