Process multiple prompts in parallel with Azure OpenAI Batch API
Ready for 3.0What this workflow does
This AI workflow has 38 nodes and runs when another workflow calls it (plus 1 other trigger). It uses only n8n's built-in nodes.
How it runs
Trigger: When another workflow calls it (plus 1 other trigger).
- Setup defaults (Edit Fields (Set)): sets or maps fields
- One query example (Edit Fields (Set)): sets or maps fields
- Truncate Chat Memory (Chat Memory Manager): uses Chat Memory Manager, with memory: Simple Memory
- Set defaults if not set already (Code): runs custom JavaScript code
- Append custom_id for single query example (Edit Fields (Set)): sets or maps fields
- Fill Chat Memory with example data (Chat Memory Manager): uses Chat Memory Manager, with memory: Simple Memory
- JSON requests to JSONL (Code): runs custom JavaScript code
- Build batch 'request' object for single query (Code): runs custom JavaScript code
- Load Chat Memory Data (Chat Memory Manager): uses Chat Memory Manager, with memory: Simple Memory
- Remove original requests (Edit Fields (Set)): sets or maps fields
…plus 25 more steps. See the full node list below.
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (16)
- Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - Code
n8n-nodes-base.code - If
n8n-nodes-base.if - Wait
n8n-nodes-base.wait - Manual Trigger
n8n-nodes-base.manualTrigger - Edit Fields (Set)
n8n-nodes-base.set - Aggregate
n8n-nodes-base.aggregate - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Chat Memory Manager
@n8n/n8n-nodes-langchain.memoryManager - Execution Data
n8n-nodes-base.executionData - Split Out
n8n-nodes-base.splitOut - Filter
n8n-nodes-base.filter - Merge
n8n-nodes-base.merge - HTTP Request
n8n-nodes-base.httpRequest - Convert to File
n8n-nodes-base.convertToFile - Execute Sub-workflow
n8n-nodes-base.executeWorkflow
From the author
Process Multiple Prompts in Parallel with Azure OpenAI Batch API Who is this for? This workflow is designed for developers and data scientists who want to efficiently send multiple prompts to the Azure OpenAI Batch API and retrieve responses in a single batch…