n8n AI Dev Ops Data Management
Contributed by Sabrina Ramonov 🍄. From the community directory at agents.sabrina.dev, republished with permission and full credit.
This workflow implements a message-batching buffer using Redis for temporary storage and GPT-4 for consolidated response generation. Incoming user messages are collected in a Redis list; once a configurable “inactivity” window elapses or a batch size threshold is reached, all buffered messages are sent to GPT-4 in a single prompt. The system then clears the buffer and returns the consolidated reply.
Key Features
- Redis-backed buffer to queue incoming messages per user session
- Dynamic wait time (shorter for long messages, longer for short messages)
- Batch trigger on inactivity timeout or minimum message count
- GPT-4 consolidation: merges all buffered messages into one coherent response
Setup InstructionsMap Input
- Rename node to “Extract Session & Message”
- Assign context_id and message from webhook or manual trigger
Compute Wait Time
- Rename node to “Determine Inactivity Timeout”
- JS Code:
javascript const wordCount = $json.message.split(' ').filter(w=>w).length; return [{ json: { context_id: $json.context_id, message: $json.message, waitSeconds: wordCount < 5 ? 45 : 30 }}]; Buffer Message in Redis
- Push into list buffer_in:{{$json.context_id}}
- INCR key buffer_count:{{$json.context_id}} with TTL {{$json.waitSeconds + 60}}
Mark Waiting State
- GET waiting_reply:{{$json.context_id}} if null, SET it to true with TTL {{$json.waitSeconds}}
- Rename nodes to “Check Waiting Flag” / “Set Waiting Flag”
Wait for Inactivity
- Wait node: pause for {{$json.waitSeconds}} seconds
Check Batch Trigger
- GET keys:
- last_seen:{{$json.context_id}}
- buffer_count:{{$json.context_id}}
- IF both:
- buffer_count >= 1
- (now, last_seen) >= waitSeconds * 1000
- Rename node to “Trigger Batch on Inactivity or Count”
Fetch & Consolidate
- GET entire list buffer_in:{{$json.context_id}}
- Information Extractor rename to “Consolidate Messages”
- System prompt: “You are an expert at merging multiple messages into one clear paragraph without duplicates.”
GPT-4 Chat
- OpenAI Chat Model (GPT-4)
Cleanup & Respond
- Delete Redis keys:
- buffer_in:{{$json.context_id}}
- waiting_reply:{{$json.context_id}}
- buffer_count:{{$json.context_id}}
- Return the consolidated reply to the user
Customization Guidance
- Batch Size Trigger: Add an additional IF to fire when buffer_count reaches your desired batch size.
- Timeout Policy: Adjust the word-count thresholds or replace with character-count logic.
- Multi-Channel Support: Change the trigger from a manual test node to any webhook (e.g., chat, SMS, email).
- Error Handling: Insert a fallback branch to catch Redis timeouts or OpenAI API errors and notify users.
Tools used: OpenAI ChatGPT, Redis, CustomJS
Download the workflow template (JSON)
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