🚀 Message-Batching Buffer Workflow (n8n)
🚀 Message-Batching Buffer Workflow (n8n) This workflow implements a lightweight message-batching buffer using Redis for temporary storage and a JavaScript consolidation function to merge messages. It collects incoming user messages per session, waits for a configurable inactivity window or batch size threshold, consolidates buffered messages via custom code, then clears the buffer and returns the combined response—all without external LLM calls. 🔑 Key Features Redis-backed buffer** queues incoming messages per context_id. Centralized Config Parameters** node to adjust thresholds and timeouts in one place. Dynamic wait time** based on message length (configurable minWords, waitLong, waitShort). Batch trigger** fires on inactivity timeout or when buffer_count ≥ batchThreshold. Zero-cost consolidation** via built-in JavaScript Function (consolidate buffer)—no GPT-4 or external API required. ⚙️ Setup Instructions Extract Session & Message Trigger: When chat message received (webhook) or When clicking ‘Test workflow’ (manual). Map inputs: set variables context_id and message into a Set node named Mock input data (for testing) or a proper mapping node in production. Config Parameters Add a Set node Config Parameters with: minWords: 3 # Word threshold waitLong: 10 # Timeout (s) for long messages waitShort: 20 # Timeout (s) for short messages batchThreshold: 3 # Messages to trigger batch early All downstream nodes reference these JSON values dynamically. Determine Wait Time Node: get wait seconds (Code) JS code: const msg = $json.message || ''; const wordCount = msg.split(/\s+/).filter(w => w).length; const { minWords, waitLong, waitShort } = items[0].json; const waitSeconds = wordCount < minWords ? waitShort : waitLong; return [{ json: { context_id: $json.context_id, message: msg, waitSeconds } }]; Buffer Message in Redis Buffer messages: LPUSH buffer_in:{{$json.context_id}} with payload {text, timestamp}. Set buffer\_count increment: INCR buffer_count:{{$json.context_id}} with TTL {{$json.waitSeconds + 60}}. Set last\_seen: record last_seen:{{$json.context_id}} timestamp with same TTL. Check & Set Waiting Flag Get waiting\_reply: if null, Set waiting\_reply to true with TTL {{$json.waitSeconds}}; else exit. Wait for Inactivity WaitSeconds (webhook): pauses for {{$json.waitSeconds}} seconds before batch evaluation. Check Batch Trigger Get last\_seen and Get buffer\_count. IF (now - last_seen) ≥ waitSeconds * 1000 OR buffer_count ≥ batchThreshold, proceed; else use Wait node to retry. Consolidate Buffer consolidate buffer (Code): const j = items[0].json; const raw = Array.isArray(j.buffer) ? j.buffer : []; const buffer = raw.map(x => { try { return typeof x === 'string' ? JSON.parse(x) : x; } catch { return null; } }).filter(Boolean); buffer.sort((a, b) => new Date(a.timestamp) - new Date(b.timestamp)); const texts = buffer.map(e => e.text?.trim()).filter(Boolean); const unique = [...new Set(texts)]; const message = unique.join(' '); return [{ json: { context_id: j.context_id, message } }]; Cleanup & Respond Delete Redis keys: buffer_in, buffer_count, waiting_reply, last_seen (for the context_id). Return consolidated message to the user via your chat integration. 🛠 Customization Guidance Adjust thresholds* by editing the *Config Parameters** node. Change concatenation** (e.g., line breaks) by modifying the join separator in the consolidation code. Add filters** (e.g., ignore empty or system messages) inside the consolidation Function. Monitor performance**: for very high volume, consider sharding Redis keys by date or user segments. © 2025 Innovatex • Automation & AI Solutions • innovatexiot.carrd.co • LinkedIn. An n8n automation workflow template by Edisson Garcia.
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