Message Buffer System with Redis and GPT-4 for Efficient Processing

Description

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 Instructions

1. Map Input

   • Rename node to “Extract Session & Message”
   • Assign context_id and message from webhook or manual trigger

2. Compute Wait Time

   • Rename node to “Determine Inactivity Timeout”

   • JS Code:

     const wordCount = $json.message.split(' ').filter(w=>w).length;
     return [{ json: {
       context_id: $json.context_id,
       message: $json.message,
       waitSeconds: wordCount < 5 ? 45 : 30
     }}];
     

3. Buffer Message in Redis

   • Push into list buffer_in:{{$json.context_id}}
   • INCR key buffer_count:{{$json.context_id}} with TTL {{$json.waitSeconds + 60}}

4. 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”

5. Wait for Inactivity

   • Wait node: pause for {{$json.waitSeconds}} seconds

6. Check Batch Trigger

   • GET keys:

     • last_seen:{{$json.context_id}}
     • buffer_count:{{$json.context_id}}

   • IF both:

     1. buffer_count >= 1
     2. (now – last_seen) >= waitSeconds * 1000

   • Rename node to “Trigger Batch on Inactivity or Count”

7. 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.”

8. GPT-4 Chat

   • OpenAI Chat Model (GPT-4)

9. 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

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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.

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