Day 7: Enhancing AI Memory for Multi-Turn Conversations #AIVoiceBot #ContextRetention

A powerful AI voice bot should remember previous interactions to provide a seamless, human-like conversation experience. Today, we’ll implement context retention in our Laravel AI call center, allowing the bot to track conversations across multiple turns.

🧠 1. Why Context Retention is Important

Without memory, AI chatbots treat each message as a separate conversation, leading to:
❌ Repetitive questions (e.g., “What’s your account number?”)
❌ Inconsistent responses (e.g., Forgetting previous details)
❌ Frustrated users

By storing previous queries, the AI can:
✅ Maintain conversation flow (e.g., “Can I change my address?” → “Yes, what’s your new address?”)
✅ Remember user details (e.g., “My order number is 1234.” → “I see, your order is being processed.”)
✅ Provide personalized responses

🔗 More on AI chat memory: OpenAI Conversation History

🛠️ 2. Implementing Conversation Memory in Laravel

We’ll store conversation history in a Redis cache or database, allowing AI to reference past interactions.

📌 Step 1: Install Laravel Redis

composer require predis/predis

📌 Step 2: Configure Redis in .env

CACHE_DRIVER=redis
REDIS_HOST=127.0.0.1
REDIS_PASSWORD=null
REDIS_PORT=6379

💾 3. Storing & Retrieving Conversation History

Now, we create a ConversationMemoryService to track previous queries.

📌 Step 1: Create Conversation Memory Service

namespace App\Services;

use Illuminate\Support\Facades\Redis;

class ConversationMemoryService
{
    public function storeMessage($sessionId, $message)
    {
        $history = Redis::get("conversation:$sessionId") ?? '[]';
        $history = json_decode($history, true);

        $history[] = ['timestamp' => now(), 'message' => $message];

        Redis::set("conversation:$sessionId", json_encode($history));
    }

    public function getConversationHistory($sessionId)
    {
        return json_decode(Redis::get("conversation:$sessionId") ?? '[]', true);
    }
}

🤖 4. Enhancing AI Responses with Memory

We’ll modify AIService to include past interactions in its response generation.

📌 Step 1: Modify AIService to Include Conversation Context

namespace App\Services;

use OpenAI;
use App\Services\ConversationMemoryService;

class AIService
{
    protected $client;
    protected $memory;

    public function __construct()
    {
        $this->client = OpenAI::factory()->withApiKey(env('OPENAI_API_KEY'))->make();
        $this->memory = new ConversationMemoryService();
    }

    public function generateResponse($sessionId, $query)
    {
        $history = $this->memory->getConversationHistory($sessionId);
        $context = implode("\n", array_column($history, 'message'));

        $response = $this->client->completions()->create([
            'model' => 'gpt-4',
            'prompt' => "Previous conversation:\n$context\nUser: $query\nAI:",
            'max_tokens' => 100,
        ]);

        $this->memory->storeMessage($sessionId, "User: $query\nAI: ".$response['choices'][0]['text']);

        return $response['choices'][0]['text'] ?? 'I couldn’t process your request.';
    }
}

📡 5. Using AI Memory in a Real Call Flow

Now, we update the call handling system to use AI memory.

📌 Step 1: Modify handleCall() to Include Context

use App\Services\AIService;
use Illuminate\Http\Request;

public function handleCall(Request $request)
{
    $sessionId = $request->input('session_id');
    $query = $request->input('query');

    $ai = new AIService();
    $response = $ai->generateResponse($sessionId, $query);

    return response()->json(['reply' => $response]);
}

📡 6. Testing Multi-Turn AI Conversations

✅ Step 1: Customer asks: “What’s my last order?”
✅ Step 2: AI checks memory and responds: “Your last order was a smartwatch on Feb 12.”
✅ Step 3: Customer follows up: “Can I cancel it?”
✅ Step 4: AI references memory and replies: “Your order is already shipped, so it can’t be canceled.”

This seamless conversation improves customer experience!

🔗 More on AI conversation tracking: Google Dialogflow Context

📝 Meta Description

“Enable AI memory in Laravel call center bots with Redis. Track conversations, improve AI responses, and create seamless multi-turn interactions! #AIVoiceBot #ContextRetention”

💡 Next: Day 8 – Integrating AI with CRM for Customer Data Access #AIVoiceBot #AIandCRM