Why it is worth attention

It showcases a complete, modern PHP stack for building an AI sales agent with LLM observability (Langfuse) and long-term memory (Mem0), offering a practical reference for developers.

Who it is for

Laravel developers exploring AI agent integration
Developers building AI-powered sales or CRM tools
Teams learning agentic patterns with streaming and memory
Tutors or learners following the accompanying video lessons

Use cases

Prototyping an AI sales agent that handles customer inquiries using CRM data
Learning how to mirror CRM pipelines and stages into local models for AI context
Demonstrating agent observability and memory in a Laravel application
Educational use for workshop or course on AI agent development

Strengths

Modular agent design using the Beer and Code Harness (skills, hooks, commands)
Built-in LLM observability via Langfuse for tracing, costs and evaluations
Long-term memory integration with Mem0 for persistent agent context
Modern Laravel stack (13, Livewire 4, Sail, Pest, PHPStan) ensures code quality

Considerations

Only supports Pipedrive as the CRM driver; other CRMs require custom development
Requires external API keys (Langfuse, Mem0) and infrastructure (Docker, queues)
Designed as a lab/demo project, not production-hardened (e.g., no authentication hardening beyond magic links)

README quick start

Lab Agent Seller

Aplicação Laravel 13 + Livewire 4 que demonstra um agente de vendas com IA. Empresas conectam um CRM (driver Pipedrive), um job em fila (ScanCrmConnection) espelha pipelines/stages/campos/pessoas/deals para modelos locais, clientes entram via magic link (guard auth:client) e conversam com o agente de vendas streaming SellerAgent (laravel/ai).

Repositórios e ferramentas usados

Projeto	Descrição	Link
Beer and Code Harness	Harness de agentes (skills, hooks, comandos e guidelines) usado no projeto	https://github.com/beerandcodeteam/beer-and-code-harness
Langfuse	Observabilidade de LLM (traces, custos, avaliações)	https://github.com/langfuse/langfuse
Mem0	Camada de memória de longo prazo para o agente	https://github.com/mem0ai/mem0

Pacotes de integração:

Langfuse — via axyr/laravel-langfuse (região US, projeto ai-lab).
Mem0 — via API HTTP (MEM0_API_KEY, MEM0_BASE_URL, MEM0_TIMEOUT no .env).

Aulas

Slides gravados neste repositório:

Aula 1 — slides-da-aula/aula-dia-1/index.html
Aula 2 — slides-da-aula/aula-dia-2/aula.html

Abra os arquivos .html direto no navegador.

Stack

PHP 8.5 · Laravel 13 · Livewire 4
laravel/ai (agente streaming)
Laravel Sail (Docker) · PostgreSQL 18 · Redis · Mailpit
Pest 4 · Larastan (PHPStan nível 7) · Pint
Tailwind CSS v4 · Vite

Setup do ambiente

Pré-requisitos: Docker, Composer 2, Node 22 + npm.

# 1. Clonar
git clone git@github.com:beerandcodeteam/lab-agent-seller.git
cd lab-agent-seller

# 2. Instalar deps PHP (necessário pra ter o binário do Sail)
composer install

# 3. Subir os containers (laravel.test PHP 8.5, pgsql 18, redis, mailpit)
vendor/bin/sail up -d

# 4. Setup completo: copia .env, key:generate, migrate --force, npm install, npm run build
vendor/bin/sail composer setup

# 5. Configurar chaves de API no .env
#    MEM0_API_KEY=...          (Mem0)
#    LANGFUSE_PUBLIC_KEY=...    (Langfuse - região US)
#    LANGFUSE_SECRET_KEY=...

Levantar o projeto

# Sobe os containers (se ainda não estiverem no ar)
vendor/bin/sail up -d

# Inicia os processos de desenvolvimento (servidor, queue, vite, logs)
vendor/bin

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