feat: implementar sistema RAG Espiritismo completo

- Stack: GPT4All + Llama 3.2 3B, LangChain, Qdrant, FastAPI, Docker
- 11 tarefas implementadas com 100% de conclusão
- Funcionalidades: chat com IA, upload PDF, bot Telegram, agendamento
- 6 livros PDF indexados (A Gênese, Livro dos Espíritos, etc.)
- Documentação rica: README, BUILD, task reports, design specs
- Deploy com Docker Compose
- Production ready

Tech stack:
- AI: GPT4All 2.4.6, Llama 3.2 3B q4_0
- Backend: FastAPI 0.115.0, Celery 5.4.0, Redis 5.2.0
- RAG: LangChain 0.3.7, Qdrant 1.11.1
- Frontend: HTML5/CSS3/Vanilla JS
- Deploy: Docker Compose

Acceptance Criteria:
✅ CPU-only, <8GB RAM, ~5GB storage
✅ Suporta upload de PDFs
✅ Interface web rica e responsiva
✅ Bot Telegram funcional
✅ Agendamento de mensagens
✅ Código limpo e documentado
✅ Deploy via Docker

Status: PRODUCTION READY
Version: 1.0.0
Date: 2026-11-01

backend/Dockerfile

@@ -0,0 +1,33 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create directories
+RUN mkdir -p /app/uploads /app/index /app/models
+
+# Copy requirements
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Set environment variables
+ENV GPT4ALL_MODEL=llama-3.2-3b-instruct-q4_0.gguf
+ENV UPLOAD_DIR=/app/uploads
+ENV INDEX_DIR=/app/index
+ENV SCHEDULES_PATH=/app/schedules.json
+
+# Copy application
+COPY app/ ./app/
+COPY frontend/ ./frontend/
+
+# Expose ports
+EXPOSE 8000
+
+# Run the application
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]