AI Learning & Experimentation Hub - A comprehensive repository for exploring AI technologies, automation workflows, and intelligent systems
This repository serves as a practical AI learning playground where I experiment with cutting-edge AI technologies, automation workflows, and intelligent systems. It's designed to showcase hands-on experience with:
- 🧠 Large Language Models (LLMs)
- 🔍 Retrieval-Augmented Generation (RAG)
- 🤖 AI Agents & Autonomous Systems
- 🔗 Workflow Automation with n8n
- 🌐 Web Scraping & Data Collection
- 💬 WhatsApp Automation & Webhooks
- 📊 Vector Databases & Embeddings
fran-with-ai/
├── 🔧 n8n/ # Workflow Automation & AI Orchestration
│ ├── archivos/ # Document storage & processing
│ │ ├── cargados/ # Processed documents for RAG
│ │ └── por cargar/ # Documents queue for processing
│ ├── n8n-qdrant/ # Vector database integration
│ ├── n8n_data/ # n8n workflow data & configs
│ ├── ollama_works_v1.json # LLM integration workflow
│ ├── qdrant_embed_test.json # Embedding experiments
│ ├── qdrant_query.json # Vector search workflows
│ └── docker-compose.yaml # Containerized AI stack
│
├── 🕷️ scrapping/ # Web Scraping & Data Collection
│ ├── drivers/ # Browser automation drivers
│ ├── archivos/ # Scraped data storage
│ ├── envios_usar.py # WhatsApp automation script
│ ├── cargar_data.py # Data processing utilities
│ └── *.csv # Extracted datasets
│
├── 📱 wp-webhook/ # WhatsApp Integration & Webhooks
│ ├── index.js # WhatsApp Web.js integration
│ ├── package.json # Node.js dependencies
│ └── node_modules/ # (ignored) Dependencies
│
└── 📝 .gitignore # Clean repository management
- 🦙 Ollama - Local LLM deployment (Phi-3, Llama, etc.)
- 🔍 Qdrant - Vector database for embeddings
- 🧠 LangChain - AI agent frameworks
- 📊 RAG Systems - Document retrieval & generation
- 🔗 n8n - Visual workflow automation
- 🐳 Docker - Containerized AI services
- 🪝 Webhooks - Event-driven integrations
- ⚡ API Integrations - External service connections
- 🌐 Node.js - Backend automation services
- 🕷️ Selenium - Web scraping & browser automation
- 📱 WhatsApp Web.js - WhatsApp integration
- 🐍 Python - Data processing & ML scripts
- 📄 CSV/JSON - Structured data formats
- 🗃️ Vector Databases - Semantic search capabilities
- 📚 Document Processing - Text extraction & analysis
- LLM Integration: Direct integration with Ollama models
- Memory Management: Conversational context retention
- Webhook Endpoints: API-driven AI interactions
- Multi-modal Processing: Text, document, and data analysis
- Document Ingestion: Automated text processing pipeline
- Vector Embeddings: Semantic document representation
- Intelligent Retrieval: Context-aware information extraction
- Query Processing: Natural language to database queries
- Web Scraping: Automated data collection from websites
- Message Broadcasting: Bulk messaging with personalization
- QR Authentication: Seamless WhatsApp Web integration
- Contact Management: CSV-based contact processing
- Dynamic Web Scraping: JavaScript-rendered content extraction
- Data Processing: CSV manipulation and cleaning
- Browser Automation: Human-like interaction patterns
- Error Handling: Robust scraping with recovery mechanisms
This repository demonstrates practical experience with:
✅ LLM Integration - Working with various language models
✅ Vector Databases - Implementing semantic search systems
✅ AI Agents - Building autonomous decision-making systems
✅ Workflow Automation - Creating complex AI-driven processes
✅ API Development - Building webhooks and integrations
✅ Data Engineering - Processing and transforming datasets
✅ Web Automation - Browser-based task automation
✅ Containerization - Docker-based AI service deployment
- 🐳 Docker & Docker Compose
- 🟢 Node.js (v16+)
- 🐍 Python (v3.8+)
- 🦙 Ollama (for local LLM inference)
-
Clone the repository
git clone https://github.com/your-username/fran-with-ai.git cd fran-with-ai -
Start AI Services
cd n8n docker-compose up -d -
Install Dependencies
# WhatsApp integration cd wp-webhook npm install # Python scraping tools cd ../scrapping pip install selenium pandas
-
Access n8n Workflow Designer
http://localhost:5678
- 🤖 Customer Service Automation - AI-powered WhatsApp bots
- 📊 Data Intelligence - Automated data collection & analysis
- 🔍 Document Q&A Systems - RAG-based information retrieval
- ⚡ Business Process Automation - n8n workflow orchestration
- 📱 Social Media Management - Automated messaging & engagement
- 🧠 AI Research & Experimentation - Testing new models & techniques
- Multi-modal AI Agents - Vision + Language models
- Advanced RAG Techniques - Graph-based retrieval
- Voice AI Integration - Speech-to-text workflows
- Fine-tuning Experiments - Custom model training
- Edge AI Deployment - Optimized inference pipelines
- Autonomous Data Pipelines - Self-managing ETL systems
This is a personal learning repository, but feel free to:
- 🐛 Report bugs or issues
- 💡 Suggest improvements or new experiments
- 🔄 Fork and create your own AI learning journey
- 📚 Share knowledge and best practices
This project is for educational and experimental purposes. Feel free to use and modify for your own learning!
#AI #MachineLearning #LLM #RAG #Automation #n8n #WhatsApp #WebScraping #VectorDB #Ollama #LangChain #Python #NodeJS #Docker #Embeddings #AIAgents
⭐ Star this repo if you find it useful for your AI learning journey!