This repository contains resources and materials for several courses by Omar Santos.

The repository is structured with five comprehensive parts covering the spectrum from basic AI concepts to advanced agentic implementations:

• part1_foundational_topics/: Foundational examples covering chat models, embeddings (with TensorFlow Projector visualization), interactive chatbots, and integration with various model providers (OpenAI, Hugging Face, Ollama)
• part2_prompt_templates/: Advanced prompt engineering techniques, template systems, and structured prompting strategies for cybersecurity applications
• part3_prompt_chaining/: Sophisticated prompt chaining workflows using LangChain Expression Language (LCEL), including branching chains, parallel processing, and conditional logic for security incident analysis and threat hunting
• part4_rag_examples/: Comprehensive Retrieval Augmented Generation implementations with vector databases (Chroma), text splitting strategies, embedding comparisons, metadata handling, and web scraping
• part5_agents_and_tools/: Advanced AI agents, tools integration, LangGraph workflows, agentic RAG, and Model Context Protocol (MCP) implementations for cybersecurity automation

This repository provides a structured learning journey covering cutting-edge AI agent technologies and their applications in cybersecurity operations.

• Chat Models: Basic chat interactions with OpenAI and LangChain (chat_model_basic.py)
• Interactive Chatbots: Complete Streamlit-based chatbot with conversation history (chatbot_example.py)
• Embeddings: Text embedding generation and visualization with TensorFlow Projector using CVE data (embeddings/)
  • 1000 CVE embeddings and metadata for hands-on visualization
  • Step-by-step guide for using TensorFlow's Embedding Projector
• Hugging Face Integration: Sentiment analysis with DistilBERT (huggingface_example.py)
• Ollama Integration: Local model deployment with streaming and multimodal capabilities (ollama/)
• Document Processing: Multimodal document analysis and chunking strategies (chunking_and_images.md)

• Advanced prompt template design and optimization
• System message crafting for cybersecurity contexts
• Multi-variable prompt construction and placeholders
• Message history management and conversation flow
• Chain-of-Thought, Tree-of-Thought, and ReAct techniques
• Meta prompting and iterative refinement strategies

• LangChain Expression Language (LCEL) fundamentals
• Sequential and parallel chain orchestration
• Conditional branching for dynamic decision-making
• Security incident analysis workflows
• Threat hunting automation with adaptive chains
• Multi-step reasoning for complex cybersecurity tasks

• Vector Database Management: Chroma vector store creation and persistence (basic_rag_part1.py, basic_rag_part2.py)
• Text Splitting Strategies: Character, sentence, token, and recursive splitting techniques (text_splitting_deep_dive.py)
• Embedding Comparisons: OpenAI vs. Hugging Face embedding models (embedding_deep_dive.py)
• Metadata Integration: Source tracking and metadata-rich vector stores (rag_basics_metadata_part1.py)
• Web Scraping: Dynamic content ingestion and processing (web_scrape_basic.py)
• Cost Optimization: Embedding cost calculation utilities (utils/embedding_cost_calculator.py)
• Cybersecurity Data: SSRF vulnerability analysis and Tesla security data examples

• Basic Agent Frameworks: ReAct agents with tool integration (basic_agent_and_tools.py)
• Security-Focused Agents: Network scanning and security tool integration (basic_agent_and_tools_scanner.py)
• Advanced Agent Architectures:
  • Chat agents with Wikipedia integration (agent_deep_dive/agent_chat.py)
  • Document-aware agents with storage capabilities (agent_deep_dive/agent_docstore.py)
• LangGraph Workflows: Complex decision workflows with state management (langgraph/)
  • Conditional branching logic and multi-step processes
  • CISA KEV agent and ethical hacking automation
• Agentic RAG: Reasoning-based real-time data retrieval with SSRF analysis (agentic_rag/)
• Model Context Protocol (MCP): FastAPI-based security servers with port scanning (mcp_servers_examples/)

Note: This will continue to be a living set of resources with updates and new content added regularly.

For any queries or further information, please contact:

Omar Santos

• X: @santosomar
• LinkedIn: /santosomar