Welcome to Tutorial 2. We go deeper into LangChain's model abstraction — prompt templates, LCEL chains, output parsers, and best practices for prompting.

1. Connecting to Groq models via ChatGroq
2. PromptTemplate and ChatPromptTemplate — dynamic prompt construction
3. LCEL chains: prompt | llm | OutputParser
4. Output parsers: StrOutputParser, CommaSeparatedListOutputParser
5. Prompt engineering best practices

• Completion of Tutorial 1
• Virtual environment active with dependencies installed
• Groq API key in .env — see Tutorial 1 for setup

cd Tutorial02
jupyter notebook Tutorial_2_Working_with_Language_Models.ipynb