langchain-core-workflow-a

# LangChain Core Workflow A: Chains & Prompts ## Overview Build production-ready chains using LangChain Expression Language (LCEL) with prompt templates, output parsers, and composition patterns. ## Prerequisites - Completed `langchain-install-auth` setup - Understanding of prompt engineering basics - Familiarity with Python type hints ## Instructions ### Step 1: Create Prompt Templates ```python from langchain_core.prompts import ( ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder ) # Simple template simple_prompt = ChatPromptTemplate.from_template( "Translate '{text}' to {language}" ) # Chat-style template chat_prompt = ChatPromptTemplate.from_messages([ SystemMessagePromptTemplate.from_template( "You are a {role}. Respond in {style} style." ), MessagesPlaceholder(variable_name="history", optional=True), HumanMessagePromptTemplate.from_template("{input}") ]) ``` ### Step 2: Build LCEL Chains ```python from langchain_openai import ChatOpenAI from langchain_core.output_parsers import StrOutputParser, JsonOutputParser llm = ChatOpenAI(model="gpt-4o-mini") # Basic chain: prompt -> llm -> parser basic_chain = simple_prompt | llm | StrOutputParser() # Invoke the chain result = basic_chain.invoke({ "text": "Hello, world!", "language": "Spanish" }) print(result) # "Hola, mundo!" ``` ### Step 3: Chain Composition ```python from langchain_core.runnables import RunnablePassth...