name = "Amit"
message = 'Hello, World!'

# Single quotes
first = 'Python'

# Double quotes  
second = "Python"

# Triple quotes for multiple lines
paragraph = """This is
a multi-line
string"""

first_name = "Aarav"
last_name = "Sharma"

# Concatenation
full_name = first_name + " " + last_name
print(full_name)  # Aarav Sharma

# Repetition
stars = "*" * 5
print(stars)  # *****

message = "Hello"
print(len(message))  # 5

empty = ""
print(len(empty))    # 0

age = 25
message = "I am " + str(age) + " years old"
print(message)  # I am 25 years old

# Or use f-strings (we'll learn more later)
message = f"I am {age} years old"

text = (
    "Hello "
    "World"
)

print(text)
# Hello World

text = "Hello World"

text = (
    "Hello"
    "World"
)

print(text)
# HelloWorld

text = (
    "Hello "
    "World "
    "Python"
)

Hello World Python

prompt = (
    "Assess the candidate's skillset. "
    "Respond with either 'Match' or 'No Match'. "
    "Application: {application}"
)

template = "Explain {topic} in simple terms."

prompt = template.format(topic="RAG")

print(prompt)

Explain RAG in simple terms.

template = """
You are a {role}.
Explain {topic} for a {audience}.
"""

prompt = template.format(
    role="Python instructor",
    topic="LangChain",
    audience="beginner"
)

print(prompt)

You are a Python instructor.
Explain LangChain for a beginner.

template = """
Answer the question using the following context.

Context:
{context}

Question:
{question}
"""

prompt = template.format(
    context="RAG retrieves relevant documents before generating an answer.",
    question="What is RAG?"
)

print(prompt)

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_template(
    """
    Answer the question using the context below.

    Context:
    {context}

    Question:
    {question}
    """
)

prompt_value = prompt.invoke({
    "context": "RAG combines retrieval with generation.",
    "question": "What is RAG?"
})

Template
   ↓
{context}  → actual context
{question} → actual question
   ↓
Final prompt