LangChain-Structured-OutPut (🦜🔗)

1. TypedDict :

is a way to define a dict in python where specific keys and values should exists. It ensures that your dictionary follows a specific structure.

When to use ✅ :

• You're working with dictionaries inside your own Python code
• You want your editor to give you autocomplete hints
• The data is simple and you control where it comes from
• You're working with existing code that uses dictionaries and you want to add type hints without changing everything

2. Pydantic :

Pydantic is a data validation and data parsing library for python. It ensures that the data you work with is correct, structured and type-safe.

When to use ✅ :

• You're receiving data from external sources (APIs, users, LLMs)
• You need validation (age must be positive, email must be valid format, CGPA between zero and ten)
• You need automatic type conversion
• You're building APIs or working with complex data models
• You want clear error messages when data is wrong

Json :

is just raw data , it's like writing information on a piece of paper. There's no enforcement, no validation, just pure data storage and transmission.

When to use ✅ :

• You're just storing or transmitting data between systems
• You're reading from or writing to files
• You're sending data over HTTP APIs
• You don't need any Python-specific features