Protocols & Duck Typing (typing.Protocol)

Using typing.Protocol to define compile-time verified interfaces without requiring explicit inheritance. Allows swapping vector databases, embedding providers, and LLM backends via structural subtyping.

Interactive Systems Visualizer

Pydantic v2 Core Rust Validation & Error Recovery

Raw LLM Output String:

{
  "query": "vector index latency",
  "confidence": 0.94,
  "is_urgent": true
}

Pydantic Core Parser Result:

STATUS: VALID

Parsed successfully by pydantic-core in 0.08ms

Key Systems Engineering Principles

Structural subtyping: any class implementing required methods automatically satisfies the Protocol.
Eliminates tight coupling and multi-inheritance dependency hell in large AI codebases.
Enables mocking LLM providers in automated test suites with 100% type fidelity.

Mental Model Analogy

“A Protocol is a job description: if a candidate has a valid passport and knows Python, they qualify for the job, regardless of what school they graduated from.”

Production Pitfall to Avoid

Forcing classes to inherit from monolithic ABCs (Abstract Base Classes), causing brittle diamond inheritance hierarchies.

production_pattern.py

from typing import Protocol, runtime_checkable

@runtime_checkable
class LLMProvider(Protocol):
    async def generate(self, prompt: str, temperature: float = 0.7) -> str: ...

# Any class matching the signature satisfies the Protocol automatically:
class MockLocalLLM:
    async def generate(self, prompt: str, temperature: float = 0.7) -> str:
        return "Deterministic test response"

def execute_pipeline(model: LLMProvider):
    assert isinstance(model, LLMProvider) # Verified!

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