Function Calling — Structured Extraction With Schema

I will implement function calling as a structured extraction mechanism — using the function calling interface to guarantee the LLM returns data in your exact Pydantic or JSON schema without the unreliable output parsing that free-text extraction requires. Using function calling for structured extraction rather than prompting for JSON is significantly more reliable because function calling schemas are enforced at the model level — the model cannot return a malformed structure, whereas JSON-in-text extraction fails whenever the model adds explanation text before or after the JSON, truncates the response, or produces slight schema deviations that break parsing.

The implementation covers Pydantic schema design for your extraction target, function schema translation from Pydantic, extraction function implementation, schema validation, multi-document batch extraction with progress tracking, and extraction accuracy evaluation on your test documents.