saksham
1a4c80958f
FastAPI + Celery + Next.js + Postgres/Redis app with company monitoring, source collection, LLM-based change analysis, enrichment, and account security (Turnstile, escalating lockout, email verification).
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
"""LLM provider interface. Every analysis task (app/prompts/*.py) is written
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against this Protocol, never against a specific vendor SDK - swapping
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`LLM_PROVIDER` changes which class `get_llm_provider()` returns and nothing
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else has to change. `generate_structured` is the primary method: it always
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returns a validated instance of the caller's Pydantic response model, never
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raw text, so a malformed model response can never propagate un-typed data
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into the rest of the app (see `LLMResponseError` / the repair loop in
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anthropic_provider.py).
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"""
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from __future__ import annotations
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from typing import Protocol
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from pydantic import BaseModel
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class LLMResponseError(Exception):
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"""Raised when a provider can't produce a response matching the
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requested schema, even after any repair attempts."""
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class LLMProvider(Protocol):
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provider_name: str
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async def generate_structured[T: BaseModel](
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self,
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system_prompt: str,
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user_prompt: str,
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response_model: type[T],
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) -> T: ...
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async def generate_text(self, system_prompt: str, user_prompt: str) -> str: ...
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