Initial commit: CI Agent competitive-intelligence monitoring app

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).

apps/api/app/analysis/llm/base.py

@@ -0,0 +1,33 @@
+"""LLM provider interface. Every analysis task (app/prompts/*.py) is written
+against this Protocol, never against a specific vendor SDK - swapping
+`LLM_PROVIDER` changes which class `get_llm_provider()` returns and nothing
+else has to change. `generate_structured` is the primary method: it always
+returns a validated instance of the caller's Pydantic response model, never
+raw text, so a malformed model response can never propagate un-typed data
+into the rest of the app (see `LLMResponseError` / the repair loop in
+anthropic_provider.py).
+"""
+
+from __future__ import annotations
+
+from typing import Protocol
+
+from pydantic import BaseModel
+
+
+class LLMResponseError(Exception):
+    """Raised when a provider can't produce a response matching the
+    requested schema, even after any repair attempts."""
+
+
+class LLMProvider(Protocol):
+    provider_name: str
+
+    async def generate_structured[T: BaseModel](
+        self,
+        system_prompt: str,
+        user_prompt: str,
+        response_model: type[T],
+    ) -> T: ...
+
+    async def generate_text(self, system_prompt: str, user_prompt: str) -> str: ...