refactor(providers): address PR #772 review round 2 — guard, naming, docs, tests

- _retry.py: replace `assert last_error is not None` with explicit
  `if last_error is None: raise RuntimeError(...)` so the original
  rate-limit error is preserved under `python -O`.
- openai.py: drop the `_retry_factory` alias chain; rename the bound
  decorator to `_retry_429` to match the pattern in mistral.py.
- mistral.py: comment the imports so future reviewers understand why
  `from mistralai.client import …` is the canonical path on 2.x (no
  top-level `__init__.py`; no `mistralai.models` subpackage either).
- docs/configuration.md: add `OPENAI_GENERATION_MODEL` and
  `OLLAMA_GENERATION_MODEL` rows to the env-var reference table.
- test_mistral.py: add direct unit test for the `_is_rate_limit`
  predicate (429 → True, 500 → False, missing-attr → False).
- test_registry.py: stub `mistralai.client.Mistral` in the registry
  picker test, mirroring the Ollama sibling, so the test doesn't
  depend on the SDK accepting arbitrary keys.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/providers/openai.py

@@ -10,14 +10,14 @@ import logging
 
 from openai import AsyncOpenAI, RateLimitError
 
-from ._retry import retry_on_rate_limit as _retry_factory
+from ._retry import retry_on_rate_limit
 from .base import Provider
 
 logger = logging.getLogger(__name__)
 
 # OpenAI's RateLimitError is itself a 429-specific class, so the default
 # is_rate_limit predicate ("always True") matches the previous behavior.
-retry_on_rate_limit = _retry_factory(RateLimitError, provider_name="OpenAI")
+_retry_429 = retry_on_rate_limit(RateLimitError, provider_name="OpenAI")
 
 
 # Well-known embedding dimensions for OpenAI models
@@ -92,7 +92,7 @@ class OpenAIProvider(Provider):
         """Whether this provider supports text generation."""
         return self.generation_model is not None
 
-    @retry_on_rate_limit
+    @_retry_429
     async def embed(self, text: str) -> list[float]:
         """
         Generate embedding vector for text.
@@ -173,7 +173,7 @@ class OpenAIProvider(Provider):
 
         return all_embeddings
 
-    @retry_on_rate_limit
+    @_retry_429
     async def _embed_batch_request(self, batch: list[str]) -> list[list[float]]:
         """Make a single batch embedding request with retry logic."""
         assert self.embedding_model is not None  # Type narrowing
@@ -208,7 +208,7 @@ class OpenAIProvider(Provider):
             )
         return self._dimension
 
-    @retry_on_rate_limit
+    @_retry_429
     async def generate(self, prompt: str, max_tokens: int = 500) -> str:
         """
         Generate text from a prompt.