refactor(providers): address PR #772 review — shared retry, cleaner imports, no-op close
Addresses the Claude Code review on PR #772 plus the SonarCloud S1192 finding: - Extract `retry_on_rate_limit` into `nextcloud_mcp_server/providers/_retry.py` as a parametric decorator. OpenAI and Mistral now share the same backoff loop; future providers can reuse it without copy-paste. - New `tests/unit/providers/test_retry.py` covers the decorator: 429 retry + success, non-429 immediate re-raise, MAX_RETRIES exhaustion, default predicate, and unrelated exception passthrough. - Tighten Mistral SDK import to `from mistralai.client.errors import SDKError` (the canonical sub-path; the reviewer's `from mistralai.models import SDKError` does not exist in mistralai 2.4.5). - Replace `MistralProvider.close()`'s direct `__aexit__` call with a no-op + comment — the Speakeasy-generated client has no public close hook and the underlying httpx client is closed by GC. - Extract the duplicated "Embedding not supported" message to a module-level constant (SonarCloud S1192). - Align `Settings.get_embedding_model_name()` Bedrock check with the registry by also considering `bedrock_generation_model`. - Add the `mock_mistral_client` fixture to `test_mistral_no_embeddings_disabled` for parity with the rest of the file. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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co-authored by
Claude Opus 4.7
parent
cf59663d9e
commit
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@@ -5,55 +5,15 @@ can be added later if needed; see ADR-015.
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"""
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import logging
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from functools import wraps
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import anyio
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from mistralai.client import Mistral
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from mistralai.client.errors.sdkerror import SDKError
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from mistralai.client.errors import SDKError
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from ._retry import retry_on_rate_limit
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from .base import Provider
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logger = logging.getLogger(__name__)
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MAX_RETRIES = 5
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INITIAL_RETRY_DELAY = 2.0
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MAX_RETRY_DELAY = 60.0
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def retry_on_rate_limit(func):
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"""Retry on Mistral 429 (rate limit) responses with exponential backoff."""
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@wraps(func)
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async def wrapper(*args, **kwargs):
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retry_delay = INITIAL_RETRY_DELAY
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last_error: Exception | None = None
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for attempt in range(1, MAX_RETRIES + 1):
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try:
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return await func(*args, **kwargs)
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except SDKError as e:
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# SDKError carries a status_code attribute populated from the
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# raw response. Only 429 is retryable here.
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status = getattr(e, "status_code", None)
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if status != 429:
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raise
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last_error = e
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if attempt < MAX_RETRIES:
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logger.warning(
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"Mistral rate limit hit (attempt %d/%d), retrying in %.1fs...",
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attempt,
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MAX_RETRIES,
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retry_delay,
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)
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await anyio.sleep(retry_delay)
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retry_delay = min(retry_delay * 2, MAX_RETRY_DELAY)
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logger.error("Mistral rate limit exceeded after %d attempts", MAX_RETRIES)
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raise last_error # type: ignore[misc]
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return wrapper
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# Well-known Mistral embedding model dimensions
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MISTRAL_EMBEDDING_DIMENSIONS: dict[str, int] = {
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"mistral-embed": 1024,
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@@ -63,6 +23,18 @@ MISTRAL_EMBEDDING_DIMENSIONS: dict[str, int] = {
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# but we keep this in line with sibling providers (OpenAI=100, Ollama=32).
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BATCH_SIZE = 64
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_NO_EMBEDDING_MODEL_MSG = "Embedding not supported - no embedding_model configured"
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def _is_rate_limit(exc: BaseException) -> bool:
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"""True only for HTTP 429 SDKErrors."""
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return getattr(exc, "status_code", None) == 429
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_retry_429 = retry_on_rate_limit(
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SDKError, is_rate_limit=_is_rate_limit, provider_name="Mistral"
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)
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class MistralProvider(Provider):
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"""
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@@ -114,13 +86,11 @@ class MistralProvider(Provider):
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def supports_generation(self) -> bool:
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return False
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@retry_on_rate_limit
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@_retry_429
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async def embed(self, text: str) -> list[float]:
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"""Generate an embedding for a single text."""
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if not self.supports_embeddings:
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raise NotImplementedError(
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"Embedding not supported - no embedding_model configured"
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)
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raise NotImplementedError(_NO_EMBEDDING_MODEL_MSG)
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assert self.embedding_model is not None
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response = await self.client.embeddings.create_async(
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@@ -149,9 +119,7 @@ class MistralProvider(Provider):
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async def embed_batch(self, texts: list[str]) -> list[list[float]]:
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"""Generate embeddings for multiple texts, chunking by ``BATCH_SIZE``."""
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if not self.supports_embeddings:
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raise NotImplementedError(
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"Embedding not supported - no embedding_model configured"
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)
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raise NotImplementedError(_NO_EMBEDDING_MODEL_MSG)
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if not texts:
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return []
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@@ -172,7 +140,7 @@ class MistralProvider(Provider):
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return all_embeddings
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@retry_on_rate_limit
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@_retry_429
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async def _embed_batch_request(self, batch: list[str]) -> list[list[float]]:
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"""Single batch request with rate-limit retry."""
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assert self.embedding_model is not None
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@@ -202,9 +170,7 @@ class MistralProvider(Provider):
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def get_dimension(self) -> int:
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if not self.supports_embeddings:
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raise NotImplementedError(
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"Embedding not supported - no embedding_model configured"
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)
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raise NotImplementedError(_NO_EMBEDDING_MODEL_MSG)
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if self._dimension is None:
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raise RuntimeError(
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@@ -221,11 +187,9 @@ class MistralProvider(Provider):
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)
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async def close(self) -> None:
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# The Mistral SDK manages its own httpx client lifecycle; close it
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# via the SDK's context-manager hook if present, otherwise no-op.
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close = getattr(self.client, "__aexit__", None)
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if close is not None:
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try:
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await close(None, None, None)
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except Exception: # pragma: no cover - best-effort cleanup
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logger.debug("Mistral client close raised; ignoring", exc_info=True)
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# The mistralai 2.x client (Speakeasy-generated) does not expose a
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# public close()/aclose() — only the async-context-manager protocol
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# (__aenter__/__aexit__). Calling __aexit__ directly is internal API
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# and brittle across SDK patch versions; the underlying httpx client
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# is closed during garbage collection, so we leave this as a no-op.
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return None
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