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>
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co-authored by
Claude Opus 4.7
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20f1770794
@@ -583,10 +583,12 @@ equivalent.** Operators who need a runtime toggle should open an issue.
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| `VECTOR_SYNC_QUEUE_MAX_SIZE` | ⚠️ Optional | `10000` | Max queued documents |
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| `OLLAMA_BASE_URL` | ⚠️ Optional | - | Ollama API endpoint for embeddings |
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| `OLLAMA_EMBEDDING_MODEL` | ⚠️ Optional | `nomic-embed-text` | Embedding model to use |
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| `OLLAMA_GENERATION_MODEL` | ⚠️ Optional | - | Ollama model for text generation |
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| `OLLAMA_VERIFY_SSL` | ⚠️ Optional | `true` | Verify SSL certificates |
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| `OPENAI_API_KEY` | ⚠️ Optional | - | OpenAI API key (selects OpenAI provider) |
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| `OPENAI_BASE_URL` | ⚠️ Optional | - | OpenAI base URL override (for compatible APIs) |
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| `OPENAI_EMBEDDING_MODEL` | ⚠️ Optional | `text-embedding-3-small` | OpenAI embedding model |
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| `OPENAI_GENERATION_MODEL` | ⚠️ Optional | - | OpenAI model for text generation |
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| `MISTRAL_API_KEY` | ⚠️ Optional | - | Mistral API key (selects Mistral provider) |
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| `MISTRAL_EMBEDDING_MODEL` | ⚠️ Optional | `mistral-embed` | Mistral embedding model (1024-dim) |
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| `MISTRAL_BASE_URL` | ⚠️ Optional | - | Mistral base URL override (proxies, on-prem) |
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@@ -69,7 +69,8 @@ def retry_on_rate_limit(
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logger.error(
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"%s rate limit exceeded after %d attempts", provider_name, MAX_RETRIES
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)
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assert last_error is not None # The loop above always assigns it.
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if last_error is None: # pragma: no cover — loop above always sets this
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raise RuntimeError("retry loop exited without capturing an error")
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raise last_error
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return wrapper
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@@ -6,6 +6,10 @@ can be added later if needed; see ADR-015.
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import logging
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# mistralai 2.x ships no top-level __init__.py, so `from mistralai import …`
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# raises ImportError. The canonical public paths are `mistralai.client` (which
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# re-exports the SDK class via `client/__init__.py`) and `mistralai.client.errors`
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# (which lazy-loads SDKError). There is no `mistralai.models` subpackage either.
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from mistralai.client import Mistral
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from mistralai.client.errors import SDKError
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@@ -10,14 +10,14 @@ import logging
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from openai import AsyncOpenAI, RateLimitError
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from ._retry import retry_on_rate_limit as _retry_factory
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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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# OpenAI's RateLimitError is itself a 429-specific class, so the default
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# is_rate_limit predicate ("always True") matches the previous behavior.
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retry_on_rate_limit = _retry_factory(RateLimitError, provider_name="OpenAI")
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_retry_429 = retry_on_rate_limit(RateLimitError, provider_name="OpenAI")
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# Well-known embedding dimensions for OpenAI models
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@@ -92,7 +92,7 @@ class OpenAIProvider(Provider):
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"""Whether this provider supports text generation."""
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return self.generation_model is not None
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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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"""
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Generate embedding vector for text.
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@@ -173,7 +173,7 @@ class OpenAIProvider(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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"""Make a single batch embedding request with retry logic."""
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assert self.embedding_model is not None # Type narrowing
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@@ -208,7 +208,7 @@ class OpenAIProvider(Provider):
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)
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return self._dimension
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@retry_on_rate_limit
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@_retry_429
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async def generate(self, prompt: str, max_tokens: int = 500) -> str:
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"""
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Generate text from a prompt.
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@@ -3,11 +3,13 @@
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from mistralai.client.errors import SDKError
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from nextcloud_mcp_server.providers.mistral import (
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BATCH_SIZE,
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MISTRAL_EMBEDDING_DIMENSIONS,
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MistralProvider,
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_is_rate_limit,
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)
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@@ -196,3 +198,17 @@ async def test_mistral_base_url_passed_to_sdk(mocker):
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api_key="test-key",
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server_url="https://example.com/mistral",
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)
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@pytest.mark.unit
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def test_mistral_is_rate_limit_predicate():
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"""_is_rate_limit returns True only for SDKErrors with status_code == 429."""
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err_429 = MagicMock(spec=SDKError)
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err_429.status_code = 429
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err_500 = MagicMock(spec=SDKError)
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err_500.status_code = 500
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assert _is_rate_limit(err_429) is True
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assert _is_rate_limit(err_500) is False
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# ValueError has no status_code attr → getattr returns None → False.
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assert _is_rate_limit(ValueError()) is False
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@@ -69,8 +69,11 @@ def test_registry_picks_simple_with_custom_dimension(clean_provider_env):
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@pytest.mark.unit
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def test_registry_picks_mistral_when_api_key_set(clean_provider_env):
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def test_registry_picks_mistral_when_api_key_set(clean_provider_env, mocker):
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"""MISTRAL_API_KEY alone is enough to select MistralProvider."""
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# MistralProvider eagerly constructs the SDK client in __init__; stub it
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# so the test doesn't depend on the SDK accepting arbitrary keys.
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mocker.patch("nextcloud_mcp_server.providers.mistral.Mistral")
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clean_provider_env.setenv("MISTRAL_API_KEY", "test-key")
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_reload_config()
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