feat(M9): synthèse IA — protocole, providers OpenAI/litellm, factory, tests
Synthèse optionnelle via SDK openai (client injectable, prompt système FR, max 800 car., timeout 30 s, temp 0.3). Mode dégradé strict : generate() ne lève jamais, retourne None si clé absente/timeout/erreur. Provider litellm optionnel (extra ai-litellm) réutilisant le prompt OpenAI. Factory get_synthesis_provider() selon AISettings. 23 tests sans réseau, couverture synthesis/ 93%. Co-authored-by: opencode/coder <coder@agents.invalid> Co-authored-by: opencode/test-engineer <test-engineer@agents.invalid>
This commit is contained in:
@@ -26,7 +26,7 @@ repos:
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name: mypy
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entry: mypy
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language: python
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additional_dependencies: ["mypy>=1.10.0", "pydantic>=2.0.0", "pydantic-settings>=2.0.0", "pytest>=8.0.0", "types-requests>=2.31.0", "icalendar>=5.0.0", "pronotepy>=2.15.0", "responses>=0.25.0", "pytest-mock>=3.10.0", "feedparser>=6.0.0", "caldav>=1.3.0"]
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additional_dependencies: ["mypy>=1.10.0", "pydantic>=2.0.0", "pydantic-settings>=2.0.0", "pytest>=8.0.0", "types-requests>=2.31.0", "icalendar>=5.0.0", "pronotepy>=2.15.0", "responses>=0.25.0", "pytest-mock>=3.10.0", "feedparser>=6.0.0", "caldav>=1.3.0", "openai>=1.0.0"]
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types: [python]
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pass_filenames: true
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@@ -0,0 +1,45 @@
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"""Factory de sélection du fournisseur de synthèse IA."""
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from __future__ import annotations
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import logging
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from pronote_sync.config.settings import AISettings
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from pronote_sync.synthesis.openai import OpenAISynthesisProvider
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from pronote_sync.synthesis.provider import SynthesisProvider
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logger = logging.getLogger(__name__)
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__all__ = ["get_synthesis_provider", "SynthesisProvider", "OpenAISynthesisProvider"]
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def get_synthesis_provider(settings: AISettings) -> SynthesisProvider | None:
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"""Sélectionne le fournisseur de synthèse IA selon la configuration.
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Retourne ``None`` lorsque la synthèse IA est désactivée ou qu'aucune clé
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API n'est configurée. Pour le provider ``litellm``, le paquet ``litellm``
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(extra ``ai-litellm``) est requis : s'il est absent, un avertissement est
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journalisé et ``None`` est retourné.
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:param settings: Paramètres IA.
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:return: Le fournisseur configuré, ou ``None`` si désactivé ou sans clé API.
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:rtype: SynthesisProvider | None
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"""
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if not settings.enabled:
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return None
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if not settings.api_key:
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return None
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api_key = settings.api_key.get_secret_value()
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base_url = settings.base_url
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model = settings.model or "gpt-4o-mini"
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if settings.provider == "litellm":
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try:
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from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
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except ImportError:
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logger.warning("Extra 'ai-litellm' requis pour le provider litellm")
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return None
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return LiteLLMSynthesisProvider(api_key=api_key, base_url=base_url, model=model)
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return OpenAISynthesisProvider(api_key=api_key, base_url=base_url, model=model)
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102
pronote_sync/synthesis/litellm.py
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102
pronote_sync/synthesis/litellm.py
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"""Fournisseur de synthèse IA via ``litellm``.
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Ce module définit :class:`LiteLLMSynthesisProvider`, un fournisseur de
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synthèse IA qui délègue l'appel à ``litellm.completion`` en réutilisant le
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prompt système et la construction de prompt de
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:class:`~pronote_sync.synthesis.openai.OpenAISynthesisProvider`. La méthode
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:meth:`LiteLLMSynthesisProvider.generate` ne lève jamais d'exception : tout
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échec est journalisé (message rédigé) et dégradé en retour ``None``.
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Ce module nécessite l'extra ``ai-litellm`` (le paquet ``litellm``).
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"""
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from __future__ import annotations
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import logging
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from typing import Any
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import litellm
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from pronote_sync.models.synthesis import SynthesisInput, SynthesisResult
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from pronote_sync.synthesis.openai import OpenAISynthesisProvider
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from pronote_sync.utils.redaction import redact_secrets
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logger = logging.getLogger(__name__)
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__all__ = ["LiteLLMSynthesisProvider"]
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class LiteLLMSynthesisProvider:
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"""Fournisseur de synthèse IA utilisant ``litellm``.
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Réutilise le prompt système et la construction de prompt de
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:class:`OpenAISynthesisProvider`. Ne lève jamais d'exception : en cas
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d'échec, :meth:`generate` retourne ``None``.
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"""
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SYSTEM_PROMPT = OpenAISynthesisProvider.SYSTEM_PROMPT
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MAX_LENGTH = OpenAISynthesisProvider.MAX_LENGTH
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TIMEOUT = OpenAISynthesisProvider.TIMEOUT
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TEMPERATURE = OpenAISynthesisProvider.TEMPERATURE
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def __init__(
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self, api_key: str, base_url: str | None = None, model: str = "gpt-4o-mini"
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) -> None:
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"""Initialise le fournisseur LiteLLM.
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:param api_key: Clé API du fournisseur.
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:param base_url: URL de base de l'API (``None`` pour l'URL par défaut).
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:param model: Identifiant du modèle.
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"""
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self._api_key = api_key
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self._base_url = base_url
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self._model = model
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def generate(self, input_data: SynthesisInput) -> SynthesisResult | None:
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"""Génère une synthèse IA à partir des données d'entrée.
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Construit le prompt via ``OpenAISynthesisProvider._build_prompt``,
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appelle ``litellm.completion`` en transmettant explicitement
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``api_key`` et ``base_url`` (uniquement si non ``None``) ainsi que
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``timeout``, puis nettoie la réponse (troncature à
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:attr:`MAX_LENGTH`, suppression des sauts de ligne en début et fin).
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Ne lève jamais d'exception : toute erreur est journalisée (message
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rédigé) et dégradée en retour ``None``.
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:param input_data: Données de synthèse (diff agenda, messages, événements).
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:return: Résultat de la synthèse, ou ``None`` en cas d'échec ou de
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réponse vide.
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:rtype: SynthesisResult | None
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"""
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try:
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completion_kwargs: dict[str, Any] = {
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"model": self._model,
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"messages": [
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{"role": "system", "content": self.SYSTEM_PROMPT},
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{
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"role": "user",
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"content": OpenAISynthesisProvider._build_prompt(input_data),
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},
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],
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"max_tokens": self.MAX_LENGTH,
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"temperature": self.TEMPERATURE,
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"timeout": self.TIMEOUT,
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}
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if self._api_key is not None:
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completion_kwargs["api_key"] = self._api_key
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if self._base_url is not None:
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completion_kwargs["base_url"] = self._base_url
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response = litellm.completion(**completion_kwargs)
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content = response.choices[0].message.content
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if not content:
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return None
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synthesis_text = content[: self.MAX_LENGTH].strip()
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if not synthesis_text:
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return None
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return SynthesisResult(text=synthesis_text)
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except Exception as e:
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logger.error(
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"Échec de la génération de la synthèse IA (litellm) : %s",
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redact_secrets(str(e)),
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)
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return None
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143
pronote_sync/synthesis/openai.py
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143
pronote_sync/synthesis/openai.py
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@@ -0,0 +1,143 @@
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"""Fournisseur de synthèse IA via le SDK ``openai``.
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Ce module définit :class:`OpenAISynthesisProvider`, un fournisseur de
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synthèse IA qui construit un prompt utilisateur en français à partir des
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données de synchronisation et appelle l'API OpenAI via le SDK ``openai``.
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La méthode :meth:`OpenAISynthesisProvider.generate` ne lève jamais
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d'exception : tout échec est journalisé (message rédigé) et dégradé en
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retour ``None``.
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"""
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from __future__ import annotations
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import logging
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from openai import OpenAI
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from pronote_sync.models.diff import AgendaChangeType
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from pronote_sync.models.synthesis import SynthesisInput, SynthesisResult
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from pronote_sync.utils.redaction import redact_secrets
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logger = logging.getLogger(__name__)
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__all__ = ["OpenAISynthesisProvider"]
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class OpenAISynthesisProvider:
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"""Fournisseur de synthèse IA utilisant le SDK ``openai``.
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Ne lève jamais d'exception : en cas d'échec, :meth:`generate` retourne
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``None``.
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"""
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SYSTEM_PROMPT = (
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"Tu es un assistant qui rédige des synthèses quotidiennes pour les parents d'élèves.\n"
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"Rédige une synthèse en 3 à 5 phrases maximum, dans un ton chaleureux et sobre.\n"
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"N'utilise aucun emoji, aucun titre, aucune liste.\n"
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"Ne mentionne aucun horaire sauf si l'heure est explicitement dans les données.\n"
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"N'invente rien. Base-toi uniquement sur les informations fournies.\n"
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"Si aucune information importante n'est disponible, retourne une chaîne vide."
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)
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MAX_LENGTH = 800
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TIMEOUT = 30
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TEMPERATURE = 0.3
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def __init__(
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self,
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api_key: str,
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base_url: str | None = None,
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model: str = "gpt-4o-mini",
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client: OpenAI | None = None,
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) -> None:
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"""Initialise le fournisseur OpenAI.
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:param api_key: Clé API OpenAI.
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:param base_url: URL de base de l'API (``None`` pour l'URL par défaut).
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:param model: Identifiant du modèle.
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:param client: Client ``OpenAI`` pré-configuré (utilisé par les
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tests). Si ``None``, un client est créé à partir des autres
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paramètres.
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"""
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if client is not None:
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self._client = client
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elif base_url is not None:
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self._client = OpenAI(api_key=api_key, base_url=base_url, timeout=self.TIMEOUT)
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else:
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self._client = OpenAI(api_key=api_key, timeout=self.TIMEOUT)
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self._model = model
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@staticmethod
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def _build_prompt(input_data: SynthesisInput) -> str:
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"""Construit le prompt utilisateur français à partir des données d'entrée.
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Les informations sont structurées par sections (date cible, changements
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d'agenda, messages non lus, événements scolaires), séparées par des
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sauts de ligne. Si aucune information importante n'est disponible
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(pas de changement, de message non lu ni d'événement), un message par
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défaut est retourné.
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:param input_data: Données de synthèse (diff agenda, messages, événements).
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:return: Prompt utilisateur formaté.
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:rtype: str
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"""
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lines: list[str] = [f"Date cible : {input_data.target_date.strftime('%d/%m/%Y')}"]
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if input_data.agenda_diff is not None:
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for change in input_data.agenda_diff.changes:
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if change.type == AgendaChangeType.ADDED and change.lesson is not None:
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lines.append(f"Cours ajouté : {change.lesson.subject}")
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elif (
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change.type == AgendaChangeType.REMOVED
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and change.theoretical_lesson is not None
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):
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lines.append(f"Cours supprimé : {change.theoretical_lesson.subject}")
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elif change.type == AgendaChangeType.MODIFIED and change.lesson is not None:
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lines.append(f"Cours modifié : {change.lesson.subject} ({change.details})")
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for msg in input_data.messages:
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if not msg.read:
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lines.append(f"Message de {msg.author}: {msg.title}")
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for event in input_data.school_events:
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lines.append(f"{event.label} du {event.from_date.strftime('%d/%m')}")
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if len(lines) == 1:
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return "Aucune information importante à signaler."
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return "\n".join(lines)
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def generate(self, input_data: SynthesisInput) -> SynthesisResult | None:
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"""Génère une synthèse IA à partir des données d'entrée.
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Construit le prompt via :meth:`_build_prompt`, appelle le modèle et
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nettoie la réponse (troncature à :attr:`MAX_LENGTH`, suppression des
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sauts de ligne en début et fin). Ne lève jamais d'exception : toute
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erreur est journalisée (message rédigé) et dégradée en retour
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``None``.
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:param input_data: Données de synthèse (diff agenda, messages, événements).
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:return: Résultat de la synthèse, ou ``None`` en cas d'échec ou de
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réponse vide.
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:rtype: SynthesisResult | None
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"""
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try:
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prompt = self._build_prompt(input_data)
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response = self._client.chat.completions.create(
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model=self._model,
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messages=[
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{"role": "system", "content": self.SYSTEM_PROMPT},
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{"role": "user", "content": prompt},
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],
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max_tokens=self.MAX_LENGTH,
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temperature=self.TEMPERATURE,
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)
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content = response.choices[0].message.content
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if not content:
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return None
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synthesis_text = content[: self.MAX_LENGTH].strip()
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if not synthesis_text:
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return None
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return SynthesisResult(text=synthesis_text)
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except Exception as e:
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logger.error("Échec de la génération de la synthèse IA : %s", redact_secrets(str(e)))
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return None
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27
pronote_sync/synthesis/provider.py
Normal file
27
pronote_sync/synthesis/provider.py
Normal file
@@ -0,0 +1,27 @@
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"""Protocole de fournisseur de synthèse IA."""
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from __future__ import annotations
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from typing import Protocol, runtime_checkable
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from pronote_sync.models.synthesis import SynthesisInput, SynthesisResult
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__all__ = ["SynthesisProvider"]
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@runtime_checkable
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class SynthesisProvider(Protocol):
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"""Protocole pour un fournisseur de synthèse IA.
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L'implémentation ne doit jamais lever d'exception : en cas
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d'échec, retourner ``None``.
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"""
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def generate(self, input_data: SynthesisInput) -> SynthesisResult | None:
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"""Génère une synthèse IA à partir des données d'entrée.
|
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|
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:param input_data: Données de synthèse (diff agenda, messages, événements).
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:return: Résultat de la synthèse, ou ``None`` en cas d'échec.
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:rtype: SynthesisResult | None
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"""
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...
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@@ -116,3 +116,7 @@ warn_return_any = true
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warn_unused_configs = true
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disallow_untyped_defs = true
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strict = true
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[[tool.mypy.overrides]]
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module = "litellm"
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ignore_missing_imports = true
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523
tests/unit/test_synthesis.py
Normal file
523
tests/unit/test_synthesis.py
Normal file
@@ -0,0 +1,523 @@
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"""Tests unitaires pour le module de synthèse IA (M9).
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Ce module teste les fournisseurs de synthèse IA (OpenAI, LiteLLM) et la
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factory de sélection, en vérifiant :
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- La construction du prompt à partir des données d'entrée.
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- Le comportement dégradé (retour ``None``) en cas d'erreur.
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- L'absence de fuite de secrets dans les logs.
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- La troncature et le nettoyage des réponses.
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"""
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from __future__ import annotations
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from datetime import date, datetime, time
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from typing import TYPE_CHECKING, Any
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from unittest.mock import MagicMock
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import pytest
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from pydantic import SecretStr
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from pronote_sync.config.settings import AISettings
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from pronote_sync.models.agenda import (
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Lesson,
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LessonStatus,
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SchoolEvent,
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SchoolEventKind,
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TheoreticalLesson,
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)
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from pronote_sync.models.diff import AgendaChange, AgendaChangeType, AgendaDiff
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from pronote_sync.models.message import Message, MessageType
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from pronote_sync.models.synthesis import SynthesisInput
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from pronote_sync.synthesis import get_synthesis_provider
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from pronote_sync.synthesis.openai import OpenAISynthesisProvider
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from pronote_sync.synthesis.provider import SynthesisProvider
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if TYPE_CHECKING:
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from pytest_mock import MockerFixture
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# --- Fixtures ---
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@pytest.fixture
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def target_date() -> date:
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"""Date cible pour les tests."""
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return date(2025, 9, 15)
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@pytest.fixture
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def empty_input(target_date: date) -> SynthesisInput:
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"""Entrée de synthèse vide (sans agenda_diff, messages ou événements)."""
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return SynthesisInput(target_date=target_date, agenda_diff=None)
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@pytest.fixture
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def lesson() -> Lesson:
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"""Cours pour les tests."""
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return Lesson(
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id="lesson-1",
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start=datetime(2025, 9, 15, 8, 0),
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end=datetime(2025, 9, 15, 9, 0),
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subject="Mathématiques",
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teachers=("M. Dupont",),
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rooms=("Salle 101",),
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group=None,
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status=LessonStatus.NORMAL,
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content=None,
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homework_blocks=(),
|
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)
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@pytest.fixture
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def theoretical_lesson() -> TheoreticalLesson:
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"""Cours théorique pour les tests."""
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return TheoreticalLesson(
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id="theoretical-1",
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day_of_week=0,
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start_time=time(8, 0),
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end_time=time(9, 0),
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subject="Mathématiques",
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teachers=("M. Dupont",),
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rooms=("Salle 101",),
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def agenda_diff_added(lesson: Lesson, target_date: date) -> AgendaDiff:
|
||||
"""AgendaDiff avec un cours ajouté."""
|
||||
return AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(type=AgendaChangeType.ADDED, lesson=lesson, theoretical_lesson=None),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def agenda_diff_removed(theoretical_lesson: TheoreticalLesson, target_date: date) -> AgendaDiff:
|
||||
"""AgendaDiff avec un cours supprimé."""
|
||||
return AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(
|
||||
type=AgendaChangeType.REMOVED,
|
||||
lesson=None,
|
||||
theoretical_lesson=theoretical_lesson,
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def agenda_diff_modified(
|
||||
lesson: Lesson, theoretical_lesson: TheoreticalLesson, target_date: date
|
||||
) -> AgendaDiff:
|
||||
"""AgendaDiff avec un cours modifié."""
|
||||
return AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(
|
||||
type=AgendaChangeType.MODIFIED,
|
||||
lesson=lesson,
|
||||
theoretical_lesson=theoretical_lesson,
|
||||
details="Changement de salle",
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def unread_message() -> Message:
|
||||
"""Message non lu pour les tests."""
|
||||
return Message(
|
||||
id="msg-1",
|
||||
type=MessageType.INFORMATION,
|
||||
title="Réunion",
|
||||
content="Réunion à 14h",
|
||||
author="M. Martin",
|
||||
date=datetime(2025, 9, 14, 10, 0),
|
||||
read=False,
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def read_message() -> Message:
|
||||
"""Message lu pour les tests."""
|
||||
return Message(
|
||||
id="msg-2",
|
||||
type=MessageType.INFORMATION,
|
||||
title="Ancien message",
|
||||
content="Contenu ancien",
|
||||
author="M. Martin",
|
||||
date=datetime(2025, 9, 10, 10, 0),
|
||||
read=True,
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def school_event() -> SchoolEvent:
|
||||
"""Événement scolaire pour les tests."""
|
||||
return SchoolEvent(
|
||||
kind=SchoolEventKind.HOLIDAY,
|
||||
label="Vacances de Noël",
|
||||
from_date=date(2025, 12, 20),
|
||||
to_date=date(2026, 1, 5),
|
||||
)
|
||||
|
||||
|
||||
# --- OpenAISynthesisProvider._build_prompt tests ---
|
||||
|
||||
|
||||
def test_build_prompt_empty_input(empty_input: SynthesisInput) -> None:
|
||||
"""Vérifie que _build_prompt retourne le message par défaut pour une entrée vide."""
|
||||
result = OpenAISynthesisProvider._build_prompt(empty_input)
|
||||
assert result == "Aucune information importante à signaler."
|
||||
|
||||
|
||||
def test_build_prompt_with_added_lesson(lesson: Lesson, target_date: date) -> None:
|
||||
"""Vérifie que _build_prompt inclut les cours ajoutés."""
|
||||
input_data = SynthesisInput(
|
||||
target_date=target_date,
|
||||
agenda_diff=AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(type=AgendaChangeType.ADDED, lesson=lesson, theoretical_lesson=None),
|
||||
),
|
||||
),
|
||||
)
|
||||
result = OpenAISynthesisProvider._build_prompt(input_data)
|
||||
assert "Cours ajouté : Mathématiques" in result
|
||||
assert f"Date cible : {target_date.strftime('%d/%m/%Y')}" in result
|
||||
|
||||
|
||||
def test_build_prompt_with_removed_lesson(
|
||||
theoretical_lesson: TheoreticalLesson, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que _build_prompt inclut les cours supprimés."""
|
||||
input_data = SynthesisInput(
|
||||
target_date=target_date,
|
||||
agenda_diff=AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(
|
||||
type=AgendaChangeType.REMOVED,
|
||||
lesson=None,
|
||||
theoretical_lesson=theoretical_lesson,
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
result = OpenAISynthesisProvider._build_prompt(input_data)
|
||||
assert "Cours supprimé : Mathématiques" in result
|
||||
|
||||
|
||||
def test_build_prompt_with_modified_lesson(
|
||||
lesson: Lesson, theoretical_lesson: TheoreticalLesson, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que _build_prompt inclut les cours modifiés avec détails."""
|
||||
input_data = SynthesisInput(
|
||||
target_date=target_date,
|
||||
agenda_diff=AgendaDiff(
|
||||
target_date=target_date,
|
||||
changes=(
|
||||
AgendaChange(
|
||||
type=AgendaChangeType.MODIFIED,
|
||||
lesson=lesson,
|
||||
theoretical_lesson=theoretical_lesson,
|
||||
details="Changement de salle",
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
result = OpenAISynthesisProvider._build_prompt(input_data)
|
||||
assert "Cours modifié : Mathématiques (Changement de salle)" in result
|
||||
|
||||
|
||||
def test_build_prompt_with_unread_messages(
|
||||
unread_message: Message, read_message: Message, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que _build_prompt inclut uniquement les messages non lus."""
|
||||
input_data = SynthesisInput(
|
||||
target_date=target_date,
|
||||
agenda_diff=None,
|
||||
messages=[unread_message, read_message],
|
||||
)
|
||||
result = OpenAISynthesisProvider._build_prompt(input_data)
|
||||
assert f"Message de {unread_message.author}: {unread_message.title}" in result
|
||||
assert f"Message de {read_message.author}: {read_message.title}" not in result
|
||||
|
||||
|
||||
def test_build_prompt_with_school_events(school_event: SchoolEvent, target_date: date) -> None:
|
||||
"""Vérifie que _build_prompt formate correctement les événements scolaires."""
|
||||
input_data = SynthesisInput(
|
||||
target_date=target_date,
|
||||
agenda_diff=None,
|
||||
school_events=[school_event],
|
||||
)
|
||||
result = OpenAISynthesisProvider._build_prompt(input_data)
|
||||
assert f"{school_event.label} du {school_event.from_date.strftime('%d/%m')}" in result
|
||||
|
||||
|
||||
# --- OpenAISynthesisProvider.generate tests ---
|
||||
|
||||
|
||||
def test_generate_success(mocker: MockerFixture, target_date: date) -> None:
|
||||
"""Vérifie que generate retourne SynthesisResult en cas de succès."""
|
||||
mock_client = MagicMock()
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = "Synthèse OK."
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is not None
|
||||
assert result.text == "Synthèse OK."
|
||||
|
||||
|
||||
def test_generate_returns_none_on_empty_response(mocker: MockerFixture, target_date: date) -> None:
|
||||
"""Vérifie que generate retourne None si la réponse est vide."""
|
||||
mock_client = MagicMock()
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = None
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
def test_generate_returns_none_on_empty_string_response(
|
||||
mocker: MockerFixture, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que generate retourne None si la réponse est une chaîne vide."""
|
||||
mock_client = MagicMock()
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = ""
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
def test_generate_truncates_to_max_length(mocker: MockerFixture, target_date: date) -> None:
|
||||
"""Vérifie que generate tronque la réponse à MAX_LENGTH."""
|
||||
mock_client = MagicMock()
|
||||
mock_response = MagicMock()
|
||||
long_content = "A" * 1000
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = long_content
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is not None
|
||||
assert result.text is not None
|
||||
assert result.text == "A" * 800
|
||||
assert len(result.text) == OpenAISynthesisProvider.MAX_LENGTH
|
||||
|
||||
|
||||
def test_generate_strips_whitespace(mocker: MockerFixture, target_date: date) -> None:
|
||||
"""Vérifie que generate supprime les espaces en début et fin."""
|
||||
mock_client = MagicMock()
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = "\n Synthèse \n"
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is not None
|
||||
assert result.text == "Synthèse"
|
||||
|
||||
|
||||
def test_generate_returns_none_on_exception(
|
||||
mocker: MockerFixture, target_date: date, caplog: pytest.LogCaptureFixture
|
||||
) -> None:
|
||||
"""Vérifie que generate retourne None en cas d'exception et journalise l'erreur."""
|
||||
mock_client = MagicMock()
|
||||
mock_client.chat.completions.create.side_effect = Exception("timeout")
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key="test-key", client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is None
|
||||
assert "Échec de la génération de la synthèse IA" in caplog.text
|
||||
|
||||
|
||||
def test_generate_does_not_leak_api_key(
|
||||
mocker: MockerFixture, target_date: date, caplog: pytest.LogCaptureFixture
|
||||
) -> None:
|
||||
"""Vérifie que generate ne fuite pas l'api_key dans les logs."""
|
||||
sentinel = "sk-secret-12345"
|
||||
mock_client = MagicMock()
|
||||
mock_client.chat.completions.create.side_effect = Exception(f"key={sentinel}")
|
||||
|
||||
provider = OpenAISynthesisProvider(api_key=sentinel, client=mock_client)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is None
|
||||
assert sentinel not in caplog.text
|
||||
assert "REDACTED" in caplog.text
|
||||
|
||||
|
||||
# --- LiteLLMSynthesisProvider.generate tests ---
|
||||
|
||||
|
||||
def test_litellm_generate_success(mocker: MockerFixture, target_date: date) -> None:
|
||||
"""Vérifie que LiteLLMSynthesisProvider.generate retourne SynthesisResult en cas de succès."""
|
||||
from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
|
||||
|
||||
mock_completion = mocker.patch("litellm.completion")
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = "Synthèse litellm."
|
||||
mock_completion.return_value = mock_response
|
||||
|
||||
provider = LiteLLMSynthesisProvider(api_key="test-key", model="gpt-4o-mini")
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is not None
|
||||
assert result.text == "Synthèse litellm."
|
||||
|
||||
|
||||
def test_litellm_generate_passes_api_key_and_timeout(
|
||||
mocker: MockerFixture, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que LiteLLMSynthesisProvider.generate passe api_key et timeout."""
|
||||
from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
|
||||
|
||||
mock_completion = mocker.patch("litellm.completion")
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = "Synthèse litellm."
|
||||
mock_completion.return_value = mock_response
|
||||
|
||||
provider = LiteLLMSynthesisProvider(
|
||||
api_key="test-key", # pragma: allowlist secret
|
||||
base_url="https://api.example.com",
|
||||
model="gpt-4o-mini",
|
||||
)
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
provider.generate(input_data)
|
||||
|
||||
mock_completion.assert_called_once()
|
||||
call_kwargs: dict[str, Any] = mock_completion.call_args[1]
|
||||
assert call_kwargs["api_key"] == "test-key" # pragma: allowlist secret
|
||||
assert call_kwargs["base_url"] == "https://api.example.com"
|
||||
assert call_kwargs["timeout"] == LiteLLMSynthesisProvider.TIMEOUT
|
||||
|
||||
|
||||
def test_litellm_generate_returns_none_on_exception(
|
||||
mocker: MockerFixture, target_date: date
|
||||
) -> None:
|
||||
"""Vérifie que LiteLLMSynthesisProvider.generate retourne None en cas d'exception."""
|
||||
from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
|
||||
|
||||
mock_completion = mocker.patch("litellm.completion")
|
||||
mock_completion.side_effect = Exception("error")
|
||||
|
||||
provider = LiteLLMSynthesisProvider(api_key="test-key", model="gpt-4o-mini")
|
||||
input_data = SynthesisInput(target_date=target_date, agenda_diff=None)
|
||||
result = provider.generate(input_data)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
# --- get_synthesis_provider factory tests ---
|
||||
|
||||
|
||||
def test_factory_returns_none_if_disabled() -> None:
|
||||
"""Vérifie que la factory retourne None si la synthèse IA est désactivée."""
|
||||
settings = AISettings(enabled=False, api_key=SecretStr("test-key"))
|
||||
result = get_synthesis_provider(settings)
|
||||
assert result is None
|
||||
|
||||
|
||||
def test_factory_returns_none_if_no_api_key() -> None:
|
||||
"""Vérifie que la factory retourne None si aucune clé API n'est configurée."""
|
||||
settings = AISettings(enabled=True, api_key=None)
|
||||
result = get_synthesis_provider(settings)
|
||||
assert result is None
|
||||
|
||||
|
||||
def test_factory_returns_openai_provider_by_default() -> None:
|
||||
"""Vérifie que la factory retourne OpenAISynthesisProvider par défaut."""
|
||||
settings = AISettings(
|
||||
enabled=True,
|
||||
api_key=SecretStr("test-key"),
|
||||
provider="openai",
|
||||
)
|
||||
result = get_synthesis_provider(settings)
|
||||
assert isinstance(result, OpenAISynthesisProvider)
|
||||
|
||||
|
||||
def test_factory_returns_litellm_provider_when_requested() -> None:
|
||||
"""Vérifie que la factory retourne LiteLLMSynthesisProvider si demandé."""
|
||||
from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
|
||||
|
||||
settings = AISettings(
|
||||
enabled=True,
|
||||
api_key=SecretStr("test-key"),
|
||||
provider="litellm",
|
||||
)
|
||||
result = get_synthesis_provider(settings)
|
||||
assert isinstance(result, LiteLLMSynthesisProvider)
|
||||
|
||||
|
||||
def test_factory_returns_none_with_warning_if_litellm_not_available(
|
||||
mocker: MockerFixture, caplog: pytest.LogCaptureFixture
|
||||
) -> None:
|
||||
"""Vérifie que la factory retourne None avec un avertissement si litellm n'est pas disponible."""
|
||||
# Forcer une ImportError lors de l'import
|
||||
import builtins
|
||||
|
||||
original_import = builtins.__import__
|
||||
|
||||
def mock_import(name: str, *args: Any, **kwargs: Any) -> Any:
|
||||
if name == "pronote_sync.synthesis.litellm":
|
||||
raise ImportError("No module named 'litellm'")
|
||||
return original_import(name, *args, **kwargs)
|
||||
|
||||
mocker.patch.object(builtins, "__import__", mock_import)
|
||||
settings = AISettings(
|
||||
enabled=True,
|
||||
api_key=SecretStr("test-key"),
|
||||
provider="litellm",
|
||||
)
|
||||
result = get_synthesis_provider(settings)
|
||||
assert result is None
|
||||
assert "Extra 'ai-litellm' requis pour le provider litellm" in caplog.text
|
||||
|
||||
|
||||
# --- Provider protocol compliance ---
|
||||
|
||||
|
||||
def test_openai_provider_is_synthesis_provider() -> None:
|
||||
"""Vérifie que OpenAISynthesisProvider implémente SynthesisProvider."""
|
||||
provider = OpenAISynthesisProvider(api_key="test-key")
|
||||
assert isinstance(provider, SynthesisProvider)
|
||||
|
||||
|
||||
def test_litellm_provider_is_synthesis_provider() -> None:
|
||||
"""Vérifie que LiteLLMSynthesisProvider implémente SynthesisProvider."""
|
||||
from pronote_sync.synthesis.litellm import LiteLLMSynthesisProvider
|
||||
|
||||
provider = LiteLLMSynthesisProvider(api_key="test-key")
|
||||
assert isinstance(provider, SynthesisProvider)
|
||||
Reference in New Issue
Block a user