Etape 1 OK, sans optionnel

backend/app/schemas/api.py

@@ -1,14 +1,27 @@
 from pydantic import BaseModel
-from typing import Optional, Any
+from typing import Optional, Any, List, Dict
 
 
 class WorkflowRequest(BaseModel):
     user_input: str
-
+    user_feedback: Optional[str] = None
+    chat_history: Optional[List[Dict[str, str]]] = []
+    spec: Optional[dict] = {}
+    status: Optional[str] = "start"
+    loop_count: Optional[int] = 0
+    existing_project: Optional[Any] = None
+    generated_code: Optional[Any] = None
+    qa_result: Optional[Any] = None
+    is_completed: Optional[bool] = False
 
 class WorkflowResponse(BaseModel):
+    user_input: str
+    user_feedback: Optional[str] = None
+    chat_history: Optional[List[Dict[str, str]]] = []
+    spec: dict
     status: str
-    spec: Optional[dict] = None
-    existing_project: Optional[dict] = None
+    loop_count: int
+    existing_project: Optional[Any] = None
     generated_code: Optional[Any] = None
-    qa_result: Optional[Any] = None
+    qa_result: Optional[Any] = None
+    is_completed: bool

backend/app/schemas/spec.py

@@ -1,10 +1,55 @@
-from pydantic import BaseModel, Field
-from typing import List, Optional
+#spec.py
+from pydantic import BaseModel, Field, model_validator
+from typing import List, Optional, Literal
 
+class InputOutputConfig(BaseModel):
+    has_inputs: bool = Field(default=False, description="Le script prend-il des éléments en entrée ?")
+    input_type: Optional[Literal["file", "directory", "api", "database", "none"]] = Field(None, description="Type d'entrée principale")
+    input_paths_or_sources: List[str] = Field(default_factory=list, description="Chemins, tables ou endpoints sources")
+    
+    has_outputs: bool = Field(default=False, description="Le script génère-t-style des éléments en sortie ?")
+    output_type: Optional[Literal["file", "directory", "database", "api_response", "log_only"]] = Field(None, description="Type de sortie principale")
+    output_formats: List[str] = Field(default_factory=list, description="Formats attendus (ex: CSV, JSON, XLSX)")
+
+class AuthenticationConfig(BaseModel):
+    requires_auth: bool = Field(default=False, description="Le script nécessite-t-il des accès sécurisés ?")
+    auth_method: Optional[Literal["env_variables", "service_account_json", "oauth2", "api_key", "none"]] = Field(None, description="Méthode d'authentification")
+    target_tools_and_apis: List[str] = Field(default_factory=list, description="Logiciels ou API avec lesquels interagir (ex: Sharepoint, JIRA)")
+
+class EnvironmentConfig(BaseModel):
+    target_os: Literal["linux", "windows", "macos", "cross_platform"] = Field(default="cross_platform", description="Système d'exploitation cible")
+    language_version: str = Field(default="^3.11", description="Contrainte de version du langage")
+    critical_dependencies: List[str] = Field(default_factory=list, description="Librairies tierces indispensables")
 
 class ProjectSpec(BaseModel):
-    title: str = Field(default="Projet ARC")
-    description: str
-    requirements: List[str] = Field(default_factory=list)
-    constraints: List[str] = Field(default_factory=list)
-    target_stack: Optional[str] = "Python"
+    title: Optional[str] = Field(None, description="Nom clair et concis du script")
+    description: Optional[str] = Field(None, description="Description macro de l'objectif du script")
+    requirements: List[str] = Field(default_factory=list, description="Liste des fonctionnalités pas-à-pas attendues")
+    constraints: List[str] = Field(default_factory=list, description="Normes, formats de code et conventions de nommage imposés")
+    language: str = Field(default="Python", description="Langage de programmation principal")
+    target_stack: str = Field(None, description="Stack technique ou framework attendu (ex: Pandas, FastAPI, Flask, Django, etc.)")
+    
+    # Sous-configurations détaillées (permettent la détection des champs manquants)
+    io_config: InputOutputConfig = Field(default_factory=InputOutputConfig)
+    auth_config: AuthenticationConfig = Field(default_factory=AuthenticationConfig)
+    env_config: EnvironmentConfig = Field(default_factory=EnvironmentConfig)
+    
+    error_handling_strategy: Literal["abort_on_error", "log_and_continue", "retry_policy"] = Field(
+        default="log_and_continue", 
+        description="Comportement du script face à une anomalie"
+    )
+    is_complete: bool = Field(default=False, description="Passez à True UNIQUEMENT si vous avez TOUTES les infos pour coder (titre, desc, reqs, io_config, auth_config si besoin).")
+    clarifying_question: Optional[str] = Field(None, description="Si is_complete est False, écrivez ici une question claire et polie pour Chainlit pour demander les détails manquants.")
+
+    @model_validator(mode="after")
+    def validate_conditional_fields(self) -> 'ProjectSpec':
+        """Validation des dépendances logiques pour marquer le cahier des charges comme valide."""
+        # Si les champs majeurs sont remplis, on valide la cohérence interne
+        if self.title and self.description and len(self.requirements) > 0:
+            if self.io_config.has_inputs and not self.io_config.input_type:
+                raise ValueError("input_type manquant alors que has_inputs est True")
+            if self.io_config.has_outputs and not self.io_config.output_type:
+                raise ValueError("output_type manquant alors que has_outputs est True")
+            if self.auth_config.requires_auth and (not self.auth_config.auth_method or self.auth_config.auth_method == "none"):
+                raise ValueError("auth_method manquante alors que requires_auth est True")
+        return self