feat: Enhance ToolCallRequest and ToolCallResponse models with detailed examples and descriptions for improved clarity and usability in MCP tool calls.

models/mcp_models.py

@@ -3,15 +3,43 @@ from typing import Any, Dict, List, Optional
 
 class ToolCallRequest(BaseModel):
     """Request for calling an MCP tool"""
-    tool_name: str
-    arguments: Dict[str, Any] = {}
+    model_config = ConfigDict(
+        json_schema_extra={
+            "example": {
+                "tool_name": "detect_stance",
+                "arguments": {
+                    "topic": "Climate change is real",
+                    "argument": "Rising global temperatures prove it"
+                }
+            }
+        }
+    )
+    
+    tool_name: str = Field(..., description="Name of the MCP tool to call (e.g., 'detect_stance', 'match_keypoint_argument', 'transcribe_audio', 'generate_speech', 'generate_argument')")
+    arguments: Dict[str, Any] = Field(default_factory=dict, description="Arguments for the tool (varies by tool)")
 
 class ToolCallResponse(BaseModel):
     """Response from MCP tool call"""
-    success: bool
-    result: Optional[Dict[str, Any]] = None
-    error: Optional[str] = None
-    tool_name: str
+    model_config = ConfigDict(
+        json_schema_extra={
+            "example": {
+                "success": True,
+                "result": {
+                    "predicted_stance": "PRO",
+                    "confidence": 0.9598,
+                    "probability_con": 0.0402,
+                    "probability_pro": 0.9598
+                },
+                "error": None,
+                "tool_name": "detect_stance"
+            }
+        }
+    )
+    
+    success: bool = Field(..., description="Whether the tool call was successful")
+    result: Optional[Dict[str, Any]] = Field(None, description="Result from the tool call")
+    error: Optional[str] = Field(None, description="Error message if the call failed")
+    tool_name: str = Field(..., description="Name of the tool that was called")
 
 # Response models for individual MCP tools
 class DetectStanceResponse(BaseModel):

routes/mcp_routes.py

@@ -188,7 +188,66 @@ async def list_mcp_tools():
 
 @router.post("/tools/call", response_model=ToolCallResponse, summary="Appeler un outil MCP")
 async def call_mcp_tool(request: ToolCallRequest):
-    """Appelle un outil MCP par son nom avec des arguments"""
+    """
+    Appelle un outil MCP par son nom avec des arguments
+    
+    **Exemples d'utilisation:**
+    
+    1. **detect_stance** - Détecter la stance d'un argument:
+    ```json
+    {
+      "tool_name": "detect_stance",
+      "arguments": {
+        "topic": "Climate change is real",
+        "argument": "Rising global temperatures prove it"
+      }
+    }
+    ```
+    
+    2. **match_keypoint_argument** - Matcher un argument avec un keypoint:
+    ```json
+    {
+      "tool_name": "match_keypoint_argument",
+      "arguments": {
+        "argument": "Renewable energy reduces emissions",
+        "key_point": "Environmental benefits"
+      }
+    }
+    ```
+    
+    3. **generate_argument** - Générer un argument:
+    ```json
+    {
+      "tool_name": "generate_argument",
+      "arguments": {
+        "topic": "Assisted suicide should be legal",
+        "position": "positive"
+      }
+    }
+    ```
+    
+    4. **transcribe_audio** - Transcrire un audio:
+    ```json
+    {
+      "tool_name": "transcribe_audio",
+      "arguments": {
+        "audio_path": "/path/to/audio.wav"
+      }
+    }
+    ```
+    
+    5. **generate_speech** - Générer de la parole:
+    ```json
+    {
+      "tool_name": "generate_speech",
+      "arguments": {
+        "text": "Hello, this is a test",
+        "voice": "Aaliyah-PlayAI",
+        "format": "wav"
+      }
+    }
+    ```
+    """
     try:
         result = await mcp_server.call_tool(request.tool_name, request.arguments)
         # Gérer différents types de retours MCP