updated

app.py

@@ -1,15 +1,5 @@
 import os
 import gradio as gr
-from fastapi import FastAPI
-from gradio.routes import mount_gradio_app
-
-from starlette.middleware import Middleware
-from starlette.middleware.base import BaseHTTPMiddleware
-from starlette.requests import Request
-from starlette.responses import JSONResponse
-
-# ==== FastMCP ====
-from fastmcp import FastMCP
 
 # Import your existing Gradio app and analysis tools
 from gradio_app import create_gradio_app
@@ -18,34 +8,29 @@ from analysis_tools import AgriculturalAnalyzer
 
 # --------- Config ---------
 PORT = int(os.environ.get("PORT", 7860))
-MCP_BEARER = os.getenv("MCP_BEARER", "")  # ajouter dans Settings > Variables & secrets si besoin
 
 # Initialize agricultural components
 data_loader = AgriculturalDataLoader()
 analyzer = AgriculturalAnalyzer(data_loader)
 
-# --------- Auth middleware (optionnel) ---------
-class BearerAuthMiddleware(BaseHTTPMiddleware):
-    def __init__(self, app, token: str | None):
-        super().__init__(app)
-        self.token = token
-
-    async def dispatch(self, request: Request, call_next):
-        if self.token:
-            auth = request.headers.get("authorization", "")
-            if not auth.startswith("Bearer ") or auth.split(" ", 1)[1] != self.token:
-                return JSONResponse({"detail": "Unauthorized"}, status_code=401)
-        return await call_next(request)
-
-# --------- Déclare le serveur MCP ---------
-mcp = FastMCP("Agricultural Analysis Tools")
-
-# --------- Outils MCP agricoles ---------
-@mcp.tool
-def analyze_weed_pressure(years: list[int] | None = None, plots: list[str] | None = None) -> str:
-    """Analyze weed pressure trends using IFT herbicide data from Kerguéhennec experimental station."""
+# --------- Fonctions MCP pour outils agricoles ---------
+@gr.mcp.tool()
+def analyze_weed_pressure(years: str = "", plots: str = "") -> str:
+    """Analyze weed pressure trends using IFT herbicide data from Kerguéhennec experimental station.
+    
+    Args:
+        years: Comma-separated list of years to analyze (e.g., "2020,2021,2022"). Leave empty for all years.
+        plots: Comma-separated list of plot names to analyze (e.g., "P1,P2,P3"). Leave empty for all plots.
+        
+    Returns:
+        Detailed analysis of weed pressure with IFT statistics and interpretation.
+    """
     try:
-        trends = analyzer.analyze_weed_pressure_trends(years=years, plots=plots)
+        # Parse parameters
+        year_list = [int(y.strip()) for y in years.split(",")] if years.strip() else None
+        plot_list = [p.strip() for p in plots.split(",")] if plots.strip() else None
+        
+        trends = analyzer.analyze_weed_pressure_trends(years=year_list, plots=plot_list)
         summary_stats = trends['summary']
         
         result = f"""🌿 ANALYSE DE LA PRESSION ADVENTICES (IFT Herbicides)
@@ -67,11 +52,19 @@ def analyze_weed_pressure(years: list[int] | None = None, plots: list[str] | Non
     except Exception as e:
         return f"❌ Erreur lors de l'analyse: {str(e)}"
 
-@mcp.tool
-def predict_future_pressure(target_years: list[int] | None = None, max_ift: float = 1.0) -> str:
-    """Predict future weed pressure and identify suitable plots for sensitive crops."""
+@gr.mcp.tool()
+def predict_future_pressure(target_years: str = "2025,2026,2027", max_ift: float = 1.0) -> str:
+    """Predict future weed pressure and identify suitable plots for sensitive crops.
+    
+    Args:
+        target_years: Comma-separated list of years to predict (e.g., "2025,2026,2027")
+        max_ift: Maximum IFT threshold for sensitive crops (default: 1.0)
+        
+    Returns:
+        Predictions for each year with suitable plots for sensitive crops.
+    """
     try:
-        year_list = target_years or [2025, 2026, 2027]
+        year_list = [int(y.strip()) for y in target_years.split(",")]
         predictions = analyzer.predict_weed_pressure(target_years=year_list)
         model_perf = predictions['model_performance']
         
@@ -106,9 +99,13 @@ def predict_future_pressure(target_years: list[int] | None = None, max_ift: floa
     except Exception as e:
         return f"❌ Erreur lors de la prédiction: {str(e)}"
 
-@mcp.tool
+@gr.mcp.tool()
 def analyze_crop_rotation() -> str:
-    """Analyze the impact of crop rotations on weed pressure at Kerguéhennec station."""
+    """Analyze the impact of crop rotations on weed pressure at Kerguéhennec station.
+    
+    Returns:
+        Analysis of the best crop rotations with lowest average IFT herbicide usage.
+    """
     try:
         rotation_impact = analyzer.analyze_crop_rotation_impact()
         
@@ -129,9 +126,13 @@ def analyze_crop_rotation() -> str:
     except Exception as e:
         return f"❌ Erreur lors de l'analyse des rotations: {str(e)}"
 
-@mcp.tool
+@gr.mcp.tool()
 def get_dataset_summary() -> str:
-    """Get a comprehensive summary of the agricultural dataset from Kerguéhennec experimental station."""
+    """Get a comprehensive summary of the agricultural dataset from Kerguéhennec experimental station.
+    
+    Returns:
+        Complete summary with statistics, top crops, top plots and data coverage.
+    """
     try:
         df = data_loader.load_all_files()
         if df.empty:
@@ -157,57 +158,73 @@ def get_dataset_summary() -> str:
     except Exception as e:
         return f"❌ Erreur lors du chargement des données: {str(e)}"
 
-@mcp.resource("agricultural://dataset/summary")
+@gr.mcp.resource("agricultural://dataset/summary")
 def dataset_resource() -> str:
-    """Agricultural dataset summary resource."""
+    """Agricultural dataset summary resource for Kerguéhennec experimental station."""
     return get_dataset_summary()
 
-# Crée l'app ASGI FastMCP et protège-la éventuellement
-mcp_app = mcp.http_app(                   # cf. doc: http_app() retourne une app ASGI montable
-    path="/",                             # endpoint interne de l'app MCP => "/"
-    custom_middleware=[
-        Middleware(BearerAuthMiddleware, token=MCP_BEARER)
-    ] if MCP_BEARER else []
-)
-
-# --------- App FastAPI parente (lifespan important) ---------
-app = FastAPI(title="Agricultural Analysis - Gradio + FastMCP", lifespan=mcp_app.lifespan)
-
-# Health simple
-@app.get("/health")
-def health():
-    return {"ok": True, "service": "agricultural-mcp-server", "version": "1.0.0"}
-
-# Monte MCP sous /mcp/ (final: /mcp/…)
-app.mount("/mcp", mcp_app)
-
-# --------- UI Gradio (utilise ton interface existante) ---------
+@gr.mcp.prompt()
+def agricultural_analysis_prompt(analysis_type: str = "general", focus: str = "sustainability") -> str:
+    """Generate analysis prompts for agricultural data interpretation.
+    
+    Args:
+        analysis_type: Type of analysis (general, weed_pressure, rotation, prediction)
+        focus: Focus area (sustainability, productivity, reduction)
+        
+    Returns:
+        Customized prompt for agricultural analysis.
+    """
+    prompts = {
+        "general": "Analyze the agricultural data to provide insights on farming practices and sustainability",
+        "weed_pressure": "Focus on weed pressure analysis and herbicide usage patterns",
+        "rotation": "Examine crop rotation strategies and their impact on weed management",
+        "prediction": "Predict future agricultural trends and provide recommendations"
+    }
+    
+    focus_additions = {
+        "sustainability": "with emphasis on sustainable and eco-friendly practices",
+        "productivity": "focusing on maximizing crop productivity and yield",
+        "reduction": "prioritizing herbicide reduction and organic alternatives"
+    }
+    
+    base_prompt = prompts.get(analysis_type, prompts["general"])
+    focus_addition = focus_additions.get(focus, focus_additions["sustainability"])
+    
+    return f"{base_prompt} {focus_addition}. Consider IFT values, crop rotations, and environmental impact in your analysis."
+
+# --------- Interface Gradio principale ---------
 demo = create_gradio_app()
 
-# Monte Gradio à la racine
-app = mount_gradio_app(app, demo, path="/")
-
-# --------- Entrée locale facultative ---------
+# --------- Lancement avec serveur MCP intégré ---------
 if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=PORT)
-
-# ========= Tests FastMCP (exemples curl) =========
-# Health
-# curl -s https://hackathoncra-mcp.hf.space/health
-
-# MCP tools list
-# curl -s -X POST https://hackathoncra-mcp.hf.space/mcp/ \
-#   -H "Content-Type: application/json" \
-#   -d '{"jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {}}'
-
-# MCP tool call
-# curl -s -X POST https://hackathoncra-mcp.hf.space/mcp/ \
-#   -H "Content-Type: application/json" \
-#   -d '{"jsonrpc": "2.0", "id": 2, "method": "tools/call", "params": {"name": "get_dataset_summary", "arguments": {}}}'
-
-# MCP avec Bearer (si MCP_BEARER défini)
-# curl -s -X POST https://hackathoncra-mcp.hf.space/mcp/ \
-#   -H "Authorization: Bearer VOTRE_TOKEN" \
-#   -H "Content-Type: application/json" \
-#   -d '{"jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {}}'
+    demo.launch(
+        mcp_server=True,  # Active le serveur MCP intégré
+        server_name="0.0.0.0",
+        server_port=PORT,
+        share=False
+    )
+
+# ========= Configuration MCP pour clients =========
+# L'endpoint MCP sera disponible à : https://hackathoncra-mcp.hf.space/gradio_api/mcp/sse
+# 
+# Configuration pour MCP Inspector ou autres clients:
+# {
+#   "mcpServers": {
+#     "agricultural-analysis": {
+#       "url": "https://hackathoncra-mcp.hf.space/gradio_api/mcp/sse"
+#     }
+#   }
+# }
+#
+# Pour Claude Desktop (avec mcp-remote):
+# {
+#   "mcpServers": {
+#     "agricultural-analysis": {
+#       "command": "npx",
+#       "args": [
+#         "mcp-remote",
+#         "https://hackathoncra-mcp.hf.space/gradio_api/mcp/sse"
+#       ]
+#     }
+#   }
+# }

requirements.txt

@@ -1,7 +1,4 @@
-fastapi>=0.112
-uvicorn[standard]>=0.30
-gradio>=4.43
-fastmcp>=2.3.2
+gradio[mcp]>=4.43
 pandas>=2.0.0
 numpy>=1.24.0
 matplotlib>=3.6.0
@@ -10,5 +7,4 @@ scikit-learn>=1.3.0
 datasets>=2.14.0
 huggingface_hub>=0.17.0
 openpyxl>=3.1.0
-plotly>=5.15.0
-python-multipart>=0.0.6
+plotly>=5.15.0