add

app.py

@@ -194,14 +194,13 @@ print("hello")
 async def generate_viz(file: UploadFile = File(...), query: str = Form(...)):
     print("hello")
     try:
-        contents = await file.read()  # 👈 Lire tout le contenu du fichier
-        excel_file = io.BytesIO(contents)  # 👈 Le convertir en fichier binaire en mémoire
-        df = pd.read_excel(excel_file)  # 👈 Pandas lit depuis le BytesIO
-        
+        contents = await file.read()  
+        excel_file = io.BytesIO(contents)  
+        df = pd.read_excel(excel_file)  
+
         if query not in VALID_PLOTS:
             return JSONResponse(content={"error": f"Type de graphique invalide. Choisissez parmi : {', '.join(VALID_PLOTS)}"}, status_code=400)
 
-        df = pd.read_excel(file.file)
         numeric_cols = df.select_dtypes(include=["number"]).columns
 
         if len(numeric_cols) < 1:
@@ -231,7 +230,6 @@ plt.close()
         outputs = codegen_model.generate(**inputs, max_new_tokens=120, pad_token_id=codegen_tokenizer.eos_token_id)
         generated_code = codegen_tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
 
-        # Nettoyage
         generated_code = re.sub(r"(import matplotlib.pyplot as plt\nimport seaborn as sns\n)+", "import matplotlib.pyplot as plt\nimport seaborn as sns\n", generated_code)
         if generated_code.strip().endswith("sns."):
             generated_code = generated_code.rsplit("\n", 1)[0]
@@ -252,7 +250,6 @@ plt.close()
         if os.path.getsize(img_path) == 0:
             return JSONResponse(content={"error": "Le fichier plot.png est vide."}, status_code=500)
 
-        # Encoder l'image en base64
         with open(img_path, "rb") as image_file:
             encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
             return JSONResponse(content={"image_base64": encoded_string})