Update app.py

app.py

@@ -1,4 +1,4 @@
-"""from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, UploadFile
 import fitz  # PyMuPDF for PDF parsing
 from tika import parser  # Apache Tika for document parsing
 import openpyxl
@@ -130,10 +130,10 @@ app = gr.mount_gradio_app(app, demo, path="/")
 @app.get("/")
 def home():
     return RedirectResponse(url="/")
-"""
 
 
-import gradio as gr
+
+"""import gradio as gr
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
@@ -155,7 +155,7 @@ print("✅ AI models loaded successfully!")
 app = FastAPI()
 
 def generate_visualization(excel_file, viz_type, user_request):
-    """Generates Python visualization code and insights based on user requests and Excel data."""
+    Generates Python visualization code and insights based on user requests and Excel data.
     try:
         print("📂 Loading Excel file...")
         df = pd.read_excel(excel_file)
@@ -182,13 +182,13 @@ def generate_visualization(excel_file, viz_type, user_request):
         print("✅ Table analysis completed!")
 
         # ✅ AI-generated code
-        prompt = f"""Generate clean and executable Python code to visualize the following dataset:
+        prompt = f Generate clean and executable Python code to visualize the following dataset:
         Columns: {list(df.columns)}
         Visualization type: {viz_type}
         User request: {user_request}
         Use the provided DataFrame 'df' without reloading it.
         Ensure 'plt.show()' is at the end.
-        """
+        
 
         print("🤖 Sending request to AI code generator...")
         generated_code = code_generator(prompt, max_length=200)[0]['generated_text']
@@ -257,5 +257,4 @@ print("✅ Gradio interface mounted successfully!")
 @app.get("/")
 def home():
     print("🏠 Redirecting to UI...")
-    return RedirectResponse(url="/")
-
+    return RedirectResponse(url="/")"""