Update app.py

app.py

@@ -3,64 +3,34 @@ import gradio as gr
 import google.generativeai as genai
 from dotenv import load_dotenv
 import httpx
+from google.generativeai import types  # Add this import
 
-load_dotenv()
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+# Update PDF URL
+COURSE_PDF_URL = "https://huggingface.co/spaces/JeCabrera/copywriter2a/resolve/main/Oferta%20CopyXpert.pdf"
 
-# PDF URL for course information
-COURSE_PDF_URL = "https://drive.google.com/file/d/1Xf46sT9kSzSVdekSCnz3NsBodpGET1Gi/view?usp=drive_link"
-
-# Load PDF content once at startup
+# Simplify PDF content retrieval
 def get_pdf_content():
     try:
-        # Convert Google Drive link to direct download link
-        file_id = COURSE_PDF_URL.split('/')[5]
-        direct_url = f"https://drive.google.com/uc?export=download&id={file_id}"
-        response = httpx.get(direct_url)
-        
-        # Add verification
+        response = httpx.get(COURSE_PDF_URL)
         if response.status_code == 200:
-            content = response.content
-            content_type = response.headers.get('content-type', '')
-            
             print(f"PDF Download Status: Success")
-            print(f"Content Type: {content_type}")
-            print(f"Content Size: {len(content)} bytes")
-            
-            if 'pdf' in content_type.lower() or content[:4] == b'%PDF':
-                return content
-            else:
-                print("Warning: Downloaded content might not be a PDF")
-                return None
-        else:
-            print(f"Failed to download PDF. Status code: {response.status_code}")
-            return None
-            
+            return response.content
     except Exception as e:
         print(f"Error loading PDF: {e}")
         return None
 
-# Configure model with system prompt and PDF content
-model = genai.GenerativeModel(
-    model_name="gemini-2.0-flash",
-    generation_config={
-        "temperature": 0.9,
-        "top_p": 1,
-        "max_output_tokens": 2048,
-    }
-)
-
 def chat(message, history):
     try:
-        # Get PDF content
         pdf_content = get_pdf_content()
         
-        # Prepare the message with PDF context
         if pdf_content:
             messages = [
                 {"role": "user", "parts": [
                     system_prompt,
-                    types.Part.from_bytes(data=pdf_content, mime_type='application/pdf'),
+                    types.Part.from_bytes(
+                        data=pdf_content,
+                        mime_type='application/pdf'
+                    ),
                     "Use the PDF content to provide detailed answers about the course."
                 ]},
                 *[{"role": "user", "parts": [msg[0]]} for msg in history],
@@ -80,6 +50,8 @@ def chat(message, history):
 
 system_prompt = """You are CopyXpert's Sales Assistant. Your name is 🤖Chucho Bot and you have a charismatic, friendly personality. You ONLY talk about CopyXpert course.
 
+IMPORTANT: Always check the provided PDF document for detailed course information before answering questions. Use this information to provide accurate and complete responses about the course content, benefits, and features.
+
 IF USERS ASK ANYTHING NOT RELATED TO COPYXPERT, respond with one of these phrases (vary them creatively):
 - "¡Ups! Solo hablo de CopyXpert. ¡Es lo único que me apasiona! 🤓"
 - "¡Beep boop! Error: Pregunta no relacionada con CopyXpert detectada. ¿Hablamos del curso? 🤖"