Update app.py

app.py

@@ -5,10 +5,10 @@ import os
 import time
 import uuid
 from typing import List, Tuple, Optional, Union
-
 import google.generativeai as genai
 import gradio as gr
 from PIL import Image
+import PyPDF2
 from dotenv import load_dotenv
 
 # Cargar las variables de entorno desde el archivo .env
@@ -39,34 +39,53 @@ def cache_pil_image(image: Image.Image) -> str:
     image.save(image_path, "JPEG")
     return image_path
 
+def cache_file(file) -> str:
+    """Guarda el archivo tal cual en el sistema temporal."""
+    file_path = f"/tmp/{uuid.uuid4()}_{file.name}"
+    with open(file_path, "wb") as f:
+        f.write(file.read())  # Aquí es donde 'file' puede tener el método read()
+    return file_path
+
+def extract_text_from_pdf(pdf_path: str) -> str:
+    """Extrae el texto de un archivo PDF."""
+    with open(pdf_path, 'rb') as f:
+        pdf_reader = PyPDF2.PdfReader(f)
+        text = ""
+        for page in pdf_reader.pages:
+            text += page.extract_text()
+    return text
+
 def upload(files: Optional[List[str]], chatbot: CHAT_HISTORY) -> CHAT_HISTORY:
     for file in files:
-        # Detectar el tipo de archivo y manejarlo adecuadamente
         mime_type = file.type if hasattr(file, 'type') else None
         
         # Si es una imagen, la procesamos con PIL
         if mime_type and mime_type.startswith('image'):
-            image = Image.open(file).convert('RGB')
+            image = Image.open(file.name).convert('RGB')  # Abrir el archivo con su ruta
             image_preview = preprocess_image(image)
             if image_preview:
                 # Mostrar una vista previa de la imagen cargada
                 gr.Image(image_preview).render()
             image_path = cache_pil_image(image)
             chatbot.append(((image_path,), None))
+        
+        # Si es un archivo PDF, lo procesamos y extraemos el texto
+        elif mime_type and mime_type == "application/pdf":
+            pdf_content = extract_text_from_pdf(file.name)
+            chatbot.append((pdf_content, None))
+        
+        # Si es un archivo de texto, lo procesamos directamente
+        elif mime_type and mime_type == "text/plain":
+            with open(file.name, 'r', encoding='utf-8') as f:
+                text_content = f.read()
+            chatbot.append((text_content, None))
+        
         else:
-            # Si no es una imagen, se guarda el archivo tal cual
+            # Si es otro tipo de archivo, se guarda el archivo tal cual
             file_path = cache_file(file)
             chatbot.append(((file_path,), None))
     return chatbot
 
-def cache_file(file: str) -> str:
-    file_filename = f"{uuid.uuid4()}_{os.path.basename(file.name)}"
-    os.makedirs(IMAGE_CACHE_DIRECTORY, exist_ok=True)
-    file_path = os.path.join(IMAGE_CACHE_DIRECTORY, file_filename)
-    with open(file_path, 'wb') as f:
-        f.write(file.read())
-    return file_path
-
 def user(text_prompt: str, chatbot: CHAT_HISTORY):
     if text_prompt:
         chatbot.append((text_prompt, None))
@@ -90,9 +109,9 @@ def bot(
     )
 
     text_prompt = [chatbot[-1][0]] if chatbot and chatbot[-1][0] and isinstance(chatbot[-1][0], str) else []
-    files_paths = [preprocess_image(Image.open(file).convert('RGB')) if file.type.startswith('image') else cache_file(file) for file in files]
+    image_prompt = [preprocess_image(Image.open(file).convert('RGB')) for file in files if file.type.startswith('image')] if files else []
     model = genai.GenerativeModel(model_choice)
-    response = model.generate_content(text_prompt + files_paths, stream=True, generation_config=generation_config)
+    response = model.generate_content(text_prompt + image_prompt, stream=True, generation_config=generation_config)
 
     chatbot[-1][1] = ""
     for chunk in response:
@@ -112,7 +131,7 @@ text_prompt_component = gr.Textbox(
     placeholder="Message...", show_label=False, autofocus=True, scale=8
 )
 upload_button_component = gr.UploadButton(
-    label="Upload Files", file_count="multiple", scale=1
+    label="Upload Files", file_count="multiple", file_types=["image", "pdf", "text"], scale=1
 )
 run_button_component = gr.Button(value="Run", variant="primary", scale=1)
 model_choice_component = gr.Dropdown(
@@ -134,8 +153,8 @@ bot_inputs = [
 ]
 
 with gr.Blocks() as demo:
-    gr.HTML(TITLE)
-    gr.HTML(SUBTITLE)
+    gr.HTML("<h1 align='center'>Gemini Playground ✨</h1>")
+    gr.HTML("<h2 align='center'>Play with Gemini Pro and Gemini Pro Vision</h2>")
     with gr.Column():
         chatbot_component.render()
         with gr.Row():
@@ -170,3 +189,4 @@ with gr.Blocks() as demo:
     )
 
 demo.queue(max_size=99).launch(debug=False, show_error=True)
+