Update app.py

app.py

@@ -1,58 +1,211 @@
-import gradio as gr
-import google.generativeai as genai
 import os
-from dotenv import load_dotenv
+import time
+import uuid
+from typing import List, Tuple, Optional, Dict, Union
+
+import google.generativeai as genai
+import gradio as gr
+from PIL import Image
+
+print("google-generativeai:", genai.__version__)
+
+GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
+
+TITLE = """<h1 align="center">Gemini Playground 💬</h1>"""
+SUBTITLE = """<h2 align="center">Play with Gemini Pro and Gemini Pro Vision</h2>"""
+DES = """
+<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
+    <span>Run with your 
+        <a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>.
+    </span>
+</div>
+"""
 
-# Cargar variables de entorno
-load_dotenv()
+IMAGE_CACHE_DIRECTORY = "/tmp"
+IMAGE_WIDTH = 512
+CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]]
 
-# Configurar la API de Google Gemini
-genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
+    return [sequence.strip() for sequence in stop_sequences.split(",")] if stop_sequences else None
 
-def respond(
-    message,
-    history,
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
+def preprocess_image(image: Image.Image) -> Optional[Image.Image]:
+    if image:
+        image_height = int(image.height * IMAGE_WIDTH / image.width)
+        return image.resize((IMAGE_WIDTH, image_height))
+
+def cache_pil_image(image: Image.Image) -> str:
+    image_filename = f"{uuid.uuid4()}.jpeg"
+    os.makedirs(IMAGE_CACHE_DIRECTORY, exist_ok=True)
+    image_path = os.path.join(IMAGE_CACHE_DIRECTORY, image_filename)
+    image.save(image_path, "JPEG")
+    return image_path
+
+def upload(files: Optional[List[str]], chatbot: CHAT_HISTORY) -> CHAT_HISTORY:
+    for file in files:
+        image = Image.open(file).convert('RGB')
+        image_preview = preprocess_image(image)
+        if image_preview:
+            # Display a preview of the uploaded image
+            gr.Image(image_preview).render()
+        image_path = cache_pil_image(image)
+        chatbot.append(((image_path,), None))
+    return chatbot
+
+def user(text_prompt: str, chatbot: CHAT_HISTORY):
+    if text_prompt:
+        chatbot.append((text_prompt, None))
+    return "", chatbot
+
+def bot(
+    google_key: str,
+    files: Optional[List[str]],
+    temperature: float,
+    max_output_tokens: int,
+    stop_sequences: str,
+    top_k: int,
+    top_p: float,
+    chatbot: CHAT_HISTORY
 ):
-    messages = [{"role": "system", "content": system_message}]
-    
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    # Configurar el modelo de Gemini
-    model_name = "gemini-1.5-pro"  # Ajusta el modelo según sea necesario
-    generation_config = {
-        "temperature": temperature,
-        "top_p": top_p,
-        "max_output_tokens": max_tokens,
-        "response_mime_type": "text/plain",
-    }
-    model = genai.GenerativeModel(model_name=model_name, generation_config=generation_config)
-    chat_session = model.start_chat(
-        history=messages
+    if not google_key and not GOOGLE_API_KEY:
+        raise ValueError("GOOGLE_API_KEY is not set.")
+
+    genai.configure(api_key=google_key if google_key else GOOGLE_API_KEY)
+    generation_config = genai.types.GenerationConfig(
+        temperature=temperature,
+        max_output_tokens=max_output_tokens,
+        stop_sequences=preprocess_stop_sequences(stop_sequences=stop_sequences),
+        top_k=top_k,
+        top_p=top_p
     )
-    response = chat_session.send_message(message)
-    return response.text
 
+    text_prompt = [chatbot[-1][0]] if chatbot and chatbot[-1][0] and isinstance(chatbot[-1][0], str) else []
+    image_prompt = [preprocess_image(Image.open(file).convert('RGB')) for file in files] if files else []
+    model_name = 'gemini-pro-vision' if files else 'gemini-pro'
+    model = genai.GenerativeModel(model_name)
+    response = model.generate_content(text_prompt + image_prompt, stream=True, generation_config=generation_config)
+
+    chatbot[-1][1] = ""
+    for chunk in response:
+        for i in range(0, len(chunk.text), 10):
+            section = chunk.text[i:i + 10]
+            chatbot[-1][1] += section
+            time.sleep(0.01)
+            yield chatbot
 
-# Crear la interfaz de Gradio
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a helpful assistant.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-    ],
+google_key_component = gr.Textbox(
+    label="GOOGLE API KEY",
+    value="",
+    type="password",
+    placeholder="...",
+    info="Please provide your own GOOGLE_API_KEY for this app",
+    visible=GOOGLE_API_KEY is None
+)
+chatbot_component = gr.Chatbot(
+    label='Gemini',
+    bubble_full_width=False,
+    scale=2,
+    height=600
+)
+text_prompt_component = gr.Textbox(
+    placeholder="Message...", show_label=False, autofocus=True, scale=8
 )
+upload_button_component = gr.UploadButton(
+    label="Upload Images", file_count="multiple", file_types=["image"], scale=1
+)
+run_button_component = gr.Button(value="Run", variant="primary", scale=1)
+temperature_component = gr.Slider(
+    minimum=0,
+    maximum=1.0,
+    value=0.4,
+    step=0.05,
+    label="Temperature",
+)
+max_output_tokens_component = gr.Slider(
+    minimum=1,
+    maximum=2048,
+    value=1024,
+    step=1,
+    label="Token limit",
+)
+stop_sequences_component = gr.Textbox(
+    label="Add stop sequence",
+    value="",
+    type="text",
+    placeholder="STOP, END",
+)
+top_k_component = gr.Slider(
+    minimum=1,
+    maximum=40,
+    value=32,
+    step=1,
+    label="Top-K",
+)
+top_p_component = gr.Slider(
+    minimum=0,
+    maximum=1,
+    value=1,
+    step=0.01,
+    label="Top-P",
+)
+
+user_inputs = [
+    text_prompt_component,
+    chatbot_component
+]
+
+bot_inputs = [
+    google_key_component,
+    upload_button_component,
+    temperature_component,
+    max_output_tokens_component,
+    stop_sequences_component,
+    top_k_component,
+    top_p_component,
+    chatbot_component
+]
+
+with gr.Blocks() as demo:
+    gr.HTML(TITLE)
+    gr.HTML(SUBTITLE)
+    gr.HTML(DES)
+    with gr.Column():
+        google_key_component.render()
+        chatbot_component.render()
+        with gr.Row():
+            text_prompt_component.render()
+            upload_button_component.render()
+            run_button_component.render()
+        with gr.Accordion("Parameters", open=False):
+            temperature_component.render()
+            max_output_tokens_component.render()
+            stop_sequences_component.render()
+            with gr.Accordion("Advanced", open=False):
+                top_k_component.render()
+                top_p_component.render()
+
+    run_button_component.click(
+        fn=user,
+        inputs=user_inputs,
+        outputs=[text_prompt_component, chatbot_component],
+        queue=False
+    ).then(
+        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
+    )
+
+    text_prompt_component.submit(
+        fn=user,
+        inputs=user_inputs,
+        outputs=[text_prompt_component, chatbot_component],
+        queue=False
+    ).then(
+        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
+    )
+
+    upload_button_component.upload(
+        fn=upload,
+        inputs=[upload_button_component, chatbot_component],
+        outputs=[chatbot_component],
+        queue=False
+    )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.queue(max_size=99).launch(debug=False, show_error=True)