Update app.py

app.py

@@ -4,20 +4,14 @@ from typing import List, Tuple, Optional
 import google.generativeai as genai
 import gradio as gr
 from PIL import Image
-import tempfile
-import os
 
+# 1. محاولة جلب المفتاح من النظام (Secrets)
 GOOGLE_API_KEY = os.environ.get("GEMINI_API_KEY")
 
 IMAGE_WIDTH = 512
-IMAGE_WIDTH = 512
-
-system_instruction_analysis = "You are an expert of the given topic. Analyze the provided text with a focus on the topic, identifying recent issues, recent insights, or improvements relevant to academic standards and effectiveness. Offer actionable advice for enhancing knowledge and suggest real-life examples."
+system_instruction_analysis = "You are an expert of the given topic. Analyze text and images with academic standards."
 model_name = "gemini-2.0-flash-exp"
-#model = genai.GenerativeModel(model_name, system_instruction=system_instruction_analysis)
-#genai.configure(api_key=google_key)
 
-# Helper Functions
 def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
     return [seq.strip() for seq in stop_sequences.split(",")] if stop_sequences else None
 
@@ -38,172 +32,85 @@ def bot(
     top_p: float,
     chatbot: List[Tuple[str, str]]
 ):
-    #google_key = google_key or GOOGLE_API_KEY
+    # استخدام المفتاح من الخانة أو من السيكرتس
     used_api_key = google_key if google_key else GOOGLE_API_KEY
+    
     if not used_api_key:
-        chatbot[-1][1] = "❌ No API Key found! Please provide it."
+        chatbot[-1][1] = "❌ No API Key found! Please provide it in the textbox or set GEMINI_API_KEY in Secrets."
         yield chatbot
         return
 
+    # ضبط الإعدادات وتفعيل الموديل داخل الدالة (لضمان الترتيب الصحيح)
+    genai.configure(api_key=used_api_key)
+    
+    generation_config = genai.types.GenerationConfig(
+        temperature=temperature,
+        max_output_tokens=max_output_tokens,
+        stop_sequences=preprocess_stop_sequences(stop_sequences),
+        top_k=top_k,
+        top_p=top_p,
+    )
+    
+    model = genai.GenerativeModel(model_name, system_instruction=system_instruction_analysis)
+
     text_prompt = chatbot[-1][0].strip() if chatbot[-1][0] else None
 
-    # Handle cases for text and/or image input
     if not text_prompt and not image_prompt:
-        chatbot[-1][1] = "Prompt cannot be empty. Please provide input text or an image."
+        chatbot[-1][1] = "Prompt cannot be empty."
         yield chatbot
         return
-    elif image_prompt and not text_prompt:
-        # If only an image is provided
-        text_prompt = "Describe the image"
-    elif image_prompt and text_prompt:
-        # If both text and image are provided, combine them
-        text_prompt = f"{text_prompt}. Also, analyze the provided image."
+    
+    # تحضير المدخلات
+    inputs = []
+    if text_prompt:
+        inputs.append(text_prompt)
+    if image_prompt:
+        inputs.append(preprocess_image(image_prompt))
 
-    # Configure the model
-    genai.configure(api_key=used_api_key)
-    #generation_config = genai.types.GenerationConfig(
-    #    temperature=temperature,
-    #    max_output_tokens=max_output_tokens,
-    #    stop_sequences=preprocess_stop_sequences(stop_sequences),
-    #    top_k=top_k,
-    #    top_p=top_p,
-    #)
-    model = genai.GenerativeModel(model_name, system_instruction=system_instruction_analysis)
-
-    # Prepare inputs
-    text_prompt = chatbot[-1][0].strip() if chatbot[-1][0] else None
-    inputs = [text_prompt] if image_prompt is None else [text_prompt, image_prompt]
-
-    # Generate response
     try:
+        # توليد الاستجابة مع تفعيل الـ stream
         response = model.generate_content(inputs, stream=True, generation_config=generation_config)
-        response.resolve()
+        chatbot[-1][1] = ""
+        for chunk in response:
+            chatbot[-1][1] += chunk.text
+            yield chatbot
     except Exception as e:
-        chatbot[-1][1] = f"Error occurred: {str(e)}"
+        chatbot[-1][1] = f"Error: {str(e)}"
         yield chatbot
-        return
-
-    # Stream the response back to the chatbot
-    chatbot[-1][1] = ""
-    for chunk in response:
-        for i in range(0, len(chunk.text), 10):
-            chatbot[-1][1] += chunk.text[i:i + 10]
-            time.sleep(0.01)
-            yield chatbot
-# Components
-google_key_component = gr.Textbox(
-    label="Google API Key",
-    type="password",
-    placeholder="Enter your Google API Key",
-    visible=GOOGLE_API_KEY is None
-)
-
-image_prompt_component = gr.Image(type="pil", label="Input Image (Optional: Figure/Graph)")
-chatbot_component = gr.Chatbot(label="Chatbot", bubble_full_width=False)
-text_prompt_component = gr.Textbox(
-    placeholder="Type your question here...",
-    label="Ask",
-    lines=3
-)
-run_button_component = gr.Button("Submit")
-temperature_component = gr.Slider(
-    minimum=0,
-    maximum=1.0,
-    value=0.4,
-    step=0.05,
-    label="Creativity (Temperature)",
-    info="Controls the randomness of the response. Higher values result in more creative answers."
-)
-max_output_tokens_component = gr.Slider(
-    minimum=1,
-    maximum=2048,
-    value=1024,
-    step=1,
-    label="Response Length (Token Limit)",
-    info="Sets the maximum number of tokens in the output response."
-)
-stop_sequences_component = gr.Textbox(
-    label="Stop Sequences (Optional)",
-    placeholder="Enter stop sequences, e.g., STOP, END",
-    info="Specify sequences to stop the generation."
-)
-top_k_component = gr.Slider(
-    minimum=1,
-    maximum=40,
-    value=32,
-    step=1,
-    label="Top-K Sampling",
-    info="Limits token selection to the top K most probable tokens. Lower values produce conservative outputs."
-)
-top_p_component = gr.Slider(
-    minimum=0,
-    maximum=1,
-    value=1,
-    step=0.01,
-    label="Top-P Sampling",
-    info="Limits token selection to tokens with a cumulative probability up to P. Lower values produce conservative outputs."
-)
-example_scenarios = [
-    "Describe Multimodal AI",
-    "What are the difference between muliagent llm and multiagent system",
-"Why it's difficult to intgrate multimodality in prompt"]
-example_images = [["ex1.png"],["ex2.png"]]
-
-
-# Gradio Interface
-user_inputs = [text_prompt_component, chatbot_component]
-bot_inputs = [
-    google_key_component,
-    image_prompt_component,
-    temperature_component,
-    max_output_tokens_component,
-    stop_sequences_component,
-    top_k_component,
-    top_p_component,
-    chatbot_component,
-]
-
 
+# --- بناء الواجهة ---
 with gr.Blocks(theme="earneleh/paris") as demo:
-    gr.Markdown("<h1 style='font-size: 36px; font-weight: bold; font-family: Arial;'>Gemini Multimodal Chatbot</h1>")
-    with gr.Row():
-        google_key_component.render()
-    with gr.Row():
-        chatbot_component.render()
+    gr.Markdown("# ✨ Gemini 2.0 Multimodal Assistant")
+    
+    # إظهار خانة الـ Key فقط إذا لم يكن موجوداً في السيكرتس
+    google_key_component = gr.Textbox(
+        label="Google API Key",
+        type="password",
+        placeholder="Paste your API key here...",
+        visible=GOOGLE_API_KEY is None or GOOGLE_API_KEY == ""
+    )
+    
+    chatbot_component = gr.Chatbot(label="Conversation", bubble_full_width=False)
+    
     with gr.Row():
-        with gr.Column(scale=0.5):
-           text_prompt_component.render()
-        with gr.Column(scale=0.5):
-           image_prompt_component.render()
-        with gr.Column(scale=0.5):
-            run_button_component.render()
-    with gr.Accordion("🧪Example Text 💬", open=False):
-        example_radio = gr.Radio(
-        choices=example_scenarios,
-        label="Example Queries",
-        info="Select an example query.")
-        # Debug callback
-        example_radio.change(
-        fn=lambda query: query if query else "No query selected.",
-        inputs=[example_radio],
-        outputs=[text_prompt_component])
-       # Custom examples section with blue styling
-    with gr.Accordion("🧪Example Image 🩻", open=False):
-        gr.Examples(
-        examples=example_images,
-        inputs=[image_prompt_component],
-        label="Example Figures",
-        )     
-    with gr.Accordion("🛠️Customize", open=False):
-        temperature_component.render()
-        max_output_tokens_component.render()
-        stop_sequences_component.render()
-        top_k_component.render()
-        top_p_component.render()
-
-    run_button_component.click(
-        fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component]
+        text_prompt_component = gr.Textbox(placeholder="Ask anything...", label="Text Input", scale=3)
+        image_prompt_component = gr.Image(type="pil", label="Image (Optional)", scale=1)
+        run_button = gr.Button("Submit", variant="primary")
+
+    with gr.Accordion("⚙️ Settings (Temperature, Tokens, etc.)", open=False):
+        temp_slider = gr.Slider(0, 1, value=0.4, label="Temperature")
+        max_tokens = gr.Slider(256, 4096, value=1024, label="Max Tokens")
+        stop_seq = gr.Textbox(label="Stop Sequences")
+        top_k_val = gr.Slider(1, 40, value=32, label="Top-K")
+        top_p_val = gr.Slider(0, 1, value=1, label="Top-P")
+
+    # ربط الأحداث
+    run_button.click(
+        user, [text_prompt_component, chatbot_component], [text_prompt_component, chatbot_component]
     ).then(
-        fn=bot, inputs=bot_inputs, outputs=[chatbot_component]
+        bot, 
+        [google_key_component, image_prompt_component, temp_slider, max_tokens, stop_seq, top_k_val, top_p_val, chatbot_component], 
+        chatbot_component
     )
+
 demo.launch()