Create app.py

app.py

@@ -1,4 +1,3 @@
-import os
 import time
 from typing import List, Tuple, Optional
 
@@ -6,11 +5,22 @@ import google.generativeai as genai
 import gradio as gr
 from PIL import Image
 
-# Ensure Google API Key is set
+print("google-generativeai:", genai.__version__)
+
 GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
 
-TITLE = """<h1 align="center">☕ Espresso with LeProf 🔥</h1>"""
-SUBTITLE = """<h2 align="center">🌟 Knowledge Shots for Curious Minds</h2>"""
+TITLE = """<h1 align="center">🕹️ Google Gemini Chatbot 🔥</h1>"""
+SUBTITLE = """<h2 align="center">🎨Create with Multimodal Gemini</h2>"""
+DUPLICATE = """
+<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
+    <a href="https://huggingface.co/spaces/Rahatara/build_with_gemini/blob/main/allgemapp.py?duplicate=true">
+        <img src="https://bit.ly/3gLdBN6" alt="Duplicate Space" style="margin-right: 10px;">
+    </a>
+    <span>Duplicate the Space and run securely with your 
+        <a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>.
+    </span>
+</div>
+"""
 
 IMAGE_WIDTH = 512
 
@@ -22,7 +32,6 @@ def preprocess_image(image: Image.Image) -> Image.Image:
     return image.resize((IMAGE_WIDTH, image_height))
 
 def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
-    """Handles user input and appends to the chatbot."""
     return "", chatbot + [[text_prompt, None]]
 
 def bot(
@@ -33,27 +42,13 @@ def bot(
     stop_sequences: str,
     top_k: int,
     top_p: float,
-    topic: str,
-    chatbot: List[Tuple[str, str]],
+    chatbot: List[Tuple[str, str]]
 ):
-    """Generates a response using Google Gemini."""
     google_key = google_key or GOOGLE_API_KEY
     if not google_key:
         raise ValueError("GOOGLE_API_KEY is not set. Please set it up.")
-    if not topic:
-        raise ValueError("Topic is not set. Please provide a topic.")
 
-    # Get the user's input
     text_prompt = chatbot[-1][0]
-
-    # Construct the system prompt
-    analysis_system_prompt = (
-        f"You are an expert in {topic}. Analyze the provided text with a focus on {topic}, "
-        "identifying recent issues, insights, or improvements relevant to academic standards and effectiveness. "
-        "Offer actionable advice for enhancing knowledge and provide real-life examples."
-    )
-
-    # Configure Generative AI model
     genai.configure(api_key=google_key)
     generation_config = genai.types.GenerationConfig(
         temperature=temperature,
@@ -61,122 +56,63 @@ def bot(
         stop_sequences=preprocess_stop_sequences(stop_sequences),
         top_k=top_k,
         top_p=top_p,
+        #instructions = "You are an expert stylist"
     )
 
-    model_name = "gemini-1.5-pro-latest"
+    model_name = "gemini-1.5-pro-latest" 
     model = genai.GenerativeModel(model_name)
+    inputs = [text_prompt] if image_prompt is None else [text_prompt, preprocess_image(image_prompt)]
+    
+    response = model.generate_content(inputs, stream=True, generation_config=generation_config)
+    response.resolve()
 
-    try:
-        # Pass the system prompt and user input as a single prompt
-        response = model.generate_content(
-            prompt=analysis_system_prompt,
-            input=text_prompt,
-            generation_config=generation_config,
-        )
-    except KeyError as e:
-        raise KeyError(f"Error in response generation: {e}")
-
-    # Process and stream the response
     chatbot[-1][1] = ""
     for chunk in response:
         for i in range(0, len(chunk.text), 10):
-            chatbot[-1][1] += chunk.text[i : i + 10]
+            chatbot[-1][1] += chunk.text[i:i + 10]
             time.sleep(0.01)
             yield chatbot
 
-# Gradio Components
 google_key_component = gr.Textbox(
     label="GOOGLE API KEY",
     type="password",
-    placeholder="Enter your API key...",
-    visible=GOOGLE_API_KEY is None,
+    placeholder="...",
+    visible=GOOGLE_API_KEY is None
 )
 
-topic_input = gr.Textbox(label="Set the Topic", placeholder="e.g., AI in Education, Human-Computer Interaction")
-text_prompt_component = gr.Textbox(label="Ask LeProf", placeholder="Type your question here...")
-chatbot_component = gr.Chatbot(label="LeProf says")
-run_button_component = gr.Button("🫗 Get Your Knowledge Shot")
-
-example_data = [
-    ["AI in Education", "What are the challenges in AI tools for personalized learning?"],
-    ["Multimedia Accessibility", "How can multimedia be made more accessible to people with disabilities?"],
-    ["Ethical AI", "What are the ethical implications of AI in social media content moderation?"],
-    ["Virtual Reality", "How does virtual reality improve skill training in industries?"],
-    ["Augmented Reality", "What are the UX challenges in augmented reality for urban navigation?"],
-]
-
-# Advanced Settings
-temperature_component = gr.Slider(
-    minimum=0, maximum=1.0, value=0.4, step=0.05, label="Creativity Level"
-)
-max_output_tokens_component = gr.Slider(
-    minimum=1, maximum=2048, value=1024, step=1, label="Max Tokens"
-)
-stop_sequences_component = gr.Textbox(label="Stop Sequences", placeholder="e.g., STOP, END")
-top_k_component = gr.Slider(
-    minimum=1, maximum=40, value=32, step=1, label="Top-K Sampling"
-)
-top_p_component = gr.Slider(
-    minimum=0, maximum=1.0, value=1.0, step=0.01, label="Top-P Sampling"
-)
+image_prompt_component = gr.Image(type="pil", label="Image")
+chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False)
+text_prompt_component = gr.Textbox(placeholder="Hi there!", label="Ask me anything and press Enter")
+run_button_component = gr.Button("Run")
+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", 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, image_prompt_component, temperature_component, max_output_tokens_component, stop_sequences_component, top_k_component, top_p_component, chatbot_component]
 
-# Layout with Gradio Blocks
 with gr.Blocks() as demo:
     gr.HTML(TITLE)
     gr.HTML(SUBTITLE)
-    google_key_component.render()
-    topic_input.render()
-    chatbot_component.render()
-    text_prompt_component.render()
-    gr.Examples(
-        examples=example_data,
-        inputs=[topic_input, text_prompt_component],
-        label="Example Questions",
-    )
-    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 Settings", open=False):
-            top_k_component.render()
-            top_p_component.render()
-
-    # Event Handlers
-    run_button_component.click(
-        fn=user, inputs=[text_prompt_component, chatbot_component], outputs=[text_prompt_component, chatbot_component], queue=False
-    ).then(
-        fn=bot,
-        inputs=[
-            google_key_component,
-            None,  # Placeholder for image_prompt (not used in this example)
-            temperature_component,
-            max_output_tokens_component,
-            stop_sequences_component,
-            top_k_component,
-            top_p_component,
-            topic_input,
-            chatbot_component,
-        ],
-        outputs=[chatbot_component]
-    )
-    text_prompt_component.submit(
-        fn=user, inputs=[text_prompt_component, chatbot_component], outputs=[text_prompt_component, chatbot_component], queue=False
-    ).then(
-        fn=bot,
-        inputs=[
-            google_key_component,
-            None,  # Placeholder for image_prompt (not used in this example)
-            temperature_component,
-            max_output_tokens_component,
-            stop_sequences_component,
-            top_k_component,
-            top_p_component,
-            topic_input,
-            chatbot_component,
-        ],
-        outputs=[chatbot_component]
-    )
-
-# Launch the App
-demo.launch()
+    gr.HTML(DUPLICATE)
+    with gr.Column():
+        google_key_component.render()
+        with gr.Row():
+            image_prompt_component.render()
+            chatbot_component.render()
+        text_prompt_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])
+demo.launch()
+-i wanted my custom app to be functional like this one. Fux my code taking Reference  then apply my customization for le prof one . I have utilized system instructions there. And more modifications as discussed