Create app.py

app.py

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+import gradio as gr
+import google.generativeai as genai
+from google.genai import types
+from PIL import Image
+from io import BytesIO
+import base64
+import os
+
+# Initialize the Google Generative AI client with the API key from environment variables
+api_key = os.getenv("GEMINI_API_KEY")
+genai.configure(api_key=api_key)
+
+# Initialize the Gemini model for text generation
+gemini_model = genai.GenerativeModel('gemini-2.5-flash-preview-04-17')
+
+def generate_item(tag):
+    """
+    Generate a single feed item consisting of text from Gemini LLM and an image from Imagen.
+    
+    Args:
+        tag (str): The tag to base the content on.
+    
+    Returns:
+        dict: A dictionary with 'text' (str) and 'image_base64' (str).
+    """
+    # Generate text using Gemini LLM
+    prompt = f"Generate a short, engaging post about {tag} in the style of a TikTok caption."
+    text_response = gemini_model.generate_content(prompt)
+    text = text_response.text.strip()
+
+    # Generate an image using Imagen based on the generated text
+    image_response = genai.generate_images(
+        model='imagen-3.0-generate-002',
+        prompt=text,
+        config=types.GenerateImagesConfig(
+            number_of_images=1,
+            aspect_ratio="9:16",  # TikTok-style vertical video ratio
+            person_generation="DONT_ALLOW"  # Avoid generating people
+        )
+    )
+    generated_image = image_response.generated_images[0]
+    image = Image.open(BytesIO(generated_image.image.image_bytes))
+
+    # Convert the image to base64 for HTML display
+    buffered = BytesIO()
+    image.save(buffered, format="PNG")
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+
+    return {'text': text, 'image_base64': img_str}
+
+def start_feed(tag):
+    """
+    Start a new feed with the given tag by generating one initial item.
+    
+    Args:
+        tag (str): The tag to generate content for.
+    
+    Returns:
+        tuple: (current_tag, feed_items, html_content)
+    """
+    item = generate_item(tag)
+    feed_items = [item]
+    html_content = generate_html(feed_items)
+    return tag, feed_items, html_content
+
+def load_more(current_tag, feed_items):
+    """
+    Append a new item to the existing feed using the current tag.
+    
+    Args:
+        current_tag (str): The tag currently being used for the feed.
+        feed_items (list): The current list of feed items.
+    
+    Returns:
+        tuple: (current_tag, updated_feed_items, updated_html_content)
+    """
+    new_item = generate_item(current_tag)
+    feed_items.append(new_item)
+    html_content = generate_html(feed_items)
+    return current_tag, feed_items, html_content
+
+def generate_html(feed_items):
+    """
+    Generate an HTML string to display the feed items.
+    
+    Args:
+        feed_items (list): List of dictionaries containing 'text' and 'image_base64'.
+    
+    Returns:
+        str: HTML string representing the feed.
+    """
+    html_str = '<div style="max-height: 600px; overflow-y: auto; border: 1px solid #ccc; padding: 10px;">'
+    for item in feed_items:
+        html_str += f"""
+        <div style="margin-bottom: 20px; border-bottom: 1px solid #eee; padding-bottom: 20px;">
+            <p style="font-size: 16px; margin-bottom: 10px;">{item['text']}</p>
+            <img src="data:image/png;base64,{item['image_base64']}" style="width: 100%; max-width: 300px; height: auto;">
+        </div>
+        """
+    html_str += '</div>'
+    return html_str
+
+# Define the Gradio interface
+with gr.Blocks(title="TikTok-Style Infinite Feed") as demo:
+    # Header
+    gr.Markdown("# TikTok-Style Infinite Feed Generator")
+    gr.Markdown("Enter a tag or select a suggested one to generate a scrollable feed of AI-generated content!")
+
+    # Input components
+    with gr.Row():
+        suggested_tags = gr.Dropdown(
+            choices=["technology", "nature", "art", "food"],
+            label="Suggested Tags",
+            value="nature"  # Default value
+        )
+        tag_input = gr.Textbox(label="Enter a Custom Tag", value="nature")
+
+    # Buttons
+    with gr.Row():
+        start_button = gr.Button("Start Feed")
+        load_more_button = gr.Button("Load More")
+
+    # Output display
+    feed_html = gr.HTML(label="Your Feed")
+
+    # State variables to maintain feed and tag
+    current_tag = gr.State(value="")
+    feed_items = gr.State(value=[])
+
+    # Event handlers
+    def set_tag(selected_tag):
+        """Update the tag input when a suggested tag is selected."""
+        return selected_tag
+
+    suggested_tags.change(fn=set_tag, inputs=suggested_tags, outputs=tag_input)
+    start_button.click(
+        fn=start_feed,
+        inputs=tag_input,
+        outputs=[current_tag, feed_items, feed_html]
+    )
+    load_more_button.click(
+        fn=load_more,
+        inputs=[current_tag, feed_items],
+        outputs=[current_tag, feed_items, feed_html]
+    )
+
+# Launch the app
+demo.launch()