Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,304 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import openai
+import requests
+from PIL import Image
+from io import BytesIO
+import re
+import urllib.parse
 
+# Set up the page
+st.set_page_config(
+    page_title="AI Thumbnail Generator", 
+    page_icon="🎬",
+    layout="wide"
+)
+
+st.title("🎬 AI Video Thumbnail Generator")
+st.write("Generate engaging thumbnails for your videos using only OpenAI API")
+
+# Sidebar for API key
+with st.sidebar:
+    st.header("🔑 Configuration")
+    openai_api_key = st.text_input("OpenAI API Key", type="password")
+    
+    if openai_api_key:
+        openai.api_key = openai_api_key
+        st.success("API Key loaded!")
+    else:
+        st.warning("Enter your OpenAI API key to continue")
+
+def extract_video_info(url):
+    """Extract video information from URL using pattern matching"""
+    video_info = {"platform": "unknown", "title": "", "id": ""}
+    
+    # YouTube patterns
+    youtube_patterns = [
+        r'(?:youtube\.com/watch\?v=|youtu\.be/)([a-zA-Z0-9_-]+)',
+        r'youtube\.com/embed/([a-zA-Z0-9_-]+)'
+    ]
+    
+    for pattern in youtube_patterns:
+        match = re.search(pattern, url)
+        if match:
+            video_info["platform"] = "youtube"
+            video_info["id"] = match.group(1)
+            break
+    
+    # Vimeo pattern
+    vimeo_match = re.search(r'vimeo\.com/(\d+)', url)
+    if vimeo_match:
+        video_info["platform"] = "vimeo"
+        video_info["id"] = vimeo_match.group(1)
+    
+    # Extract filename from URL for other videos
+    if video_info["platform"] == "unknown":
+        parsed_url = urllib.parse.urlparse(url)
+        filename = parsed_url.path.split('/')[-1]
+        video_info["title"] = filename.replace('.mp4', '').replace('.avi', '').replace('.mov', '')
+    
+    return video_info
+
+def analyze_video_content(url, custom_description=""):
+    """Use GPT to analyze and create description for thumbnail generation"""
+    
+    video_info = extract_video_info(url)
+    
+    prompt = f"""
+    I need to create an engaging thumbnail for a video. Here's what I know:
+
+    Video URL: {url}
+    Platform: {video_info['platform']}
+    Video ID: {video_info['id']}
+    
+    """
+    
+    if custom_description:
+        prompt += f"User Description: {custom_description}\n"
+    
+    prompt += """
+    Based on this information, create a detailed description for an engaging video thumbnail that would:
+    1. Grab viewers' attention
+    2. Represent the video content accurately  
+    3. Look professional and clickable
+    4. Include visual elements, colors, and composition suggestions
+
+    Respond with a clear, detailed description in 2-3 sentences that I can use to generate the thumbnail image.
+    """
+    
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=200,
+            temperature=0.7
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        st.error(f"Error analyzing video: {str(e)}")
+        return None
+
+def generate_thumbnail(description, style="professional", size="1024x1024"):
+    """Generate thumbnail using DALL-E"""
+    
+    style_prompts = {
+        "professional": "professional, clean, high-quality",
+        "creative": "creative, artistic, visually striking", 
+        "minimalist": "minimalist, clean, simple design",
+        "colorful": "vibrant, colorful, eye-catching",
+        "dramatic": "dramatic lighting, cinematic, bold"
+    }
+    
+    full_prompt = f"""
+    Create a {style_prompts[style]} YouTube-style thumbnail image: {description}
+    
+    Requirements:
+    - 16:9 aspect ratio suitable for video thumbnails
+    - High contrast and bold visual elements
+    - Professional quality that would perform well on video platforms
+    - Engaging composition that draws the eye
+    """
+    
+    try:
+        response = openai.Image.create(
+            prompt=full_prompt,
+            n=1,
+            size=size,
+            quality="hd" if size == "1024x1024" else "standard"
+        )
+        
+        image_url = response.data[0].url
+        image_response = requests.get(image_url)
+        return Image.open(BytesIO(image_response.content))
+        
+    except Exception as e:
+        st.error(f"Error generating thumbnail: {str(e)}")
+        return None
+
+# Main interface
+st.header("📥 Input")
+
+col1, col2 = st.columns([2, 1])
+
+with col1:
+    video_url = st.text_input(
+        "Video URL:", 
+        placeholder="https://youtube.com/watch?v=... or https://example.com/video.mp4",
+        help="Paste any video URL here"
+    )
+
+with col2:
+    custom_description = st.text_area(
+        "Video Description (Optional):",
+        placeholder="Describe your video content...",
+        height=100,
+        help="Add details about your video for better thumbnails"
+    )
+
+# Style and options
+st.header("🎨 Customization")
+
+col1, col2, col3 = st.columns(3)
+
+with col1:
+    thumbnail_style = st.selectbox(
+        "Thumbnail Style:",
+        ["professional", "creative", "minimalist", "colorful", "dramatic"],
+        help="Choose the visual style for your thumbnail"
+    )
+
+with col2:
+    image_size = st.selectbox(
+        "Image Size:",
+        ["1024x1024", "512x512"],
+        help="Higher resolution costs more but looks better"
+    )
+
+with col3:
+    num_variations = st.slider(
+        "Number of Variations:",
+        min_value=1,
+        max_value=4,
+        value=1,
+        help="Generate multiple thumbnail options"
+    )
+
+# Generate button
+if st.button("🚀 Generate Thumbnail", type="primary", use_container_width=True):
+    
+    if not video_url:
+        st.error("❌ Please enter a video URL")
+        
+    elif not openai_api_key:
+        st.error("❌ Please enter your OpenAI API key in the sidebar")
+        
+    else:
+        # Step 1: Analyze video content
+        with st.spinner("🔍 Analyzing video content..."):
+            analysis = analyze_video_content(video_url, custom_description)
+            
+        if analysis:
+            st.success("✅ Video analysis complete!")
+            
+            with st.expander("📝 AI Analysis", expanded=True):
+                st.write(analysis)
+            
+            # Step 2: Generate thumbnails
+            st.header("🖼️ Generated Thumbnails")
+            
+            for i in range(num_variations):
+                with st.spinner(f"🎨 Generating thumbnail {i+1}/{num_variations}..."):
+                    
+                    # Add variation to prompt for multiple generations
+                    varied_analysis = analysis
+                    if num_variations > 1:
+                        varied_analysis += f" (Style variation {i+1})"
+                    
+                    thumbnail = generate_thumbnail(varied_analysis, thumbnail_style, image_size)
+                    
+                    if thumbnail:
+                        col1, col2 = st.columns([3, 1])
+                        
+                        with col1:
+                            st.image(
+                                thumbnail, 
+                                caption=f"Thumbnail {i+1} - {thumbnail_style.title()} Style",
+                                use_column_width=True
+                            )
+                        
+                        with col2:
+                            # Download button
+                            buffer = BytesIO()
+                            thumbnail.save(buffer, format="PNG")
+                            st.download_button(
+                                label="📥 Download",
+                                data=buffer.getvalue(),
+                                file_name=f"thumbnail_{i+1}_{thumbnail_style}.png",
+                                mime="image/png",
+                                key=f"download_{i}",
+                                use_container_width=True
+                            )
+                        
+                        st.divider()
+        else:
+            st.error("❌ Failed to analyze video content. Please try again.")
+
+# Information sections
+st.header("ℹ️ How It Works")
+
+col1, col2, col3 = st.columns(3)
+
+with col1:
+    st.subheader("1️⃣ URL Analysis")
+    st.write("AI analyzes your video URL and description to understand the content")
+
+with col2:
+    st.subheader("2️⃣ Content Description") 
+    st.write("GPT-4 creates a detailed description optimized for thumbnail generation")
+
+with col3:
+    st.subheader("3️⃣ Image Generation")
+    st.write("DALL-E creates professional thumbnails based on the analysis")
+
+# Supported platforms
+st.header("🌐 Supported Platforms")
+st.info("""
+✅ **Fully Supported:** YouTube, Vimeo, direct video file URLs  
+✅ **Partially Supported:** Any video URL (works with custom descriptions)  
+✅ **Best Results:** Provide detailed video descriptions for better thumbnails
+""")
+
+# Pricing info
+st.header("💰 Cost Information")
+cost_info = f"""
+**OpenAI API Costs (approximate):**
+- GPT-4 Analysis: ~$0.001 per video
+- DALL-E Image Generation: ~$0.04 per {image_size} image
+- **Total per thumbnail:** ~$0.041 USD
+
+*Costs may vary based on current OpenAI pricing*
 """
-# Welcome to Streamlit!
+st.info(cost_info)
 
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# Tips
+st.header("💡 Tips for Best Results")
+tips = """
+🎯 **For Better Thumbnails:**
+- Provide detailed video descriptions
+- Use keywords that describe the mood/style
+- Try different style variations
+- Include the target audience in your description
 
-In the meantime, below is an example of what you can do with just a few lines of code:
+🚀 **Platform Optimization:**
+- Use colorful/dramatic styles for YouTube
+- Professional style works well for business content
+- Minimalist style good for educational content
 """
+st.info(tips)
 
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# Footer
+st.divider()
+st.markdown("""
+<div style='text-align: center; color: #666;'>
+    <p>Built with ❤️ using Streamlit and OpenAI API</p>
+</div>
+""", unsafe_allow_html=True)