Upload src/streamlit_app.py with huggingface_hub

src/streamlit_app.py

@@ -0,0 +1,269 @@
+=== requirements.txt ===
+streamlit
+Pillow
+
+=== config.py ===
+import os
+
+# --- General Configuration ---
+APP_TITLE = "Sora 2 Simulator: Text & Image to Video Generation"
+ANYCODER_LINK = "https://huggingface.co/spaces/akhaliq/anycoder"
+ANYCODER_TEXT = "Built with anycoder"
+
+# --- Generation Parameters ---
+MIN_DURATION_S = 4
+MAX_DURATION_S = 120
+DEFAULT_DURATION_S = 30
+GENERATION_COST_PER_SECOND = 0.05 # Mock cost
+
+# --- Mock Output Configuration ---
+# NOTE: Since actual binary files cannot be generated or shipped, 
+# we use mock placehoolder URLs/data.
+MOCK_VIDEO_URL = "https://storage.googleapis.com/gtv-videos-bucket/sample/BigBuckBunny.mp4" # Public domain sample video
+MOCK_AUDIO_DATA = "placeholder_audio.mp3" 
+
+# Mock audio data (Base64 encoded silence or small placeholder)
+# In a real app, this would be a loaded audio file.
+# Using a descriptive placeholder here for pure Python execution.
+MOCK_AUDIO_DESCRIPTION = "Simulated high-fidelity audio track generated based on prompt."
+
+# --- UI Texts ---
+DISCLAIMER = (
+    "🚨 **IMPORTANT SIMULATION NOTICE:** The actual OpenAI Sora 2 model is not publicly available. "
+    "This application is a sophisticated simulation demonstrating the expected capabilities and workflow "
+    "of a next-generation video generation interface. Video output is a public domain placeholder."
+)
+
+=== utils.py ===
+import time
+import random
+from config import MOCK_VIDEO_URL, MOCK_AUDIO_DESCRIPTION
+
+def simulate_video_generation(prompt: str, duration_s: int, generate_audio: bool) -> dict:
+    """
+    Simulates the intensive process of generating a video using a large AI model.
+    The mock duration is proportional to the requested video length.
+    """
+    
+    # Calculate simulated generation time (e.g., 0.5s per 10 seconds of video)
+    base_time = 3.0
+    time_per_second = 0.5 
+    
+    simulated_delay = base_time + (duration_s / 10 * time_per_second)
+    
+    # Cap the delay for user experience
+    if simulated_delay > 15:
+        simulated_delay = 15 + random.uniform(0, 5) # Max 20s simulation
+        
+    time.sleep(simulated_delay)
+    
+    # Mock generation metadata
+    output = {
+        "status": "success",
+        "video_url": MOCK_VIDEO_URL,
+        "duration_s": duration_s,
+        "prompt_used": prompt,
+        "model_version": "Sora 2.1 (Simulated)",
+        "cost": round(duration_s * 0.05 + random.uniform(0.5, 1.5), 2), # Mock Cost calculation
+        "audio_description": MOCK_AUDIO_DESCRIPTION if generate_audio else None
+    }
+    
+    return output
+
+=== streamlit_app.py ===
+import streamlit as st
+from PIL import Image
+import io
+from config import (
+    APP_TITLE, ANYCODER_LINK, ANYCODER_TEXT,
+    MIN_DURATION_S, MAX_DURATION_S, DEFAULT_DURATION_S,
+    GENERATION_COST_PER_SECOND, DISCLAIMER
+)
+from utils import simulate_video_generation
+
+# --- Configuration and Setup ---
+st.set_page_config(
+    page_title=APP_TITLE,
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Initialize Session State
+if 'generation_output' not in st.session_state:
+    st.session_state.generation_output = None
+if 'is_running' not in st.session_state:
+    st.session_state.is_running = False
+
+def clear_output():
+    """Clears the previous generation results."""
+    st.session_state.generation_output = None
+
+def handle_generation(prompt, image_file, duration_s, generate_audio):
+    """Handles the submission and simulation process."""
+    if st.session_state.is_running:
+        st.warning("A generation task is already running. Please wait.")
+        return
+
+    st.session_state.is_running = True
+    clear_output()
+
+    input_prompt = prompt
+    if image_file:
+        # Simulate processing the image input
+        input_prompt = f"Image-to-Video: {image_file.name}. Prompt: {prompt}"
+
+    try:
+        # Display feedback and run simulation
+        with st.spinner(f"Generating high-fidelity video sequence ({duration_s}s)... This may take up to 20 seconds."):
+            output = simulate_video_generation(input_prompt, duration_s, generate_audio)
+            st.session_state.generation_output = output
+        
+        st.balloons()
+        st.success("Video generation complete!")
+
+    except Exception as e:
+        st.error(f"An error occurred during simulation: {e}")
+    finally:
+        st.session_state.is_running = False
+        st.rerun()
+
+
+# --- Sidebar UI ---
+with st.sidebar:
+    st.title("Sora 2 Controls")
+    st.markdown(
+        f"""
+        **Maximum Duration:** {MAX_DURATION_S // 60}m {MAX_DURATION_S % 60}s  
+        **Input Modes:** Text-to-Video, Image-to-Video
+        """
+    )
+    
+    # Custom CSS for the sidebar link
+    st.markdown(
+        f"""
+        <style>
+            .footer-link {{
+                font-size: 0.8rem;
+                color: #888888;
+                margin-top: 15px;
+            }}
+        </style>
+        <div class="footer-link">
+            <a href="{ANYCODER_LINK}" target="_blank">{ANYCODER_TEXT}</a>
+        </div>
+        """,
+        unsafe_allow_html=True
+    )
+
+# --- Main Application UI ---
+st.markdown(f"## {APP_TITLE}")
+st.caption(DISCLAIMER)
+st.divider()
+
+# Input Form
+with st.form("sora_generation_form", clear_on_submit=False):
+    col1, col2 = st.columns([3, 1])
+    
+    with col1:
+        prompt = st.text_area(
+            "🎬 Describe your desired scene (Text-to-Video)",
+            placeholder="A golden retriever wearing a tiny chef's hat, baking bread on a cloud, cinematic 8K, highly detailed.",
+            height=100
+        )
+    
+    with col2:
+        image_file = st.file_uploader(
+            "🖼️ Upload starting image (Image-to-Video)",
+            type=["png", "jpg", "jpeg"],
+            help="Optional: Start the video generation from a specific image."
+        )
+
+        if image_file:
+            st.image(image_file, caption="Input Image Preview", use_column_width=True)
+
+    st.subheader("Generation Settings")
+    
+    settings_col1, settings_col2, settings_col3 = st.columns(3)
+    
+    with settings_col1:
+        video_duration = st.slider(
+            "⏱️ Video Duration (seconds)",
+            min_value=MIN_DURATION_S,
+            max_value=MAX_DURATION_S,
+            value=DEFAULT_DURATION_S,
+            step=1,
+            help=f"Generates videos from {MIN_DURATION_S}s up to 2 minutes."
+        )
+    
+    with settings_col2:
+        generate_audio = st.checkbox(
+            "🔊 Generate Realistic Audio Track",
+            value=True,
+            help="Sora 2 includes synchronized, high-fidelity audio generation."
+        )
+        
+    with settings_col3:
+        # Mock Cost Display
+        mock_cost = round(video_duration * GENERATION_COST_PER_SECOND, 2)
+        st.metric(
+            label="Estimated Token Cost (Mock)",
+            value=f"${mock_cost:.2f}",
+            delta=f"${GENERATION_COST_PER_SECOND} / second"
+        )
+    
+    st.markdown("---")
+    
+    # Disable button if inputs are missing
+    is_disabled = not (prompt or image_file) or st.session_state.is_running
+    
+    submit_button = st.form_submit_button(
+        label="⚡ Generate Video (Simulated)",
+        type="primary",
+        disabled=is_disabled
+    )
+    
+    if submit_button:
+        if not prompt and image_file:
+             st.warning("Please provide a text prompt to guide the video generation, even if uploading an image.")
+        elif not prompt and not image_file:
+            st.error("Please provide either a text description or an image file to start.")
+        else:
+            handle_generation(prompt, image_file, video_duration, generate_audio)
+
+
+# --- Output Display ---
+if st.session_state.generation_output:
+    output = st.session_state.generation_output
+    st.subheader("🎥 Sora 2 Simulated Output")
+    
+    st.info(f"Generated successfully in {output['duration_s']} seconds using **{output['model_version']}**.")
+    
+    # Layout for metadata and video
+    output_col1, output_col2 = st.columns([1, 2])
+    
+    with output_col1:
+        st.markdown("**Generation Metadata**")
+        st.json({
+            "Prompt Input": output['prompt_used'][:100] + "...",
+            "Output Duration": f"{output['duration_s']} seconds",
+            "Simulated Cost": f"${output['cost']:.2f}",
+        })
+        
+        st.download_button(
+            label="⬇️ Download Video (Mock File)",
+            data="This is a simulated download link.",
+            file_name="sora_output_simulated.mp4",
+            mime="text/plain",
+            type="secondary"
+        )
+
+    with output_col2:
+        st.markdown("### Video Output (Public Placeholder)")
+        st.video(output['video_url'], format="video/mp4", start_time=0)
+        
+        if output['audio_description']:
+            st.markdown("### Audio Track")
+            st.markdown(f"**Description:** {output['audio_description']}")
+            # Streamlit audio component using a simple placeholder representation
+            st.audio(data=b'', format="audio/mp3", loop=False)
+            st.caption("Audio component is displayed, simulating a synchronized audio track.")