src/streamlit_app.py

=== 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.")