initialized

Dockerfile

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+# Use an official Python runtime as a parent image
+FROM python:3.9-slim
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the backend requirements file and install dependencies
+COPY backend/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the backend and frontend code into the container
+COPY backend/ /app/backend
+COPY frontend/ /app/frontend
+
+# Expose the port the app runs on
+EXPOSE 7860
+
+# Run the application
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

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+---
+title: VEO3 Video Generator
+emoji: 📹
+colorFrom: blue
+colorTo: green
+sdk: docker
+app_port: 7860
+---
+
+# VEO3 Video Generator
+
+This is a simple web application to generate videos using Google's VEO3 models via a Vertex Express Mode Key loophole.
+
+## How to use
+
+1.  Enter your Vertex Express Key.
+2.  Enter a text prompt.
+3.  Optionally, upload an image or video.
+4.  Select the desired parameters.
+5.  Click "Generate Video".

backend/main.py

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+import uvicorn
+from fastapi import FastAPI, File, UploadFile, Form, HTTPException
+from fastapi.responses import FileResponse
+from fastapi.staticfiles import StaticFiles
+from typing import Optional
+import services.vertex_service as vertex_service
+import services.video_service as video_service
+import os
+
+app = FastAPI()
+
+app.mount("/", StaticFiles(directory="frontend", html=True), name="static")
+
+@app.post("/api/generate_video")
+async def generate_video(
+    api_key: str = Form(...),
+    prompt: str = Form(...),
+    model: str = Form(...),
+    aspect_ratio: str = Form(...),
+    duration: int = Form(...),
+    resolution: str = Form(...),
+    generate_audio: bool = Form(...),
+    image: Optional[UploadFile] = File(None),
+    video: Optional[UploadFile] = File(None),
+):
+    try:
+        project_id = await vertex_service.get_project_id(api_key)
+        
+        params = {
+            "prompt": prompt,
+            "model": model,
+            "aspectRatio": aspect_ratio,
+            "durationSeconds": duration,
+            "resolution": resolution,
+            "generateAudio": generate_audio,
+        }
+
+        if image:
+            params["image"] = await image.read()
+            params["image_mime_type"] = image.content_type
+        
+        if video:
+            params["video"] = await video.read()
+            params["video_mime_type"] = video.content_type
+
+        operation_name = await vertex_service.start_video_generation(project_id, api_key, params)
+        video_data = await vertex_service.poll_video_status(operation_name, api_key)
+        
+        video_path = await video_service.save_video(video_data)
+        
+        return {"video_url": f"/api/video/{os.path.basename(video_path)}"}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/api/video/{video_id}")
+async def get_video(video_id: str):
+    video_path = os.path.join(video_service.VIDEO_DIR, video_id)
+    if os.path.exists(video_path):
+        return FileResponse(video_path)
+    raise HTTPException(status_code=404, detail="Video not found")
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)

backend/requirements.txt

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+fastapi
+uvicorn[standard]
+python-multipart
+requests
+aiohttp
+python-dotenv

backend/services/vertex_service.py

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+import aiohttp
+import asyncio
+import base64
+import re
+from typing import Dict, Any
+
+# A simple in-memory cache for project IDs
+project_id_cache = {}
+
+async def get_project_id(api_key: str) -> str:
+    if api_key in project_id_cache:
+        return project_id_cache[api_key]
+
+    url = f"https://aiplatform.googleapis.com/v1/publishers/google/models/gemini-2.6:streamGenerateContent?key={api_key}"
+    headers = {"Content-Type": "application/json"}
+    data = {}
+
+    async with aiohttp.ClientSession() as session:
+        async with session.post(url, headers=headers, json=data) as response:
+            error_data = await response.json()
+            message = error_data[0]["error"]["message"]
+            match = re.search(r"projects/(\d+)/", message)
+            if match:
+                project_id = match.group(1)
+                project_id_cache[api_key] = project_id
+                return project_id
+            else:
+                raise Exception("Could not extract project ID")
+
+async def start_video_generation(project_id: str, api_key: str, params: Dict[str, Any]) -> str:
+    location = "us-central1" # Or make this a parameter
+    model_id = params.pop("model")
+    url = f"https://{location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{location}/publishers/google/models/{model_id}:predictLongRunning?key={api_key}"
+    
+    instances = [{"prompt": params.get("prompt")}]
+    if "image" in params:
+        instances[0]["image"] = {
+            "bytesBase64Encoded": base64.b64encode(params["image"]).decode("utf-8"),
+            "mimeType": params["image_mime_type"]
+        }
+    if "video" in params:
+        instances[0]["video"] = {
+            "bytesBase64Encoded": base64.b64encode(params["video"]).decode("utf-8"),
+            "mimeType": params["video_mime_type"]
+        }
+        
+    payload = {
+        "instances": instances,
+        "parameters": {
+            "aspectRatio": params.get("aspectRatio"),
+            "durationSeconds": params.get("durationSeconds"),
+            "resolution": params.get("resolution"),
+            "generateAudio": params.get("generateAudio"),
+        }
+    }
+
+    async with aiohttp.ClientSession() as session:
+        async with session.post(url, json=payload) as response:
+            response.raise_for_status()
+            data = await response.json()
+            return data["name"]
+
+async def poll_video_status(operation_name: str, api_key: str) -> Dict[str, Any]:
+    location = "us-central1"
+    model_id = operation_name.split("/")[5]
+    url = f"https://{location}-aiplatform.googleapis.com/v1/projects/{operation_name.split('/')[1]}/locations/{location}/publishers/google/models/{model_id}:fetchPredictOperation?key={api_key}"
+    
+    payload = {"operationName": operation_name}
+
+    async with aiohttp.ClientSession() as session:
+        while True:
+            async with session.post(url, json=payload) as response:
+                response.raise_for_status()
+                data = await response.json()
+                if data.get("done"):
+                    return data["response"]
+            await asyncio.sleep(5) # Poll every 5 seconds

backend/services/video_service.py

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+import os
+import uuid
+import base64
+import aiohttp
+from typing import Dict, Any
+
+VIDEO_DIR = "generated_videos"
+os.makedirs(VIDEO_DIR, exist_ok=True)
+
+async def save_video(video_data: Dict[str, Any]) -> str:
+    video_filename = f"{uuid.uuid4()}.mp4"
+    video_path = os.path.join(VIDEO_DIR, video_filename)
+
+    if "gcsUri" in video_data["videos"][0]:
+        gcs_uri = video_data["videos"][0]["gcsUri"]
+        async with aiohttp.ClientSession() as session:
+            async with session.get(gcs_uri) as response:
+                response.raise_for_status()
+                with open(video_path, "wb") as f:
+                    f.write(await response.read())
+    elif "bytesBase64Encoded" in video_data["videos"][0]:
+        video_bytes = base64.b64decode(video_data["videos"][0]["bytesBase64Encoded"])
+        with open(video_path, "wb") as f:
+            f.write(video_bytes)
+    else:
+        raise Exception("No video data found in response")
+
+    return video_path

frontend/app.js

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+document.getElementById("video-form").addEventListener("submit", async (event) => {
+    event.preventDefault();
+
+    const form = event.target;
+    const formData = new FormData();
+    
+    formData.append("api_key", form["api-key"].value);
+    formData.append("prompt", form["prompt"].value);
+    formData.append("model", form["model"].value);
+    formData.append("aspect_ratio", form["aspect-ratio"].value);
+    formData.append("duration", form["duration"].value);
+    formData.append("resolution", form["resolution"].value);
+    formData.append("generate_audio", form["generate-audio"].checked);
+
+    const imageFile = form["image-prompt"].files[0];
+    if (imageFile) {
+        formData.append("image", imageFile);
+    }
+
+    const videoFile = form["video-prompt"].files[0];
+    if (videoFile) {
+        formData.append("video", videoFile);
+    }
+
+    const loader = document.getElementById("loader");
+    const videoElement = document.getElementById("generated-video");
+    const errorContainer = document.getElementById("error-container");
+
+    loader.classList.remove("hidden");
+    videoElement.style.display = "none";
+    errorContainer.classList.add("hidden");
+
+    try {
+        const response = await fetch("/api/generate_video", {
+            method: "POST",
+            body: formData,
+        });
+
+        if (!response.ok) {
+            const errorData = await response.json();
+            throw new Error(errorData.detail || "An unknown error occurred");
+        }
+
+        const data = await response.json();
+        videoElement.src = data.video_url;
+        videoElement.style.display = "block";
+    } catch (error) {
+        errorContainer.textContent = error.message;
+        errorContainer.classList.remove("hidden");
+    } finally {
+        loader.classList.add("hidden");
+    }
+});

frontend/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>VEO3 Video Generator</title>
+    <link rel="stylesheet" href="/style.css">
+</head>
+<body>
+    <header>
+        <h1>VEO3 Video Generator</h1>
+    </header>
+    <main>
+        <form id="video-form">
+            <label for="api-key">Vertex Express Key:</label>
+            <input type="text" id="api-key" name="api-key" required>
+
+            <label for="prompt">Prompt:</label>
+            <textarea id="prompt" name="prompt" rows="4" required></textarea>
+
+            <label for="model">Model:</label>
+            <select id="model" name="model">
+                <option value="veo-2.0-generate-001">veo-2.0-generate-001</option>
+                <option value="veo-3.0-generate-001">veo-3.0-generate-001</option>
+                <option value="veo-3.0-fast-generate-001">veo-3.0-fast-generate-001</option>
+                <option value="veo-3.0-generate-preview" selected>veo-3.0-generate-preview</option>
+                <option value="veo-3.0-fast-generate-preview">veo-3.0-fast-generate-preview</option>
+            </select>
+
+            <label for="aspect-ratio">Aspect Ratio:</label>
+            <select id="aspect-ratio" name="aspect-ratio">
+                <option value="16:9">16:9</option>
+                <option value="9:16">9:16</option>
+            </select>
+
+            <label for="duration">Duration (seconds):</label>
+            <input type="number" id="duration" name="duration" value="8" min="5" max="8">
+
+            <label for="resolution">Resolution:</label>
+            <select id="resolution" name="resolution">
+                <option value="720p">720p</option>
+                <option value="1080p">1080p</option>
+            </select>
+
+            <label for="generate-audio">Generate Audio:</label>
+            <input type="checkbox" id="generate-audio" name="generate-audio" checked>
+
+            <label for="image-prompt">Image Prompt:</label>
+            <input type="file" id="image-prompt" name="image-prompt" accept="image/jpeg,image/png">
+
+            <label for="video-prompt">Video Prompt:</label>
+            <input type="file" id="video-prompt" name="video-prompt" accept="video/mp4">
+
+            <button type="submit">Generate Video</button>
+        </form>
+
+        <div id="video-container">
+            <div id="loader" class="hidden"></div>
+            <video id="generated-video" controls></video>
+            <div id="error-container" class="hidden"></div>
+        </div>
+    </main>
+    <script src="/app.js"></script>
+</body>
+</html>

frontend/style.css

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+body {
+    font-family: sans-serif;
+    margin: 0;
+    background-color: #f4f4f4;
+    color: #333;
+}
+
+header {
+    background-color: #333;
+    color: #fff;
+    padding: 1rem;
+    text-align: center;
+}
+
+main {
+    max-width: 800px;
+    margin: 2rem auto;
+    padding: 1rem;
+    background-color: #fff;
+    border-radius: 5px;
+}
+
+form {
+    display: flex;
+    flex-direction: column;
+    gap: 1rem;
+}
+
+label {
+    font-weight: bold;
+}
+
+input[type="text"],
+textarea,
+select {
+    padding: 0.5rem;
+    border: 1px solid #ccc;
+    border-radius: 3px;
+}
+
+button {
+    padding: 0.75rem;
+    background-color: #333;
+    color: #fff;
+    border: none;
+    border-radius: 3px;
+    cursor: pointer;
+}
+
+button:hover {
+    background-color: #555;
+}
+
+#video-container {
+    margin-top: 2rem;
+    text-align: center;
+}
+
+#generated-video {
+    max-width: 100%;
+    display: none;
+}
+
+.hidden {
+    display: none;
+}
+
+#loader {
+    border: 8px solid #f3f3f3;
+    border-top: 8px solid #3498db;
+    border-radius: 50%;
+    width: 50px;
+    height: 50px;
+    animation: spin 1s linear infinite;
+    margin: 0 auto;
+}
+
+@keyframes spin {
+    0% { transform: rotate(0deg); }
+    100% { transform: rotate(360deg); }
+}
+
+#error-container {
+    color: red;
+    margin-top: 1rem;
+}