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| import gradio as gr | |
| import requests | |
| import base64 | |
| import time | |
| # --- 核心配置 --- | |
| API_KEY = "zz2026022" | |
| # 根据截图,Base URL 是 http://<IP>:<端口>/flow/v1 | |
| BASE_URL = "http://154.40.59.124:8000/flow/v1" | |
| def encode_image(image_path): | |
| """将本地图片路径转换为 Base64 字符串""" | |
| if not image_path: | |
| return None | |
| with open(image_path, "rb") as f: | |
| encoded = base64.b64encode(f.read()).decode('utf-8') | |
| return f"data:image/png;base64,{encoded}" | |
| def generate_video_task(prompt, start_img_path, end_img_path): | |
| if not start_img_path: | |
| return None, "错误:请至少上传起始帧图片。" | |
| headers = { | |
| "Authorization": f"Bearer {API_KEY}", # | |
| "Content-Type": "application/json" | |
| } | |
| # 1. 转换图片为 Base64 | |
| start_b64 = encode_image(start_img_path) | |
| end_b64 = encode_image(end_img_path) if end_img_path else None | |
| # 2. 构造符合 /v1/videos 接口要求的 payload | |
| input_refs = [start_b64] | |
| if end_b64: | |
| input_refs.append(end_b64) # 传入 [起始帧, 结束帧] 列表 | |
| payload = { | |
| "prompt": prompt if prompt else "Generate transition video", # | |
| "model": "veo_3_1", # 使用文档指定的模型名称 | |
| "input_reference": input_refs # 接口参数名为 input_reference | |
| } | |
| try: | |
| # 3. 提交生成任务 (POST /v1/videos) | |
| response = requests.post(f"{BASE_URL}/videos", json=payload, headers=headers) | |
| res_data = response.json() | |
| if response.status_code != 200: | |
| return None, f"任务提交失败: {res_data}" | |
| video_id = res_data.get("id") | |
| if not video_id: | |
| return None, "未获取到任务 ID,请检查接口返回格式。" | |
| # 4. 轮询视频生成状态 (GET /v1/videos/{video_id}) | |
| status_url = f"{BASE_URL}/videos/{video_id}" | |
| for _ in range(60): # 最多等待 300 秒 | |
| time.sleep(5) | |
| status_res = requests.get(status_url, headers=headers) | |
| status_data = status_res.json() | |
| # 这里的状态判断逻辑需根据您的 API 实际返回字段名进行适配(如 status 或 state) | |
| status = status_data.get("status") | |
| if status == "completed" or status == "succeeded": | |
| return status_data.get("url"), f"生成成功!ID: {video_id}" | |
| elif status == "failed": | |
| return None, f"视频生成失败: {status_data.get('error')}" | |
| print(f"正在生成中... 状态: {status}") | |
| return None, "任务超时,请稍后重试。" | |
| except Exception as e: | |
| return None, f"程序异常: {str(e)}" | |
| # --- Gradio 交互界面 --- | |
| with gr.Blocks(title="首尾帧视频生成测试") as demo: | |
| gr.Markdown("## 🎬 视频接口生成测试 (/v1/videos)") | |
| gr.Markdown("当前使用模型:`veo_3_1`") | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt_input = gr.Textbox(label="视频提示词 (Prompt)", value="画小猫") # | |
| start_img = gr.Image(label="起始帧 (Start Frame)", type="filepath") | |
| end_img = gr.Image(label="结束帧 (End Frame)", type="filepath") | |
| btn = gr.Button("提交视频生成任务", variant="primary") | |
| with gr.Column(): | |
| video_out = gr.Video(label="生成结果") | |
| info_out = gr.Textbox(label="任务状态信息", interactive=False) | |
| btn.click( | |
| fn=generate_video_task, | |
| inputs=[prompt_input, start_img, end_img], | |
| outputs=[video_out, info_out] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |