""" NanoBanana 工具测试脚本 测试场景： 1. 纯文本生成图像 2. 基于第一个测试生成的图像，转换为不同风格 """ import asyncio import sys from pathlib import Path from dotenv import load_dotenv # 添加项目根目录到 Python 路径 project_root = Path(__file__).parent.parent.parent sys.path.insert(0, str(project_root)) # 从 Agent 根目录加载 .env 文件 env_path = project_root / ".env" if env_path.exists(): load_dotenv(env_path) print(f"✅ 已加载环境变量: {env_path}") else: print(f"⚠️ 未找到 .env 文件: {env_path}") from agent.core.runner import AgentRunner, RunConfig from agent.trace.store import FileSystemTraceStore from agent.trace.models import Trace, Message from agent.llm.openrouter import create_openrouter_llm_call async def test_text_to_image(output_dir: Path) -> Path: """测试1: 纯文本生成图像 Returns: 生成的图片路径 """ print("\n" + "="*60) print("测试1: 纯文本生成图像") print("="*60) # 导入自定义工具 import examples.test_nanobanana.tool store = FileSystemTraceStore(base_path=".trace") llm_call = create_openrouter_llm_call(model="anthropic/claude-sonnet-4.5") runner = AgentRunner( trace_store=store, llm_call=llm_call, ) config = RunConfig( model="anthropic/claude-sonnet-4.5", temperature=0.3, max_iterations=10, ) # 使用绝对路径 output_path = output_dir / "cat.png" task = f""" 请使用 nanobanana 工具生成一张图片： - 内容：一只可爱的橙色小猫，坐在窗台上看着外面的雨 - 风格：水彩画风格 - 保存到：{output_path} 注意：路径必须使用绝对路径。 """ print(f"\n任务: 生成小猫图片") print(f"输出路径: {output_path}\n") # 将任务转换为消息格式 messages = [{"role": "user", "content": task}] generated_image = None try: async for item in runner.run(messages=messages, config=config): # 处理 Trace 对象（整体状态变化） if isinstance(item, Trace): if item.status == "running": print(f"[Trace] 开始: {item.trace_id[:8]}...") elif item.status == "completed": print(f"\n[Trace] ✅ 完成") print(f" - Total messages: {item.total_messages}") print(f" - Total tokens: {item.total_tokens}") print(f" - Total cost: ${item.total_cost:.4f}") if output_path.exists(): generated_image = output_path print(f" - 生成的图片: {generated_image}") elif item.status == "failed": print(f"\n[Trace] ❌ 失败: {item.error_message}") elif item.status == "stopped": print(f"\n[Trace] ⏸️ 已停止") # 处理 Message 对象（执行过程） elif isinstance(item, Message): if item.role == "assistant": content = item.content if isinstance(content, dict): text = content.get("text", "") tool_calls = content.get("tool_calls") if text and not tool_calls: # 纯文本回复（最终响应） print(f"\n[Response] {text}") elif tool_calls: # 工具调用 tool_names = [tc.get("function", {}).get("name") for tc in tool_calls] print(f"[Tool Call] {', '.join(tool_names)}") elif item.role == "tool": # 工具结果 if isinstance(item.content, dict): tool_name = item.content.get("tool_name", "unknown") print(f"[Tool Result] {tool_name}") except Exception as e: print(f"\n❌ 测试失败: {e}") import traceback traceback.print_exc() return generated_image async def test_image_to_image(input_image: Path, output_dir: Path): """测试2: 基于参考图像生成新图像 Args: input_image: 参考图像路径（来自测试1） output_dir: 输出目录 """ print("\n" + "="*60) print("测试2: 基于参考图像生成新图像") print("="*60) if not input_image or not input_image.exists(): print("⚠️ 跳过测试2: 测试1没有成功生成图片") return print(f"参考图像: {input_image}") # 导入自定义工具 import examples.test_nanobanana.tool store = FileSystemTraceStore(base_path=".trace") llm_call = create_openrouter_llm_call(model="anthropic/claude-sonnet-4.5") runner = AgentRunner( trace_store=store, llm_call=llm_call, ) config = RunConfig( model="anthropic/claude-sonnet-4.5", temperature=0.3, max_iterations=10, ) # 使用绝对路径 output_path = output_dir / "cat_oil_painting.png" task = f""" 请使用 nanobanana 工具，基于参考图像生成一张新图片： - 参考图像：{input_image} - 要求：保持小猫和窗台的元素，但改变风格为油画风格 - 保存到：{output_path} 注意：路径必须使用绝对路径。 """ print(f"\n任务: 将小猫图片转换为油画风格") print(f"输出路径: {output_path}\n") # 将任务转换为消息格式 messages = [{"role": "user", "content": task}] try: async for item in runner.run(messages=messages, config=config): # 处理 Trace 对象（整体状态变化） if isinstance(item, Trace): if item.status == "running": print(f"[Trace] 开始: {item.trace_id[:8]}...") elif item.status == "completed": print(f"\n[Trace] ✅ 完成") print(f" - Total messages: {item.total_messages}") print(f" - Total tokens: {item.total_tokens}") print(f" - Total cost: ${item.total_cost:.4f}") if output_path.exists(): print(f" - 生成的图片: {output_path}") elif item.status == "failed": print(f"\n[Trace] ❌ 失败: {item.error_message}") elif item.status == "stopped": print(f"\n[Trace] ⏸️ 已停止") # 处理 Message 对象（执行过程） elif isinstance(item, Message): if item.role == "assistant": content = item.content if isinstance(content, dict): text = content.get("text", "") tool_calls = content.get("tool_calls") if text and not tool_calls: # 纯文本回复（最终响应） print(f"\n[Response] {text}") elif tool_calls: # 工具调用 tool_names = [tc.get("function", {}).get("name") for tc in tool_calls] print(f"[Tool Call] {', '.join(tool_names)}") elif item.role == "tool": # 工具结果 if isinstance(item.content, dict): tool_name = item.content.get("tool_name", "unknown") print(f"[Tool Result] {tool_name}") except Exception as e: print(f"\n❌ 测试失败: {e}") import traceback traceback.print_exc() async def main(): """运行所有测试""" print("\n" + "="*60) print("NanoBanana 工具测试") print("="*60) # 创建输出目录（使用绝对路径） output_dir = Path(__file__).parent / "output" output_dir.mkdir(exist_ok=True) print(f"输出目录: {output_dir.absolute()}\n") try: # 测试1: 纯文本生成 generated_image = await test_text_to_image(output_dir) # 测试2: 图像转换（基于测试1的结果） if generated_image: await test_image_to_image(generated_image, output_dir) else: print("\n⚠️ 跳过测试2: 测试1未成功生成图片") print("\n" + "="*60) print("测试完成！") print("="*60) print(f"\n查看生成的图片:") if generated_image and generated_image.exists(): print(f" 1. {generated_image}") oil_painting = output_dir / "cat_oil_painting.png" if oil_painting.exists(): print(f" 2. {oil_painting}") except KeyboardInterrupt: print("\n\n⚠️ 测试被用户中断") except Exception as e: print(f"\n\n❌ 测试失败: {e}") import traceback traceback.print_exc() if __name__ == "__main__": asyncio.run(main())