#!/usr/bin/env python3 """ 快速启动脚本 - 测试整个系统 """ import os import sys import json from pathlib import Path # 添加项目路径 SCRIPT_DIR = Path(__file__).parent REPO_ROOT = SCRIPT_DIR.parent sys.path.insert(0, str(REPO_ROOT)) from tools.asset_description_manager import AssetDescriptionManager from tools.asset_finder import AssetFinder def test_cache_manager(): """测试缓存管理器""" print("="*60) print("TEST 1: Asset Description Manager") print("="*60) manager = AssetDescriptionManager() # 测试保存和读取 test_uid = "test_model_uid_001" test_desc = "A beautiful wooden chair with armrests and cushion" print(f"✓ Created manager at: {manager.cache_file}") # 清除测试数据 if test_uid in manager.cache: del manager.cache[test_uid] manager._save_cache() print(f"\n1. Saving description...") manager.set_description(test_uid, test_desc, category="chair") print(f" ✓ Saved: {test_desc}") print(f"\n2. Reading description...") retrieved_desc = manager.get_description(test_uid) assert retrieved_desc == test_desc, "Description mismatch!" print(f" ✓ Retrieved: {retrieved_desc}") print(f"\n3. Checking if exists...") exists = manager.has_description(test_uid) assert exists, "Should exist!" print(f" ✓ Exists: {exists}") print(f"\n4. Stats...") stats = manager.get_stats() print(f" ✓ Total cached: {stats['total_assets']}") print(f" ✓ Cache file: {stats['cache_file']}") print("\n✓ Cache manager test PASSED\n") def test_asset_finder(): """测试资产查找器""" print("="*60) print("TEST 2: Asset Finder") print("="*60) asset_lib = "/home/v-meiszhang/amlt-project/InternScenes/data/asset_library" if not os.path.exists(asset_lib): print(f"✗ Asset library not found: {asset_lib}") print(" Skipping this test") return finder = AssetFinder(asset_lib) print(f"✓ Created finder for: {asset_lib}") # 测试查找 test_cases = [ "hssd-models/objects/8/8046bdb393aa1e9257f1e0611c91f89f28f37355", "partnet_mobility/7290", ] print(f"\nTesting asset lookup:") for uid in test_cases: print(f"\n Searching for: {uid}") info = finder.find_asset_info(uid) print(f" Found: {info['found']}") if info['found']: print(f" GLB: {os.path.basename(info['glb_path'])}") print(f" Category: {info['category']}") print("\n✓ Asset finder test PASSED\n") def test_layout_structure(): """测试layout文件结构""" print("="*60) print("TEST 3: Layout File Structure") print("="*60) layout_file = "/home/v-meiszhang/amlt-project/InternScenes/data/Layout_info/scannet/scene0000_01/layout_with_boundary.json" if not os.path.exists(layout_file): print(f"✗ Layout file not found: {layout_file}") return print(f"✓ Found layout file: {layout_file}") with open(layout_file, 'r') as f: layout = json.load(f) print(f"\n1. Layout structure:") print(f" ✓ Has 'instances': {'instances' in layout}") if "instances" in layout: num_instances = len(layout["instances"]) print(f" ✓ Number of instances: {num_instances}") # 统计model_uid model_uids = set() for inst in layout["instances"]: if "model_uid" in inst: model_uids.add(inst["model_uid"]) print(f" ✓ Unique model UIDs: {len(model_uids)}") # 显示样本 print(f"\n2. Sample instance:") if layout["instances"]: sample = layout["instances"][0] for key, value in sample.items(): if key != "pos" and key != "rot" and key != "size": print(f" {key}: {value}") # 检查是否已有description字段 has_desc = any("description" in inst for inst in layout["instances"]) print(f"\n3. Current status:") print(f" ✓ Already has description field: {has_desc}") print("\n✓ Layout structure test PASSED\n") def test_gpt_setup(): """测试Azure OpenAI API设置""" print("="*60) print("TEST 4: Azure GPT API Setup") print("="*60) try: from openai import AzureOpenAI from azure.identity import ChainedTokenCredential, AzureCliCredential, ManagedIdentityCredential, get_bearer_token_provider print("✓ Azure OpenAI packages are installed") # Try to initialize the client try: scope = "api://trapi/.default" credential = get_bearer_token_provider(ChainedTokenCredential( AzureCliCredential(), ManagedIdentityCredential(), ), scope) api_version = '2024-12-01-preview' deployment_name = 'gpt-4o_2024-11-20' instance = 'msra/shared' endpoint = f'https://trapi.research.microsoft.com/{instance}' client = AzureOpenAI( azure_endpoint=endpoint, azure_ad_token_provider=credential, api_version=api_version, ) print("✓ Azure OpenAI client created successfully") # Test simple API call print("\nTesting API connection...") response = client.chat.completions.create( model=deployment_name, messages=[ {"role": "user", "content": "Say 'test' in one word."} ], max_tokens=10 ) print(f"✓ API Response: {response.choices[0].message.content}") print("✓ Azure OpenAI API is working!") except Exception as e: print(f"⚠ Failed to initialize Azure OpenAI client: {e}") print(" Make sure you are logged in with: az login") except ImportError as e: print("✗ Azure OpenAI packages not installed") print(f" Error: {e}") print(" Install with: pip install openai azure-identity") except Exception as e: print(f"✗ Error: {e}") print() def test_render_script(): """测试render_to_image.py""" print("="*60) print("TEST 5: Render Script Availability") print("="*60) render_script = Path(__file__).parent.parent / "render_to_image.py" if render_script.exists(): print(f"✓ Found render script: {render_script}") # 尝试导入或检查语法 try: with open(render_script, 'r') as f: content = f.read(100) print(f"✓ Script is readable") except Exception as e: print(f"✗ Cannot read script: {e}") else: print(f"✗ render_to_image.py not found at: {render_script}") print() def main(): print("\n" + "="*60) print("ASSET DESCRIPTION SYSTEM - QUICK START TEST") print("="*60 + "\n") try: test_cache_manager() test_asset_finder() test_layout_structure() test_gpt_setup() test_render_script() print("="*60) print("ALL TESTS COMPLETED") print("="*60) print("\nNext steps:") print("1. Make sure you are logged in with: az login") print("2. Run: python tools/process_asset_descriptions.py --dry-run") print("3. Then: python tools/process_asset_descriptions.py") print() except Exception as e: print(f"\n✗ Test failed with error: {e}") import traceback traceback.print_exc() sys.exit(1) if __name__ == "__main__": main()