"""
测试 Milvus Lite 向量检索实现

运行前确保：
1. pip install -r knowhub/requirements.txt
2. 设置环境变量 OPENROUTER_API_KEY
"""

import asyncio
import sys
from pathlib import Path

# 添加项目路径
sys.path.insert(0, str(Path(__file__).parent))

from knowhub.vector_store import MilvusStore
from knowhub.embeddings import get_embedding, get_embeddings_batch


async def test_basic():
    """测试基本功能"""
    print("=" * 60)
    print("测试 1: 初始化 Milvus Lite")
    print("=" * 60)

    store = MilvusStore(data_dir="./test_milvus_data")
    print(f"✓ Milvus Lite 初始化成功")
    print(f"  当前知识数量: {store.count()}")

    print("\n" + "=" * 60)
    print("测试 2: 生成 Embedding")
    print("=" * 60)

    text = "如何使用 Python 读取 PDF 文件"
    embedding = await get_embedding(text)
    print(f"✓ 单条 embedding 生成成功")
    print(f"  文本: {text}")
    print(f"  向量维度: {len(embedding)}")

    texts = ["测试文本1", "测试文本2", "测试文本3"]
    embeddings = await get_embeddings_batch(texts)
    print(f"✓ 批量 embedding 生成成功")
    print(f"  文本数量: {len(texts)}")
    print(f"  向量数量: {len(embeddings)}")

    print("\n" + "=" * 60)
    print("测试 3: 插入知识")
    print("=" * 60)

    import time
    knowledge = {
        "id": "test-001",
        "embedding": embedding,
        "message_id": "",
        "task": "读取 PDF 文件",
        "content": "使用 pymupdf 库可以高效读取 PDF 文件内容",
        "types": ["tool"],
        "tags": {"category": "file_processing"},
        "scopes": ["org:test"],
        "owner": "test_user",
        "resource_ids": [],
        "source": {"name": "test"},
        "eval": {"score": 4, "helpful": 0, "harmful": 0},
        "created_at": int(time.time()),
        "updated_at": int(time.time()),
    }

    store.insert(knowledge)
    print(f"✓ 知识插入成功")
    print(f"  ID: {knowledge['id']}")
    print(f"  当前知识数量: {store.count()}")

    print("\n" + "=" * 60)
    print("测试 4: 查询知识")
    print("=" * 60)

    result = store.get_by_id("test-001")
    print(f"✓ 按 ID 查询成功")
    print(f"  Task: {result['task']}")
    print(f"  Content: {result['content']}")

    print("\n" + "=" * 60)
    print("测试 5: 向量检索")
    print("=" * 60)

    query_text = "怎么处理 PDF"
    query_embedding = await get_embedding(query_text)
    results = store.search(query_embedding, limit=5)
    print(f"✓ 向量检索成功")
    print(f"  查询: {query_text}")
    print(f"  结果数量: {len(results)}")
    if results:
        print(f"  Top 1: {results[0]['task']}")

    print("\n" + "=" * 60)
    print("测试 6: 更新知识")
    print("=" * 60)

    store.update("test-001", {"content": "使用 pymupdf 库（推荐）或 PyPDF2 库读取 PDF"})
    updated = store.get_by_id("test-001")
    print(f"✓ 知识更新成功")
    print(f"  新内容: {updated['content']}")

    print("\n" + "=" * 60)
    print("测试 7: 删除知识")
    print("=" * 60)

    store.delete("test-001")
    deleted = store.get_by_id("test-001")
    print(f"✓ 知识删除成功")
    print(f"  删除后查询结果: {deleted}")
    print(f"  当前知识数量: {store.count()}")

    print("\n" + "=" * 60)
    print("所有测试通过！")
    print("=" * 60)


if __name__ == "__main__":
    asyncio.run(test_basic())