OpenViking 火山引擎配置完成摘要

{
  "storage": {
    "workspace": "D:/openviking_workspace"
  },
  "log": {
    "level": "INFO",
    "output": "stdout"
  },
  "embedding": {
    "dense": {
      "backend": "volcengine",
      "api_key": "YOUR_API_KEY_HERE",
      "model": "doubao-embedding-vision-251215",
      "api_base": "https://ark.cn-beijing.volces.com/api/coding/v3",
      "dimension": 1024,
      "input": "multimodal"
    }
  },
  "vlm": {
    "backend": "volcengine",
    "api_key": "YOUR_API_KEY_HERE",
    "model": "doubao-seed-2-0-pro-260215",
    "api_base": "https://ark.cn-beijing.volces.com/api/coding/v3",
    "temperature": 0.1,
    "max_retries": 3
  }
}

python3 configure_openviking.py

python3 verify_openviking_config.py

python3 openviking_usage_examples.py

import openviking as ov

# 初始化客户端
client = ov.OpenViking(path="./data")
client.initialize()

# 添加资源
add_result = client.add_resource(
    path="https://raw.githubusercontent.com/volcengine/OpenViking/refs/heads/main/README.md"
)
root_uri = add_result['root_uri']

# 查看目录结构
ls_result = client.ls(root_uri)
print(f"Directory structure:\n{ls_result}\n")

# 等待语义处理
print("Wait for semantic processing...")
client.wait_processed()

# 获取摘要和概览
abstract = client.abstract(root_uri)
overview = client.overview(root_uri)

print(f"L0 Abstract:\n{abstract}\n")
print(f"L1 Overview:\n{overview[:500]}...\n")

# 语义搜索
results = client.find("what is openviking", target_uri=root_uri)
print(f"Search results:\n{results}\n")

# 断开连接
client.disconnect()