集成:可观测性、Agent 与训练
最后验证:2026-03-12
目录
可观测性与代理
LiteLLM(代理)
import litellm
response = litellm.completion(
model="deepseek/deepseek-r1",
api_base="https://api.ppio.com/openai",
api_key="<YOUR_API_KEY>",
messages=[{"role": "user", "content": "Hello!"}]
)
Helicone(日志)
from openai import OpenAI
client = OpenAI(
base_url="https://api.ppio.com/openai",
api_key="<YOUR_API_KEY>",
default_headers={
"Helicone-Auth": "Bearer <HELICONE_KEY>",
}
)
Langfuse(链路追踪)
配置完成后,Langfuse 自动追踪兼容 OpenAI 的调用:
from langfuse.openai import openai
openai.api_base = "https://api.ppio.com/openai"
openai.api_key = "<YOUR_API_KEY>"
Portkey(网关)
from portkey_ai import Portkey
client = Portkey(
base_url="https://api.ppio.com/openai",
api_key="<YOUR_API_KEY>",
virtual_key="ppio-xxx"
)
AI Agent
Browser Use
import asyncio
from browser_use import Agent
from langchain_openai import ChatOpenAI
async def main():
llm = ChatOpenAI(
base_url="https://api.ppio.com/openai",
api_key="<YOUR_API_KEY>",
model="deepseek/deepseek-r1",
)
agent = Agent(task="Search for...", llm=llm)
await agent.run()
asyncio.run(main())
Skyvern
在环境变量中设置:
LLM_API_BASE=https://api.ppio.com/openai
LLM_API_KEY=<YOUR_API_KEY>
MODEL_NAME=deepseek/deepseek-r1
模型训练
Axolotl
在 Axolotl 配置文件中使用:
base_model: ppio/model-name
api_url: https://api.ppio.com/openai
Kohya SS GUI
在训练流水线中使用 PPIO 作为推理endpoint。