Observability SDK for AI agents — traces, costs, and alerts in 3 lines of code.
Project description
Vantra Python SDK
Observability for AI agents — traces, costs, and alerts in 3 lines of code.
Install
pip install vantra
Quickstart
import vantra
vantra.init(
api_key="van_live_...",
project="my-agent"
)
@vantra.trace
def run_agent(message: str):
# your existing code — completely untouched
return agent.run(message)
Every call to run_agent appears as a trace in your Vantra dashboard with timing, token usage, cost, and status.
Nested spans
@vantra.trace
def run_agent(message: str):
with vantra.span("search", kind="tool") as span:
results = search(message)
span.set_output({"results": results})
with vantra.span("generate", kind="llm"):
return llm.chat(message, context=results)
Auto-patching
Vantra automatically captures OpenAI and Anthropic calls after init() — no extra code needed.
import vantra
import openai
vantra.init(api_key="van_live_...", project="my-agent")
client = openai.OpenAI()
@vantra.trace
def ask(question: str) -> str:
# This call is captured automatically
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": question}]
)
return response.choices[0].message.content
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