capybara-sdk
Emit OpenTelemetry gen_ai.* traces to a local capybara
trace debugger. Import name is capybara.
pip install capybara-sdk
import capybara
from pydantic import BaseModel
capybara.init() # export to a local capybara on 127.0.0.1:4318
class Price(BaseModel):
price: float
currency: str
capybara.schema("lookup_price", Price) # declared beats learned
@capybara.trace(tool="lookup_price")
def lookup_price(sku: str) -> dict:
return {"price": 42.0, "currency": "USD"}
init() reuses a TracerProvider you already configured, so OpenInference or
OpenLLMetry instrumentors covering OpenAI, Anthropic, or LangChain keep working;
capybara only adds an OTLP exporter and the schema processor.
@capybara.trace wraps un-instrumented functions. A bare @capybara.trace
records a tool span named after the function; kind="agent" or kind="llm"
records other span kinds. capybara.schema(tool, model) attaches a Pydantic
model's JSON Schema to that tool's spans so capybara reports contract drift on
the first violating call.
Sync and async functions are both supported.
capybara.replay is invoked by the binary, not by you: pressing r in the TUI
re-executes the recorded process, serving the recorded model responses and tool
outputs so nothing touches the network. A call that is not in the recording
stops the replay instead of running live; only model calls made after an edited
value has been served are allowed to diverge.
1 maintainer
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