pisama-auto 0.1.0

Zero-code auto-instrumentation for LLM applications — adds Pisama failure detection with one line

pisama-auto

Zero-code auto-instrumentation for LLM applications. Add Pisama failure detection with one line.

Quick Start

pip install pisama-auto

import pisama_auto
pisama_auto.init()  # traces locally; set PISAMA_API_KEY + PISAMA_ENDPOINT to export

# All subsequent LLM calls are automatically traced
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)
# ^ This call is automatically traced (and sent to Pisama if endpoint is configured)

Supported Libraries

Library	Status	What's Traced
anthropic	GA	messages.create(), messages.stream()
openai	GA	chat.completions.create()

How It Works

1. pisama_auto.init() sets up an OpenTelemetry tracer that exports to Pisama
2. It then patches supported LLM libraries to emit spans with gen_ai.* semantic conventions
3. Pisama's detection engine analyzes the traces for 44 failure modes
4. Results appear in your Pisama dashboard

Configuration

pisama_auto.init(
    api_key="ps_...",                    # or set PISAMA_API_KEY env var
    endpoint="https://your-instance/api/v1/traces/ingest",  # or PISAMA_ENDPOINT env var
    service_name="my-agent",             # OTEL service name
    auto_patch=True,                     # auto-patch all detected libraries
)

Without an endpoint, traces are generated locally but not exported. Set PISAMA_ENDPOINT to send them to the Pisama platform.

Selective Patching

import pisama_auto
pisama_auto.init(auto_patch=False)  # don't auto-patch

from pisama_auto.patches import patch
patch("anthropic")  # only patch anthropic