respan-instrumentation-openai 1.2.1

Respan instrumentation plugin for direct OpenAI SDK usage (native, Traceloop-free)

respan-instrumentation-openai

Respan instrumentation plugin for direct OpenAI SDK usage. A native, Traceloop-free instrumentation: it patches the OpenAI SDK directly and emits Respan's own LLM span conventions (llm.request.type, gen_ai.*, traceloop.entity.*, respan.entity.log_type), so chat, responses, completions, and embeddings calls are traced as real LLM calls with token/cost roll-up. Covers sync, async, and streaming.

Configuration

1. Install

pip install respan-instrumentation-openai

2. Set Environment Variables

Variable	Required	Description
RESPAN_API_KEY	Yes	Your Respan API key. Authenticates both proxy and tracing.
RESPAN_BASE_URL	No	Defaults to https://api.respan.ai.

All vendor-specific variables (e.g. OPENAI_API_KEY) are derived from these in your application code.

Quickstart

3. Run Script

import os
from openai import OpenAI
from respan import Respan
from respan_instrumentation_openai import OpenAIInstrumentor

respan_api_key = os.environ["RESPAN_API_KEY"]
respan_base_url = os.getenv("RESPAN_BASE_URL", "https://api.respan.ai")

respan = Respan(
    api_key=respan_api_key,
    base_url=respan_base_url,
    instrumentations=[OpenAIInstrumentor()],
)

client = OpenAI(
    api_key=respan_api_key,
    base_url=f"{respan_base_url}/api/openai",
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

respan.flush()

4. View Dashboard

After running the script, traces appear on your Respan dashboard.

Further Reading

See the examples/openai-sdk/ directory for runnable examples including streaming, tool use, Responses API, and gateway routing.