splunk-otel-util-genai-translator-openlit 0.1.1

openlit -> GenAI translator emitter for OpenTelemetry GenAI

This package automatically translates openlit sdk instrumented spans into OpenTelemetry GenAI semantic conventions. It intercepts spans with `gen_ai.*` openlit specific attributes and creates corresponding spans with gen_ai.* semantic convention compliant attributes, enabling seamless integration between openlit instrumentation and GenAI observability tools.

Mapping Table

Old Key (OpenLit)	New Key (OTel SemConv)
gen_ai.completion.0.content	gen_ai.output.messages
gen_ai.prompt.0.content	gen_ai.input.messages
gen_ai.prompt	gen_ai.input.messages
gen_ai.completion	gen_ai.output.messages
gen_ai.content.prompt	gen_ai.input.messages
gen_ai.content.completion	gen_ai.output.messages
gen_ai.request.embedding_dimension	gen_ai.embeddings.dimension.count
gen_ai.token.usage.input	gen_ai.usage.input_tokens
gen_ai.token.usage.output	gen_ai.usage.output_tokens
gen_ai.llm.provider	gen_ai.provider.name
gen_ai.llm.model	gen_ai.request.model
gen_ai.llm.temperature	gen_ai.request.temperature
gen_ai.llm.max_tokens	gen_ai.request.max_tokens
gen_ai.llm.top_p	gen_ai.request.top_p
gen_ai.operation.type	gen_ai.operation.name
gen_ai.output_messages	gen_ai.output.messages
gen_ai.session.id	gen_ai.conversation.id
gen_ai.openai.thread.id	gen_ai.conversation.id
gen_ai.tool.args	gen_ai.tool.call.arguments
gen_ai.tool.result	gen_ai.tool.call.result
gen_ai.vectordb.name	db.system.name
gen_ai.vectordb.search.query	db.query.text
gen_ai.vectordb.search.results_count	db.response.returned_rows

Installation

pip install opentelemetry-util-genai-openlit-translator

Quick Start (Automatic Registration)

The easiest way to use the translator is to simply import it - no manual setup required!

from openai import OpenAI
import openlit
from dotenv import load_dotenv
import os
import traceback

load_dotenv()

try:
   openlit.init(otlp_endpoint="http://0.0.0.0:4318")

   client = OpenAI(
      api_key=os.getenv("OPENAI_API_KEY")
   )

   chat_completion = client.chat.completions.create(
      messages=[
            {
               "role": "user",
               "content": "What is LLM Observability?",
            }
      ],
      model="gpt-3.5-turbo",
   )
   print("response:", chat_completion.choices[0].message.content)
except Exception as e:
   print(f"An error occurred: {e}")
   traceback.print_exc()

Tests

pytest util/opentelemetry-util-genai-openlit-translator/tests