This library contains modified versions of the OpenTelemetry instrumentaions for openai and bedrock, designed to simplify LLM application development and production tracing and debugging.
pip install llm-tracekit[openai]
pip install llm-tracekit[bedrock]
This section describes how to setup up instrumentation for OpenAI or Bedrock. The examples will use the OpenAI instrumentation, but the usage is identical for both instrumentations, so you can simple replace OpenAIInstrumentor
with BedrockInstrumentor
if you are using Bedrock.
You can use the setup_export_to_coralogix
function to setup tracing and export traces to Coralogix
from llm_tracekit import setup_export_to_coralogix
setup_export_to_coralogix(
service_name="ai-service",
application_name="ai-application",
subsystem_name="ai-subsystem",
capture_content=True,
)
Alternatively, you can set up tracing manually:
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
tracer_provider = TracerProvider(
resource=Resource.create({SERVICE_NAME: "ai-service"}),
)
exporter = OTLPSpanExporter()
span_processor = SimpleSpanProcessor(exporter)
tracer_provider.add_span_processor(span_processor)
trace.set_tracer_provider(tracer_provider)
To instrument all clients, call the instrument
method
from llm_tracekit import OpenAIInstrumentor
OpenAIInstrumentor().instrument()
Message content such as the contents of the prompt, completion, function arguments and return values are not captured by default. To capture message content as span attributes, do one of the following:
- Pass
capture_content=True
when callingsetup_export_to_coralogix
- Set the environment variable
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT
totrue
Most Coralogix AI evaluations will not work without message contents, so it is highly recommended to enable capturing.
To uninstrument clients, call the uninstrument
method:
OpenAIInstrumentor().uninstrument()
from llm_tracekit import OpenAIInstrumentor, setup_export_to_coralogix
from openai import OpenAI
# Optional: Configure sending spans to Coralogix
# Reads Coralogix connection details from the following environment variables:
# - CX_TOKEN
# - CX_ENDPOINT
setup_export_to_coralogix(
service_name="ai-service",
application_name="ai-application",
subsystem_name="ai-subsystem",
capture_content=True,
)
# Activate instrumentation
OpenAIInstrumentor().instrument()
# Example OpenAI Usage
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "user", "content": "Write a short poem on open telemetry."},
],
)
- The
user
parameter in the OpenAI Chat Completions API is now recorded in the span as thegen_ai.openai.request.user
attribute - The
tools
parameter in the OpenAI Chat Completions API is now recorded in the span as thegen_ai.openai.request.tools
attributes. - User prompts and model responses are captured as span attributes instead of log events (see Semantic Conventions below)
Attribute | Type | Description | Examples |
---|---|---|---|
gen_ai.prompt.<message_number>.role |
string | Role of message author for user message <message_number> | system , user , assistant , tool |
gen_ai.prompt.<message_number>.content |
string | Contents of user message <message_number> | What's the weather in Paris? |
gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.id |
string | ID of tool call in user message <message_number> | call_O8NOz8VlxosSASEsOY7LDUcP |
gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.type |
string | Type of tool call in user message <message_number> | function |
gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.function.name |
string | The name of the function used in tool call within user message <message_number> | get_current_weather |
gen_ai.prompt.<message_number>.tool_calls.<tool_call_number>.function.arguments |
string | Arguments passed to the function used in tool call within user message <message_number> | {"location": "Seattle, WA"} |
gen_ai.prompt.<message_number>.tool_call_id |
string | Tool call ID in user message <message_number> | call_mszuSIzqtI65i1wAUOE8w5H4 |
gen_ai.completion.<choice_number>.role |
string | Role of message author for choice <choice_number> in model response | assistant |
gen_ai.completion.<choice_number>.finish_reason |
string | Finish reason for choice <choice_number> in model response | stop , tool_calls , error |
gen_ai.completion.<choice_number>.content |
string | Contents of choice <choice_number> in model response | The weather in Paris is rainy and overcast, with temperatures around 57°F |
gen_ai.completion.<choice_number>.tool_calls.<tool_call_number >.id |
string | ID of tool call in choice <choice_number> | call_O8NOz8VlxosSASEsOY7LDUcP |
gen_ai.completion.<choice_number>.tool_calls.<tool_call_number >.type |
string | Type of tool call in choice <choice_number> | function |
gen_ai.completion.<choice_number>.tool_calls.<tool_call_number >.function.name |
string | The name of the function used in tool call within choice <choice_number> | get_current_weather |
gen_ai.completion.<choice_number>.tool_calls.<tool_call_number >.function.arguments |
string | Arguments passed to the function used in tool call within choice <choice_number> | {"location": "Seattle, WA"} |
Attribute | Type | Description | Examples |
---|---|---|---|
gen_ai.openai.request.user |
string | A unique identifier representing the end-user | [email protected] |
gen_ai.openai.request.tools.<tool_number>.type |
string | Type of tool entry in tools list | function |
gen_ai.openai.request.tools.<tool_number>.function.name |
string | The name of the function to use in tool calls | get_current_weather |
gen_ai.openai.request.tools.<tool_number>.function.description |
string | Description of the function | Get the current weather in a given location |
gen_ai.openai.request.tools.<tool_number>.function.parameters |
string | JSON describing the schema of the function parameters | {"type": "object", "properties": {"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}, "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}}, "required": ["location"]} |
Attribute | Type | Description | Examples |
---|---|---|---|
gen_ai.bedrock.agent_alias.id |
string | The ID of the agent-alias in an invoke_agent call |
[email protected] |
gen_ai.bedrock.request.tools.<tool_number>.function.name |
string | The name of the function to use in tool calls | get_current_weather |
gen_ai.bedrock.request.tools.<tool_number>.function.description |
string | Description of the function | Get the current weather in a given location |
gen_ai.bedrock.request.tools.<tool_number>.function.parameters |
string | JSON describing the schema of the function parameters | {"type": "object", "properties": {"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}, "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}}, "required": ["location"]} |