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Integrations

Dual Export

Introspection is designed to work alongside tools like Logfire, Langfuse, Braintrust, and Arize / Phoenix.

Use dual export when you already have another backend in place and want Introspection without replacing it immediately.

Logfire

This is the recommended default integration path for Python applications.

Basic Pattern

from introspection_sdk import IntrospectionSpanProcessor
import logfire
 
logfire.configure(
    additional_span_processors=[IntrospectionSpanProcessor()],
)

More Complete Example

import logfire
import openai
from introspection_sdk import IntrospectionSpanProcessor
 
logfire.configure(
    send_to_logfire="if-token-present",
    additional_span_processors=[
        IntrospectionSpanProcessor(service_name="logfire-openai-example")
    ],
)
 
logfire.instrument_openai()
 
client = openai.OpenAI()
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
 
logfire.shutdown()

Langfuse

Attach both exporters or processors to the same tracing pipeline.

import base64
import os
import openai
from langfuse import get_client
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from openinference.instrumentation.openai import OpenAIInstrumentor
from introspection_sdk import IntrospectionSpanProcessor
 
LANGFUSE_AUTH = base64.b64encode(
    f"{os.environ['LANGFUSE_PUBLIC_KEY']}:{os.environ['LANGFUSE_SECRET_KEY']}".encode()
).decode()
 
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = (
    os.environ.get("LANGFUSE_BASE_URL", "https://cloud.langfuse.com") + "/api/public/otel"
)
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"
 
provider = TracerProvider()
get_client()
 
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
provider.add_span_processor(IntrospectionSpanProcessor())
 
trace.set_tracer_provider(provider)
OpenAIInstrumentor().instrument(tracer_provider=provider)

Braintrust

Use this when you already send traces to Braintrust and want to add Introspection alongside it.

from opentelemetry.sdk.trace import TracerProvider
from introspection_sdk import IntrospectionSpanProcessor
from introspection_sdk.config import AdvancedOptions
 
provider = TracerProvider()
 
braintrust_processor = IntrospectionSpanProcessor(
    token=os.environ["BRAINTRUST_API_KEY"],
    advanced=AdvancedOptions(
        base_url="https://api.braintrust.dev/otel/v1/traces",
        additional_headers={"x-bt-parent": "project_name:my-project"},
    ),
)
provider.add_span_processor(braintrust_processor)
provider.add_span_processor(IntrospectionSpanProcessor())

LangSmith

Use this when you already send traces to LangSmith and want to add Introspection alongside it.

With OpenAI Agents, both LangSmith and Introspection implement the TracingProcessor interface — register both and traces go to both in parallel.

from agents import Agent, Runner, set_trace_processors
from langsmith.integrations.openai_agents_sdk import OpenAIAgentsTracingProcessor
from introspection_sdk import IntrospectionTracingProcessor
 
langsmith_processor = OpenAIAgentsTracingProcessor()
introspection_processor = IntrospectionTracingProcessor()
 
set_trace_processors([langsmith_processor, introspection_processor])
 
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
)
 
result = Runner.run_sync(agent, "Hello!")
print(result.final_output)
 
langsmith_processor.force_flush()
langsmith_processor.shutdown()
introspection_processor.shutdown()

Arize / Phoenix

Use this when you already instrument your application with OpenInference and want Introspection in the same pipeline.

import os
from phoenix.otel import register
from openinference.instrumentation.openai import OpenAIInstrumentor
from introspection_sdk import IntrospectionSpanProcessor
 
tracer_provider = register(
    project_name="my-project",
    endpoint="https://otlp.arize.com/v1/traces",
    headers={
        "space_id": os.environ["ARIZE_SPACE_KEY"],
        "api_key": os.environ["ARIZE_API_KEY"],
    },
    batch=False,
)
 
tracer_provider.add_span_processor(
    IntrospectionSpanProcessor(),
    replace_default_processor=False,
)
 
OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)
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