openinference-instrumentation-langchain

import os from opentelemetry import trace from opentelemetry.sdk.resources import Resource from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessor from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter from openinference.instrumentation.langchain import LangChainInstrumentor from langchain.agents import AgentExecutor, create_tool_calling_agent from langchain_core.prompts import ChatPromptTemplate from langchain_core.tools import tool from langchain_openai import ChatOpenAI # Set up OpenTelemetry resource = Resource.create({"service.name": "my-langchain-app"}) tracer_provider = TracerProvider(resource=resource) span_exporter = OTLPSpanExporter(endpoint=os.environ.get('OTEL_EXPORTER_OTLP_ENDPOINT', 'http://localhost:6006/v1/traces')) tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter)) trace.set_tracer_provider(tracer_provider) # Instrument LangChain LangChainInstrumentor().instrument() # Ensure OpenAI API key is set for the example os.environ["OPENAI_API_KEY"] = os.environ.get('OPENAI_API_KEY', 'sk-YOUR_OPENAI_KEY_HERE') # Replace with actual key or ensure env var is set @tool def multiply(a: int, b: int) -> int: """Multiply two numbers together.""" return a * b @tool def add(a: int, b: int) -> int: """Add two numbers together.""" return a + b llm = ChatOpenAI(temperature=0, model="gpt-4o-mini") tools = [multiply, add] prompt = ChatPromptTemplate.from_messages([ ("system", "You are a helpful assistant."), ("human", "{input}"), ]) agent = create_tool_calling_agent(llm, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) if __name__ == "__main__": print("Running agent...") response = agent_executor.invoke({"input": "What is 123 multiplied by 456?"}) print(f"Agent Response: {response['output']}") print("Traces should be visible in your configured OpenTelemetry collector (e.g., Phoenix at http://localhost:6006).")