LangChain

pip install netra-sdk langchain langchain-openai

from netra import Netra
from langchain_openai import ChatOpenAI
import os

# Initialize Netra
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    trace_content=True
)

# Use LangChain as normal - automatically traced
model = ChatOpenAI(temperature=0.9)
response = model.invoke("Tell me a joke")

from netra import workflow, span
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate

model = ChatOpenAI()

@workflow()
def summarize_chain(text: str):
    prompt = PromptTemplate.from_template(
        "Summarize this text: {text}"
    )
    chain = prompt | model
    return chain.invoke({"text": text})

result = summarize_chain("Long article text...")

from netra import agent, task, SpanWrapper
from langchain_openai import ChatOpenAI
from langchain.agents import create_react_agent, AgentExecutor
from langchain.tools import Tool

model = ChatOpenAI()

@agent()
def run_agent(query: str):
    span = SpanWrapper("agent-execution").start()
    
    try:
        agent_executor = create_react_agent(
            llm=model,
            tools=[calculator_tool]
        )
        
        result = agent_executor.invoke({"input": query})
        span.end()
        return result
    except Exception as e:
        span.set_attribute("error", str(e))
        span.end()
        raise

from netra import task

@task()
def stream_response(query: str):
    model = ChatOpenAI(streaming=True)
    
    for chunk in model.stream(query):
        print(chunk.content, end="", flush=True)

from netra import Netra
from netra.instrumentation.instruments import InstrumentSet

# Only enable specific instruments
Netra.init(
    headers=f"x-api-key={os.environ.get('NETRA_API_KEY')}",
    instruments={InstrumentSet.OPENAI}
)