text: EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerPortkeylogging_tracing_portkeyOn this pagelogging_tracing_portkeyLog, Trace, and Monitor Langchain LLM CallsWhen building apps or agents using Langchain, you end up making multiple API calls to fulfill a single user request. However, these requests are not chained when you want to analyse them. With Portkey, all the embeddings, completion, and other requests from a single user request will get logged and traced to a common ID, enabling you to gain full visibility of user interactions.This notebook serves as a step-by-step guide on how to integrate and use Portkey in your Langchain app.First, let's import Portkey, OpenAI, and Agent toolsimport osfrom langchain.agents import AgentType, initialize_agent, load_toolsfrom langchain.llms import OpenAIfrom langchain.utilities import PortkeyPaste your OpenAI API key below. (You can find it here)os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>"Get Portkey API Keyâ€‹Sign up for Portkey hereOn your dashboard, click on the profile icon on the top left, then click on "Copy API Key"Paste it belowPORTKEY_API_KEY = "<PORTKEY_API_KEY>"  # Paste your Portkey API Key hereSet Trace IDâ€‹Set the trace id for your request belowThe Trace ID can be common for all API calls originating from a single requestTRACE_ID = "portkey_langchain_demo"  # Set trace id hereGenerate