text: EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerAimAimAim makes it super easy to visualize and debug LangChain executions. Aim tracks inputs and outputs of LLMs and tools, as well as actions of agents. With Aim, you can easily debug and examine an individual execution:Additionally, you have the option to compare multiple executions side by side:Aim is fully open source, learn more about Aim on GitHub.Let's move forward and see how to enable and configure Aim callback.Tracking LangChain Executions with AimIn this notebook we will explore three usage scenarios. To start off, we will install the necessary packages and import certain modules. Subsequently, we will configure two environment variables that can be established either within the Python script or through the terminal.pip install aimpip install langchainpip install openaipip install google-search-resultsimport osfrom datetime import datetimefrom langchain.llms import OpenAIfrom langchain.callbacks import AimCallbackHandler, StdOutCallbackHandlerOur examples use a GPT model as the LLM, and OpenAI offers an API for this purpose. You can obtain the key from the following link: https://platform.openai.com/account/api-keys .We will use the SerpApi to retrieve search results from Google. To acquire the SerpApi key, please go to https://serpapi.com/manage-api-key .os.environ["OPENAI_API_KEY"] = "..."os.environ["SERPAPI_API_KEY"] = "..."The event methods of AimCallbackHandler accept the LangChain module or agent