π LangSmith is a new platform designed to debug, test, and monitor LLM applications, bridging the gap between prototypes and production.
π₯οΈ The platform provides a user interface for creating and managing projects and data sets, but it is more efficient to use code for most tasks.
π To get started, users need to create a project, retrieve an API key, and set up environment variables. The API key is important for tracking LLM code with sensitivity in mind.
π¦ In order to bring LLM systems to production, we need to install LinkSmith, LangChain, and Python packages.
βοΈ By loading environment variables and running a chain, we can get the output from OpenAI.
π To have more control, we can use LangSmith and LangChain libraries and create trace instances.
π Tagging LM codes allows for filtering and organizing different steps of the LM chain.
π Grouping different LM calls can be done using the Trace Ace chain group function.
π₯οΈ The project UI provides a visual representation of the tagged and grouped LM calls.
π±οΈ You can structure your LLM calls using tags or by listing them with code.
π You can filter LLM runs based on the start time, run type, or metadata.
π» You can create a data set and use it to evaluate the quality of an LLM.
π The tutorial explains how to create a dataset and upload it to LangSmith.
π Different data formats, such as tuples and CSV files, can be used for storing data in LangSmith.
π§ͺ The tutorial also covers evaluating LLMs using the RunEvalConfig and RunOnDataset methods.
π The video explains how to bring LLM systems to production.
π» The process involves creating a client, running the data set method, and utilizing evaluation configuration.
π A custom prompt template can be created to categorize query, answer, and prediction results.
π The tutorial discusses the usage of the context QA and chord QA classes in the LangSmith system.
π» The q and a class takes an evaluator type, with the llm set to none and the prompt set to default.
π The tutorial demonstrates running the system on a data set and viewing the output in the UI.
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