Manage LangSmith runs, datasets, and prompts via a command-line interface.
npx skills add https://github.com/gigaverse-app/langsmith-cli --skill langsmith
Please help me install this Agent Skill. Skill: langsmith Source: https://github.com/gigaverse-app/langsmith-cli/tree/main/skills/langsmith Command: npx skills add https://github.com/gigaverse-app/langsmith-cli --skill langsmith
This Skill provides a command-line interface to interact with LangSmith, enabling efficient management and inspection of AI application traces, datasets, and prompts.
Use the langsmith skill to list the last 5 runs in the 'my-project' project.
High-intent search queries and answers about installing and using this skill.
Trace analysis allows you to inspect and filter AI application runs to debug failures. By listing recent errors and examining their inputs and outputs, you can identify the root cause of failing chains.
Prompt versioning for AI applications is managed by pushing, getting, and listing prompt templates. This approach enables strict version control and easy sharing of prompts across different environments.
You can extract examples from datasets for LLM evaluation by creating, listing, and managing datasets through a command-line interface. This supports advanced filtering and data extraction directly to files.
Yes, you can monitor AI application performance in real-time via a command-line interface. The CLI supports real-time monitoring and advanced filtering of runs to track application behavior continuously.
Yes, LangSmith CLI supports advanced filtering for run inspection. You can efficiently inspect, filter, and analyze runs to manage data and debug AI applications directly from your terminal.
lguibrInstrument applications to generate LangSmith traces for LLM observability.
Supporter09Configure and troubleshoot LLaMA-Factory LLM fine-tuning workflows end to end.
vecearCompose LangChain chains, agents, memory, tools, and RAG pipelines.
ddnettersQuery Langfuse REST API for LLM traces, generations, costs, and metrics.
