LangSmith Fetch: CLI tool to debug agents from your terminal

LangChain · Beginner ·💻 AI-Assisted Coding ·5mo ago
Learn how to debug agents from your terminal using LangSmith Fetch, the new CLI that brings LangSmith trace data directly into your workflow. Pull traces and threads into your terminal or IDE with a single command. This may be helpful for developers working with coding agents like Claude Code, Cursor, or anyone who prefers a terminal-first workflow. We walk through: • Fetching your most recent traces instantly • Exporting traces and threads in bulk for evals and analysis • Using coding agents to analyze failures, spot patterns, and suggest fixes • Integrating LangSmith Fetch with your existing LangSmith setup LangSmith Fetch repo: https://github.com/langchain-ai/langsmith-fetch LangSmith docs: https://docs.langchain.com/langsmith Try LangSmith: https://smith.langchain.com/
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15 Shortwave Assistant Deepdive Webinar
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16 Cognitive Architectures for Language Agents
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17 Effectively Building with LLMs in the Browser with Jacob
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18 Data Privacy for LLMs
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19 "Theory of Mind" Webinar with Plastic Labs
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20 LangChain Templates
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21 Using Natural Language to Query Postgres with Jacob
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22 Building a Research Assistant from Scratch
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23 Benchmarking RAG over LangChain Docs
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25 Benchmarking Methods for Semi-Structured RAG
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26 LangSmith Highlights: Getting Started
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27 LangSmith Highlights: Debugging
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28 LangSmith Highlights: Datasets
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29 LangSmith Highlights: Evaluation
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30 LangSmith Highlights: Human Annotation
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31 LangSmith Highlights: Monitoring
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32 LangSmith Highlights: Hub
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33 SQL Research Assistant
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34 Getting Started with Multi-Modal LLMs
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36 Auto-Prompt Builder (with Hosted LangServe)
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37 LangChain v0.1.0 Launch: Introduction
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38 LangChain v0.1.0 Launch: Observability
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39 LangChain v0.1.0 Launch: Integrations
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40 LangChain v0.1.0 Launch: Composability
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41 LangChain v0.1.0 Launch: Streaming
LangChain v0.1.0 Launch: Streaming
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42 LangChain v0.1.0 Launch: Output Parsing
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43 LangChain v0.1.0 Launch: Retrieval
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44 LangChain v0.1.0 Launch: Agents
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45 Build and Deploy a RAG app with Pinecone Serverless
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46 Hosted LangServe + LangChain Templates
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47 LangGraph: Intro
LangGraph: Intro
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48 LangGraph: Agent Executor
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49 LangGraph: Chat Agent Executor
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50 LangGraph: Human-in-the-Loop
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51 LangGraph: Dynamically Returning a Tool Output Directly
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52 LangGraph: Respond in a Specific Format
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53 LangGraph: Managing Agent Steps
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54 LangGraph: Force-Calling a Tool
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55 LangGraph: Multi-Agent Workflows
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56 Streaming Events: Introducing a new `stream_events` method
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57 Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
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58 OpenGPTs
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Open Source RAG with Nomic's New Embedding Model (and ChromaDB and Ollama)
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60 LangGraph: Persistence
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