Automations: Streamlined data workflow for Datasets, Annotations, and Online Evaluations
Skills:
AI Workflow Automation90%
Production AI applications generate a large volume of data, and in order to extract insights and improve your app, you’ll need a way to sift through information quickly. While it’s useful to look at data by hand, creating automations to route your data can save a considerable amount of time.
Documentation: https://docs.smith.langchain.com/monitoring/faq/automations
Blog post: https://blog.langchain.dev/langsmith-production-logging-automations/
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Chat With Your Documents Using LangChain + JavaScript
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LangChain SQL Webinar
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LangChain "OpenAI functions" Webinar
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LangSmith Launch
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LangChain x Pinecone: Supercharging Llama-2 with RAG
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LangChain Expression Language
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Building LLM applications with LangChain with Lance
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Benchmarking Question/Answering Over CSV Data
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LangChain "RAG Evaluation" Webinar
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Fine-tuning in Your Voice Webinar
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Tabular Data Retrieval
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Building an LLM Application with Audio by AssemblyAI
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Superagent Deepdive Webinar
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Lessons from Deploying LLMs with LangSmith
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Shortwave Assistant Deepdive Webinar
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Cognitive Architectures for Language Agents
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Effectively Building with LLMs in the Browser with Jacob
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Data Privacy for LLMs
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"Theory of Mind" Webinar with Plastic Labs
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LangChain Templates
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Using Natural Language to Query Postgres with Jacob
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Building a Research Assistant from Scratch
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Benchmarking RAG over LangChain Docs
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Skeleton-of-Thought: Building a New Template from Scratch
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Benchmarking Methods for Semi-Structured RAG
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LangSmith Highlights: Getting Started
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LangSmith Highlights: Debugging
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LangSmith Highlights: Datasets
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LangSmith Highlights: Evaluation
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LangSmith Highlights: Human Annotation
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LangSmith Highlights: Monitoring
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LangSmith Highlights: Hub
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SQL Research Assistant
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Getting Started with Multi-Modal LLMs
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Build a Full Stack RAG App With TypeScript
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Auto-Prompt Builder (with Hosted LangServe)
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LangChain v0.1.0 Launch: Introduction
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LangChain v0.1.0 Launch: Observability
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LangChain v0.1.0 Launch: Integrations
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LangChain v0.1.0 Launch: Composability
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LangChain v0.1.0 Launch: Streaming
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LangChain v0.1.0 Launch: Output Parsing
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LangChain v0.1.0 Launch: Retrieval
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LangChain v0.1.0 Launch: Agents
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Hosted LangServe + LangChain Templates
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LangGraph: Intro
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LangGraph: Agent Executor
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LangGraph: Chat Agent Executor
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LangGraph: Human-in-the-Loop
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LangGraph: Dynamically Returning a Tool Output Directly
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LangGraph: Respond in a Specific Format
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LangGraph: Managing Agent Steps
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LangGraph: Force-Calling a Tool
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LangGraph: Multi-Agent Workflows
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Streaming Events: Introducing a new `stream_events` method
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Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
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OpenGPTs
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