LangChain Changelog

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September 2024

🧵 Collated trace view for enhanced conversation tracking & filtering

We're introduced a new default collated trace view for conversations! This update allows you to open and view multiple traces within a conversation without...

September 13, 2024

August 2024

📊 Custom dashboards to monitor LLM app performance

Create custom dashboards in LangSmith to track key metrics for your LLM app's performance such as cost, latency, and quality - including feedback from users...

August 29, 2024

🏷️ Resource tags to organize your Workspace in LangSmith

You can now organize your Workspace in LangSmith with resource tags. Resource tags help you efficiently manage, group, search, and filter through resources...

August 22, 2024

💥 Dynamic few-shot example selection in open beta

Dynamic few-shot example selection is now available in open beta for LangSmith users (currently for Cloud only). With this feature, you can perform...

August 21, 2024

🪄 Generate synthetic examples to enhance a LangSmith dataset

You can now generate synthetic examples for your datasets in LangSmith. Using the dataset schema you've defined, we generate new examples based on existing...

August 15, 2024

LangSmith LangGraph

☁️ 🤖 LangGraph Cloud is available in open beta

LangGraph Cloud is now available in open beta. LangGraph Cloud lets you build fault-tolerant, scalable agents. You can: All LangSmith users on Plus and...

🚀 Few-shot examples with LangSmith datasets

LangSmith now supports fast, easy-to-use APIs to find few shot examples from your datasets, which you can use to improve your LLM applications without...

LangSmith LangGraph

🚀 LangGraph Studio: The first agent IDE

LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of...

🏃 Trace comparison view & saving custom trace filters

In the runs table in LangSmith, you can now select traces to compare side-by-side. This lets you make direct comparisons to see discrepancies in output...

📊 Define, validate, and update dataset schemas in LangSmith

When building a dataset iteratively for an LLM app, having a defined schema for testing across examples lets you avoid broken code and keep your data clean...

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