| Semantic Chunker (Experimental) | [SemanticChunker](/docs/how_to/semantic-chunker/) | Sentences | | First splits on sentences. Then combines ones next to each other if they are semantically similar enough. Taken from [Greg Kamradt](https://github.com/FullStackRetrieval-com/RetrievalTutorials/blob/main/tutorials/LevelsOfTextSplitting/5_Levels_Of_Text_Splitting.ipynb) |
| Integration: AI21 Semantic | [AI21SemanticTextSplitter](/docs/integrations/document_transformers/ai21_semantic_text_splitter/) | ✅ | Identifies distinct topics that form coherent pieces of text and splits along those. |
Evaluation is the process of assessing the performance and effectiveness of your LLM-powered applications.
It involves testing the model's responses against a set of predefined criteria or benchmarks to ensure it meets the desired quality standards and fulfills the intended purpose.
This process is vital for building reliable applications.
![](/img/langsmith_evaluate.png)
[LangSmith](https://docs.smith.langchain.com/) helps with this process in a few ways:
- It makes it easier to create and curate datasets via its tracing and annotation features
- It provides an evaluation framework that helps you define metrics and run your app against your dataset
- It allows you to track results over time and automatically run your evaluators on a schedule or as part of CI/Code
To learn more, check out [this LangSmith guide](https://docs.smith.langchain.com/concepts/evaluation).
@ -303,7 +303,15 @@ You can peruse [LangGraph how-to guides here](https://langchain-ai.github.io/lan
## [LangSmith](https://docs.smith.langchain.com/)
LangSmith allows you to closely trace, monitor and evaluate your LLM application.
It seamlessly integrates with LangChain, and you can use it to inspect and debug individual steps of your chains as you build.
It seamlessly integrates with LangChain and LangGraph, and you can use it to inspect and debug individual steps of your chains and agents as you build.
LangSmith documentation is hosted on a separate site.
You can peruse [LangSmith how-to guides here](https://docs.smith.langchain.com/how_to_guides/).