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docs: update /launch blog post
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pages/blog/launch-week-1.mdx

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We're happy to share that the Decorator-based integration for Python now supports all Langfuse features and is the recommended way to use Langfuse in Python. The decorator makes integrating with Langfuse so much easier. Head over to the [Python Decorator docs](/docs/sdk/python/decorators) to learn more. All inputs, outputs, timings are captured automatically, and it works with all other [Langfuse integrations](/docs/integrations) (LangChain, LlamaIndex, OpenAI SDK, ...). To celebrate this milestone, we wrote a [blog post](/blog/2024-04-python-decorator) on the technical details and created the [example notebook](/guides/cookbook/example_decorator_openai_langchain) shown in the video as it demonstrates what's really cool about the decorator. Thanks again to [@lshalon](https://github.com/lshalon) and [@AshisGhosh](https://github.com/AshisGhosh) for your contributions to this!
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### Day 4: Datasets v2
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We're thrilled to release Datasets v2, featuring significant enhancements to the dataset experience in Langfuse. Improvements include a new editor powered by Codemirror, metadata support on all objects, tables that render inputs/outputs side-by-side, the ability to link dataset runs to traces, and the option to create dataset items directly from traces. We've also extended the public API with new endpoints for programmatic management of datasets. Check out the [changelog](/changelog/2024-04-25-datasets-v2) which summarizes all the new features and improvements.
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## Launch Week Events
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### Wednesday: First virtual town hall [#townhall]

theme.config.tsx

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<span className="sm:hidden">Langfuse Launch Week 1 →</span>
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{/* desktop */}
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<span className="hidden sm:inline">
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Langfuse Launch Week, Day 3: Decorator-based integration
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Langfuse Launch Week, Day 4: Datasets v2
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</span>
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</Link>
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