We're thrilled to introduce **AutoRAG v0.3.0**, packed with new features and key improvements. Here’s what’s new:
1. **Improved Response Time for Deployment**
In earlier versions, the response time during deployment was slow, making it difficult to use optimized RAG pipeline. With v0.3.0, we've significantly **reduced the response time**, making deployment much more efficient for user-facing services.
2. **Re-designed Data Creation Process**
Data creation is an essential part of optimizing RAG pipelines, and we've made the process much smoother. In earlier versions, this feature was still in its early stages. Now, in v0.3.0, you can build **the data creation process** within AutoRAG.
We’ve added **AutoParse** and **AutoChunk**, allowing you to configure, parse, and chunk your data using a single YAML file. You can also easily compare different methods to refine your pipeline. Whether you build QA datasets with LLMs or manually, this structure offers a **human-in-the-loop** process to help you create and manage your data.
[Check out the detailed guide on data creation](https://www.notion.so/V0-3-version-10ad4b3072558064afe7c8811a621351?pvs=21).
3. **Python & Library Support Updates**
- **Python 3.9** is no longer supported. Please upgrade to Python 3.10.
- AutoRAG now works with **LangChain 0.3**, **LlamaIndex 0.11**, **Pydantic v2**, and **OpenAI o1** models.
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