v1.0.0

We’re thrilled to announce the release of Co-STORM, a major update to the STORM project that brings **collaborative human-AI knowledge curation** into the spotlight! This new version empowers users to engage with language models in a more interactive and aligned way, transforming how we explore and curate knowledge together.

The knowledge-storm package is now at v1.0.0—make sure to upgrade by running:
```python
pip install knowledge-storm --upgrade
```

## News 🔥
- [2024/09] Co-STORM is now live and fully integrated into the knowledge-storm Python package. Try it out by upgrading the package today!
- [2024/09] Our paper on Co-STORM has been accepted to EMNLP 2024! You can read it [here](https://www.arxiv.org/abs/2408.15232).

## New Features 🎉

**🚀 Co-STORM Engine**

- Co-STORM is now integrated into the knowledge-storm package. Check out the [API documentation](https://github.com/stanford-oval/storm#co-storm-1) for more details.
- We introduce the **Agent interface** in Co-STORM, providing a unified framework for defining different LM agent policies for information seeking and knowledge curation. You can explore this interface [here](https://github.com/stanford-oval/storm/blob/main/knowledge_storm/interface.py).
  - Co-STORM LLM Experts: These agents ground their responses in external knowledge sources and ask follow-up questions based on the discourse.
  - Moderator Agent: Guides the conversation by generating insightful questions, drawing attention to discovered but underexplored areas.
  - Human Engagement: Users can inject their own utterances to steer the conversation, enabling an interactive and collaborative experience.

**🧠 Dynamic Mind Map**

Co-STORM introduces the **KnowledgeBase** [data class](https://github.com/stanford-oval/storm/blob/main/knowledge_storm/dataclass.py) that structures retrieved information into a concept-oriented hierarchy, forming a shared conceptual space between the user and the system. This is presented as a mind map in the graphical UI, allowing users to easily navigate and explore deep knowledge curation processes.

**💻 Graphical UI Update**

An interactive graphical UI of Co-STORM will be available soon on our [live research preview website](http://storm.genie.stanford.edu/). Stay tuned for updates!

**🔧 Modularity and Flexibility**

- Just like STORM, Co-STORM is built using the [dspy](https://github.com/stanfordnlp/dspy) library, ensuring full modularity. You can easily customize both language models (LMs) and retrieval modules (RMs) for advanced use cases. Check out the [customization guide](https://github.com/stanford-oval/storm#co-storm-2).
- Co-STORM supports the same LMs and RMs as STORM. See the full list of supported models [here](https://github.com/stanford-oval/storm#api).

## Contributors 🙌

This release wouldn’t be possible without the hard work of:

- [@Yucheng-Jiang](https://github.com/Yucheng-Jiang)
- [@shaoyijia](https://github.com/shaoyijia)
- [@dekunma](https://github.com/dekunma)