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Update introduction.md and add video (#62)
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hasit authored Jul 15, 2024
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14 changes: 8 additions & 6 deletions docs/introduction/introduction.md → docs/introduction.md
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Expand Up @@ -23,6 +23,8 @@ performing continuous, incremental reviews for each commit within a pull
request. Review feedback is sent back to the pull requests and can be directly
committed.

<iframe width="560" height="315" src="https://www.youtube.com/embed/3SyUOSebG7E?si=i0oT9RAnH0PW81lY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

### How does CodeRabbit work?

**CodeRabbit** integrates into code repositories using GitHub or GitLab webhooks
Expand All @@ -31,7 +33,7 @@ A comprehensive review is performed when a PR or MR is created, and for
incremental commits and comments addressed to the bot. The feedback is then sent
directly back to the PR or MR.

![CodeRabbit Flow](../about/images/CodeRabbitFlow.png)
![CodeRabbit Flow](about/images/CodeRabbitFlow.png)

### Data, Privacy, and Security

Expand All @@ -40,11 +42,11 @@ influence the models. Queries to the Large Language Models (LLMs) are ephemeral
and there is zero retention on LLMs. Neither we nor the LLMs provider(s) share
any data collected during the code review process with third parties.

Data storage: Code downloaded during the review process is temporarily stored in
memory and deleted once the review is completed. The code is not stored or used for
any other purpose. However, CodeRabbit enhances future reviews for your organization by
storing the embeddings of the learnings generated from chat conversations. Additionally,
it integrates embeddings from issues in workflow systems (Liner, Jira, GitHub/GitLab issues)
Data storage: Code downloaded during the review process is temporarily stored in
memory and deleted once the review is completed. The code is not stored or used for
any other purpose. However, CodeRabbit enhances future reviews for your organization by
storing the embeddings of the learnings generated from chat conversations. Additionally,
it integrates embeddings from issues in workflow systems (Liner, Jira, GitHub/GitLab issues)
to assess the impact of code changes on existing issues.

Compliance and Data Privacy: Your data is kept confidential, isolated by the
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