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docs: update docs from notion (#3074)

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* Update docs from Notion

* feat: Add RAG (Retrieval-Augmented Generation) components documentation

This commit adds documentation for RAG (Retrieval-Augmented Generation) components. It explains how these components process a user query by retrieving relevant documents and generating a concise summary that addresses the user's question. The documentation includes information about the Vectara component, its parameters, and the Vectara corpus. For more details, refer to the [Vectara documentation](https://docs.vectara.com/docs).

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Co-authored-by: ogabrielluiz <ogabrielluiz@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
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@ -6,26 +6,23 @@ slug: /components-rag
RAG (Retrieval-Augmented Generation) components process a user query by retrieving relevant documents and generating a concise summary that addresses the user's question.
### Vectara
`Vectara` performs RAG using a Vectara corpus, including document retrieval, reranking results, and summary generation.
`Vectara` performs RAG using a Vectara corpus, including document retrieval, reranking results, and summary generation.
**Parameters:**
- **Vectara Customer ID:** Customer ID.
- **Vectara Corpus ID:** Corpus ID.
- **Vectara API Key:** API key.
- **Search Query:** User query.
- **Lexical Interpolation:** How much to weigh lexical vs. embedding scores.
- **Metadata Filters:** Filters to narrow down the search documents and parts.
- **Reranker Type:** How to rerank the retrieved results.
- **Number of Results to Rerank:** Maximum reranked results.
- **Diversity Bias:** How much to diversify retrieved results (only for MMR reranker).
- **Max Results to Summarize:** Maximum search results to provide to summarizer.
- **Response Language:** The language code (use ISO 639-1 or 639-3 codes) of the summary.
- **Prompt Name:** The summarizer prompt.
**Parameters:**
- **Vectara Customer ID:** Customer ID.
- **Vectara Corpus ID:** Corpus ID.
- **Vectara API Key:** API key.
- **Search Query:** User query.
- **Lexical Interpolation:** How much to weigh lexical vs. embedding scores.
- **Metadata Filters:** Filters to narrow down the search documents and parts.
- **Reranker Type:** How to rerank the retrieved results.
- **Number of Results to Rerank:** Maximum reranked results.
- **Diversity Bias:** How much to diversify retrieved results (only for MMR reranker).
- **Max Results to Summarize:** Maximum search results to provide to summarizer.
- **Response Language:** The language code (use ISO 639-1 or 639-3 codes) of the summary.
- **Prompt Name:** The summarizer prompt.
For more information, consult the [Vectara documentation](https://docs.vectara.com/docs)
For more information, consult the [Vectara documentation](https://docs.vectara.com/docs)