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Nicholas Tindle 90466908a8 refactor(docs): restructure platform docs for GitBook and remove MkDo… (#11825 )

<!-- Clearly explain the need for these changes: -->
we met some reality when merging into the docs site but this fixes it
### Changes 🏗️
updates paths, adds some guides
<!-- Concisely describe all of the changes made in this pull request:
-->
update to match reality
### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
  - [x] deploy it and validate

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> Aligns block integrations documentation with GitBook.
> 
> - Changes generator default output to
`docs/integrations/block-integrations` and writes overview `README.md`
and `SUMMARY.md` at `docs/integrations/`
> - Adds GitBook frontmatter and hint syntax to overview; prefixes block
links with `block-integrations/`
> - Introduces `generate_summary_md` to build GitBook navigation
(including optional `guides/`)
> - Preserves per-block manual sections and adds optional `extras` +
file-level `additional_content`
> - Updates sync checker to validate parent `README.md` and `SUMMARY.md`
> - Rewrites `docs/integrations/README.md` with GitBook frontmatter and
updated links; adds `docs/integrations/SUMMARY.md`
> - Adds new guides: `guides/llm-providers.md`,
`guides/voice-providers.md`
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
fdb7ff8111. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: bobby.gaffin <bobby.gaffin@agpt.co>

2026-01-23 06:18:16 +00:00

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Jina Embeddings

Blocks for generating text embeddings using Jina AI.

Jina Embedding

What it is

Generates embeddings using Jina AI

How it works

This block generates vector embeddings for text using Jina AI's embedding models. Embeddings are numerical representations that capture semantic meaning, enabling similarity search and clustering.

Optionally specify which Jina model to use for embedding generation.

Inputs

Input	Description	Type	Required
texts	List of texts to embed	List[Any]	Yes
model	Jina embedding model to use	str	No

Outputs

Output	Description	Type
error	Error message if the operation failed	str
embeddings	List of embeddings	List[Any]

Possible use case

Semantic Search: Generate embeddings to enable semantic similarity search over documents.

Vector Database: Create embeddings for storage in vector databases like Pinecone or Weaviate.

Document Clustering: Embed documents to cluster similar content or find related items.

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