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90466908a8
<!-- 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:
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- [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>
42 lines
1.2 KiB
Markdown
42 lines
1.2 KiB
Markdown
# Jina Embeddings
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<!-- MANUAL: file_description -->
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Blocks for generating text embeddings using Jina AI.
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## Jina Embedding
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### What it is
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Generates embeddings using Jina AI
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### How it works
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<!-- MANUAL: how_it_works -->
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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.
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Optionally specify which Jina model to use for embedding generation.
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<!-- END MANUAL -->
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### Inputs
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| Input | Description | Type | Required |
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|-------|-------------|------|----------|
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| texts | List of texts to embed | List[Any] | Yes |
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| model | Jina embedding model to use | str | No |
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### Outputs
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| Output | Description | Type |
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|--------|-------------|------|
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| error | Error message if the operation failed | str |
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| embeddings | List of embeddings | List[Any] |
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### Possible use case
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<!-- MANUAL: use_case -->
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**Semantic Search**: Generate embeddings to enable semantic similarity search over documents.
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**Vector Database**: Create embeddings for storage in vector databases like Pinecone or Weaviate.
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**Document Clustering**: Embed documents to cluster similar content or find related items.
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<!-- END MANUAL -->
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---
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