Datasets:
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license: apache-2.0
language:
- en
tags:
- clickhouse
- rag
- embeddings
- documentation
pretty_name: ClickHouse Documentation Embeddings
task_categories:
- feature-extraction
---
# ClickHouse Documentation Embeddings
Vector dataset used as the knowledge base for the ClickHouse RAG API. Contains chunked ClickHouse documentation with precomputed embeddings.
**Not intended for fine-tuning the embedding model.**
## Purpose
This dataset backs the retrieval step of the ClickHouse RAG API. At query time, the API embeds an incoming question using the same model and performs
cosine distance search against the `embedding` column in ClickHouse to retrieve relevant documentation chunks.
## Schema
| Column | Type | Description |
|---|---|---|
| `source_link` | `string` | URL of the source documentation page |
| `title` | `string` | Title of the documentation page |
| `chunk_index` | `int32` | Position of this chunk within the source page (0-based) |
| `chunk_text` | `string` | Text content of the chunk |
| `embedding` | `Sequence[float32]` | 4096-dimensional embedding vector |
## Embedding Model
Embeddings were produced by `qwen3_embedding_8b` served via [Text Embeddings Inference (TEI)](https://github.com/huggingface/text-embeddings-inference).
- **Dimensions:** 4096
- **Dtype:** float32
To query this dataset, embed your query using the same model and configuration. Using a different model will produce incompatible vectors and degrade
retrieval quality.
## Source
Sourced from the [ClickHouse documentation](https://clickhouse.com/docs).
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