---
  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).