> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloosphere.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Search Engine

> Configure the vector database and search settings used by Knowledge Bases, Glossaries, and DbSphere.

<Info>Admin › Settings › Search Engine</Info>

Set the vector database type and search parameters.

* These settings are shared across [Knowledge Bases](/en/workspace/knowledge) (KbSphere), Glossaries, and DbSphere.

<Frame caption="Search Engine settings tab">
  <img src="https://mintcdn.com/cloocus/Or1RjU_AzOVJRxuS/images/admin/settings-search-engine.png?fit=max&auto=format&n=Or1RjU_AzOVJRxuS&q=85&s=5624f21040b0a5ae99180eeda338c065" alt="Search Engine settings tab" width="2880" height="1800" data-path="images/admin/settings-search-engine.png" />
</Frame>

***

## Search Engine Selection

| Engine                      | Strengths                                                          |
| --------------------------- | ------------------------------------------------------------------ |
| **Azure AI Search**         | Azure managed service, hybrid search supported by default          |
| **PostgreSQL pgvector**     | PostgreSQL extension, memory-efficient halfvec support             |
| **Milvus**                  | Large-scale distributed processing, high-performance vector search |
| **Elasticsearch**           | Hybrid search (BM25 + vector), reuse existing ELK stack            |
| **Google Vertex AI Search** | Google Cloud managed search service                                |

<Tabs>
  <Tab title="Azure AI Search">
    | Setting         | Description                      |
    | --------------- | -------------------------------- |
    | **Endpoint**    | Azure Search service URL         |
    | **API Key**     | Admin API Key                    |
    | **API Version** | API version (e.g., `2024-07-01`) |
  </Tab>

  <Tab title="pgvector">
    | Setting      | Description               |
    | ------------ | ------------------------- |
    | **Host**     | PostgreSQL server address |
    | **Port**     | Port number               |
    | **Database** | Database name             |
    | **User**     | Connection username       |
    | **Password** | Connection password       |

    <Note>
      The `pgvector` extension must be installed in PostgreSQL.
    </Note>
  </Tab>

  <Tab title="Milvus">
    | Setting      | Description              |
    | ------------ | ------------------------ |
    | **URI**      | Milvus server address    |
    | **Token**    | Auth token (optional)    |
    | **User**     | Auth username (optional) |
    | **Password** | Auth password (optional) |
  </Tab>

  <Tab title="Elasticsearch">
    | Setting          | Description                  |
    | ---------------- | ---------------------------- |
    | **URL**          | Elasticsearch server URL     |
    | **Username**     | Auth username (optional)     |
    | **Password**     | Auth password (optional)     |
    | **Index Prefix** | Index name prefix (optional) |
  </Tab>

  <Tab title="Vertex AI Search">
    | Setting                         | Description                                                                                                     |
    | ------------------------------- | --------------------------------------------------------------------------------------------------------------- |
    | **Project ID**                  | Google Cloud project ID                                                                                         |
    | **Location**                    | Region                                                                                                          |
    | **Collection**                  | Data store collection                                                                                           |
    | **Use Global Google Cloud Key** | When enabled, uses the global Google Cloud key. When disabled, enter Service Account Key JSON directly below.   |
    | **Service Account Key JSON**    | JSON input field shown when `Use Global Google Cloud Key` is disabled. Paste the full service account key JSON. |
  </Tab>
</Tabs>

<Note>
  Embedding engines and models are configured in the **[Settings > Documents](/en/admin/settings/documents)** tab. Vector dimensions must match between search engine and embedding settings.
</Note>

***

## Search Settings

Configure the number of results to retrieve from vector search.

| Setting   | Description                                                   | Default |
| --------- | ------------------------------------------------------------- | ------- |
| **Top K** | Number of search results to retrieve from the vector database | `10`    |

**Adjusting Top K:**

* **Higher** — retrieves more candidate documents and lowers the chance of missing the answer, but increases irrelevant results (noise), context tokens, and cost, and slows responses.
* **Lower** — precise, fast, and token-saving, but may miss the document containing the answer.

***

## Reranker

The reranker re-ranks search results with a semantic model to improve accuracy (optional).

* Select the reranker to use from the **Reranker Type** dropdown and configure the related parameters.

| Setting                | Description                                                                         | Default                      |
| ---------------------- | ----------------------------------------------------------------------------------- | ---------------------------- |
| **Reranker Type**      | Type of reranker to use                                                             | `Azure AI Search (built-in)` |
| **Reranker Top K**     | Result count after reranker                                                         | `5`                          |
| **Reranker threshold** | Minimum relevance score after reranking (0–1). Results below threshold are filtered | `0.0`                        |

**Tuning guide** — Reranker Top K decides how many of the results fetched by Top K are finally used, so always keep it at or below Top K.

* **Reranker Top K** — Raising it passes more evidence to the LLM and reduces omissions but increases noise and tokens; lowering it keeps only the most relevant few for precision but may miss results.
* **Reranker threshold** — Raising it filters out low-relevance results and reduces noise, but setting it too high lets no results through and returns an empty search. `0` passes everything with no filter.

When you select **Vertex AI Ranking API** as the reranker type, the sub-fields below are shown.

| Setting            | Description                                                                        |
| ------------------ | ---------------------------------------------------------------------------------- |
| **Project ID**     | Google Cloud project ID (optional — uses Vertex AI Search's Project ID when unset) |
| **Location**       | Vertex AI Ranking API region                                                       |
| **Reranker Model** | Reranking model to use                                                             |
| **Authentication** | Auth method (Use Global Google Cloud Key toggle or Service Account Key JSON entry) |

<Warning>
  Changing the search engine type makes previously indexed data inaccessible. Always plan data migration before changing.
</Warning>