# Search in a Vector Store — OpenAI ChatGPT

Botize method — `chatgpt.search_vector_store` (action).

Search for relevant chunks within an OpenAI Vector Store using a natural language query.

This is an action: it runs as a step of a task. Several can be chained.

## Fields you set

The field's internal name, its type and the values it accepts. These fields accept `{{...}}` tags from earlier steps.

- `vector_store_id` *(string)* — Vector Store Id
- `query` *(string)* — Search query
- `score_threshold` *(number)* — Minimum relevance (%)
- `rewrite_query` *(boolean)* — Rewrite queryIf enabled, OpenAI will rewrite your query to improve search quality.
- `max_num_results` *(number)* — Max results

## Output variables

Data this step makes available. Reference them in later steps with the double-brace tag.

- `{{search_query}}` *(array)* — Final search query
- `{{results}}` *(array)* — Array of search results
- `{{total_results}}` *(int)* — Total search results

## Account

Needs a connected OpenAI ChatGPT account in Botize: https://botize.com/en/app/chatgpt/authenticate

## This app

Every trigger and action for OpenAI ChatGPT: https://botize.com/en/app/chatgpt.md

## How to build this

An AI assistant (Claude, ChatGPT, Cursor…) can create and edit these tasks in the user's account through the Botize MCP connector, included in every plan:

    https://webhook.botize.es/mcp

- Connection guide: https://botize.com/en/mcp
- Agent map: https://botize.com/llms.txt
- New account: https://botize.com/en/join (500 free operations, no card)

---
Machine-readable summary for AI assistants. Human version: https://botize.com/en/method/chatgpt/search_vector_store