QamaqQamaq
POST

Search knowledge base (POST)

/search

Performs semantic search across the knowledge base using vector embeddings.

Common Use Cases

  • Build a search interface for your knowledge base
  • Power an AI chatbot with relevant context
  • Find related documents for research

Important Notes

  • Search results include a relevance score from 0 to 1
  • Use the threshold parameter to filter low-relevance results
  • For best results, use natural language queries

Request Body

application/jsonrequired
{
query*:string

Search query

limit:integer

Maximum number of results

Default: 10

folder_id:string

Limit search to specific folder

file_types:string[]

Filter by file types (e.g., ['pdf', 'docx'])

include_content:boolean

Include content snippets in results

Default: true

threshold:number

Minimum relevance score

Default: 0.7

}

Code Examples

curl -X POST "https://api.qamaq.io/api/v1/search" \
  -H "Authorization: Bearer qmq_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{"key": "value"}'

Responses

200Search results

Response Body

{
query:string
results:object[]
total:integer
processing_time_ms:number
}
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