# Collections

Collections let you group files together for targeted querying. When you chat with a collection, only the files in that collection are searched.

***

## Create a collection

`POST` `https://api.knowbase.ai/api/v1/collections`

#### Headers

| Name            | Type   | Description             |
| --------------- | ------ | ----------------------- |
| Authorization\* | string | `Bearer YOUR_API_TOKEN` |
| Content-Type\*  | string | `application/json`      |

#### Request Body

| Name        | Type   | Description                        |
| ----------- | ------ | ---------------------------------- |
| name\*      | string | Name of the collection             |
| file\_ids\* | array  | List of file ID strings to include |

```json
{
  "name": "Q4 Reports",
  "file_ids": [
    "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "b2c3d4e5-f6a7-8901-bcde-f12345678901"
  ]
}
```

#### Response (201: Created)

```json
{
  "id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
  "name": "Q4 Reports",
  "created_at": "2025-03-15",
  "files": [
    {"id": "a1b2c3d4-...", "filename": "report.pdf", "type": "pdf", "status": "success"},
    {"id": "b2c3d4e5-...", "filename": "analysis.docx", "type": "word", "status": "success"}
  ]
}
```

***

## List all collections

`GET` `https://api.knowbase.ai/api/v1/collections`

#### Response (200: OK)

```json
{
  "collections": [
    {
      "id": "c3d4e5f6-a7b8-9012-cdef-123456789012",
      "name": "Q4 Reports",
      "created_at": "2025-03-15",
      "files": [
        {"id": "a1b2c3d4-...", "filename": "report.pdf", "type": "pdf", "status": "success"}
      ]
    }
  ]
}
```

***

## Get collection details

`GET` `https://api.knowbase.ai/api/v1/collections/{collection_id}`

Returns the collection with its files.

***

## Delete a collection

`DELETE` `https://api.knowbase.ai/api/v1/collections/{collection_id}`

Deletes the collection. **The files inside are NOT deleted** -- they remain in your library.

#### Response (200: OK)

```json
{
  "message": "Collection deleted successfully"
}
```

***

### Example: Create and query a collection

```python
import requests

TOKEN = "YOUR_API_TOKEN"
BASE = "https://api.knowbase.ai/api/v1"
headers = {"Authorization": f"Bearer {TOKEN}", "Content-Type": "application/json"}

# Create a collection
collection = requests.post(f"{BASE}/collections", headers=headers, json={
    "name": "Research Papers",
    "file_ids": ["file-id-1", "file-id-2", "file-id-3"]
}).json()

# Chat with the collection
answer = requests.post(f"{BASE}/chat", headers=headers, json={
    "question": "What are the common themes across these papers?",
    "collection_id": collection["id"]
}).json()

print(answer["answer"])
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.knowbase.ai/api-reference/collections.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.