ibl-data-manager (3.59.0-ai-plus)
API for iblai
Request
Retrieve document sources related to a given query.
This endpoint performs a semantic search to find document sources that are relevant to the provided query within the specified pathway, and returns them along with confidence levels.
Args: request: The HTTP request containing the search query. org: Organization key identifier.
Returns: Response: A list of document sources with confidence levels.
Raises: ValidationError: If the request data is invalid.
- application/json
- application/x-www-form-urlencoded
- multipart/form-data
- Mock server
https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/sources/
https://base.manager.iblai.app/api/ai-index/orgs/{org}/users/{user_id}/documents/sources/
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X POST \
'https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/sources/' \
-H 'Authorization: YOUR_API_KEY_HERE' \
-H 'Content-Type: application/json' \
-d '{
"query": "Computational thinking",
"pathway": "test-pathway"
}'[ [ { … }, { … } ] ]
Request
Check the status of a document training task.
This endpoint retrieves the current status of an asynchronous document training task that was previously initiated.
Args: request: The HTTP request. org: Organization key identifier. task_id: The ID of the training task to check.
Returns: Response: The current status of the document training task, which can be "pending", "completed", or "failed".
- Mock server
https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/tasks/{task_id}/
https://base.manager.iblai.app/api/ai-index/orgs/{org}/users/{user_id}/documents/tasks/{task_id}/
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X GET \
'https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/tasks/{task_id}/' \
-H 'Authorization: YOUR_API_KEY_HERE'{ "status": "pending", "message": "Training document pending" }
Request
Train a document through a worker process.
This endpoint queues larger documents for training through a worker process, which is more suitable for handling documents that would take too long to process directly.
Args: request: The HTTP request containing the document information. org: Organization key identifier.
Returns: Response: A confirmation that the document was queued for training, including a task ID for tracking the progress.
Raises: ValidationError: If the request data is invalid. BadRequest: If there was an error processing the document.
- multipart/form-data
- application/x-www-form-urlencoded
- application/json
The patterns that the crawler should use to match urls. Patterns may be a glob pattern or a full regex pattern. Indicate the specified type in crawler_use_glob_matching.
- Mock server
https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/train/
https://base.manager.iblai.app/api/ai-index/orgs/{org}/users/{user_id}/documents/train/
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X POST \
'https://docs.ibl.ai/_mock/apis/ibl/api/ai-index/orgs/{org}/users/{user_id}/documents/train/' \
-H 'Authorization: YOUR_API_KEY_HERE' \
-H 'Content-Type: multipart/form-data' \
-F pathway=string \
-F url=string \
-F text=string \
-F type=string \
-F translate=false \
-F file=string \
-F access=private \
-F branch=string \
-F google_drive_auth_data=null \
-F dropbox_auth_data=null \
-F crawler_max_depth=0 \
-F crawler_max_pages_limit=0 \
-F crawler_max_concurrency=0 \
-F crawler_match_patterns=string \
-F crawler_use_glob_matching=true[ { "task_id": "4194d20c-37d5-4148-882f-f7d2d91f7769", "document_id": "doc-123456", "message": "Document received. Your request to train is queued" } ]