Knowledge API

Knowledge Sources

Method	Endpoint	Description
POST	/api/knowledge-sources	Register knowledge source
GET	/api/knowledge-sources	List sources (optional ?tags= filter)
GET	/api/knowledge-sources/{id}	Get source
PUT	/api/knowledge-sources/{id}	Update source
DELETE	/api/knowledge-sources/{id}	Delete source (cascade-deletes items)
POST	/api/knowledge-sources/{id}/test	Test connection

Register Source

POST /api/knowledge-sources

{
  "name": "product-docs",
  "type": "vector_db",
  "connection_config": {"url": "http://qdrant:6333", "collection": "docs"},
  "tags": ["documentation"]
}

Source types: vector_db, mongo_db.

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Knowledge Items

Method	Endpoint	Description
POST	/api/knowledge-items	Create text knowledge item
POST	/api/knowledge-items/upload	Upload file/image (multipart)
GET	/api/knowledge-items	List items (?source_id=, ?tags=, ?content_type=)
GET	/api/knowledge-items/{id}	Get item metadata
GET	/api/knowledge-items/{id}/content	Download file content
PUT	/api/knowledge-items/{id}	Update item tags/metadata
DELETE	/api/knowledge-items/{id}	Delete item
POST	/api/knowledge-items/query	Query items by tags

Create Text Item

POST /api/knowledge-items

{
  "source_id": "<SOURCE_ID>",
  "content": "Our SLA guarantees 99.9% uptime.",
  "tags": ["sla", "production"]
}

Upload File

POST /api/knowledge-items/upload
Content-Type: multipart/form-data

curl -X POST http://localhost:8000/api/knowledge-items/upload \
  -H "Authorization: Bearer $GITHUB_TOKEN" \
  -F "file=@runbook.pdf" \
  -F "source_id=<SOURCE_ID>" \
  -F "tags=runbook,ops"

Query Items

POST /api/knowledge-items/query

{
  "tags": ["sla"]
}