vector_dbs

api_update_plan.md

@@ -226,7 +226,7 @@ Before finalizing documentation, verify:
 [x] 5. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/tools/tools.py` - Tool system APIs
 [x] 6. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/tools/rag_tool.py` - RAG tool runtime
 [x] 7. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/vector_io/vector_io.py` - Vector database operations
-8. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/vector_dbs/vector_dbs.py` - Vector database management
+[x] 8. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/vector_dbs/vector_dbs.py` - Vector database management
 9. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/files/files.py` - File management
 10. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/datasets/datasets.py` - Dataset management
 11. `/Users/saip/Documents/GitHub/llama-stack/llama_stack/apis/datasetio/datasetio.py` - Dataset I/O operations

docs/_static/llama-stack-spec.html

@@ -11387,15 +11387,17 @@
                             "tool",
                             "tool_group"
                         ],
-                        "title": "ResourceType",
                         "const": "vector_db",
-                        "default": "vector_db"
+                        "default": "vector_db",
+                        "description": "Type of resource, always 'vector_db' for vector databases"
                     },
                     "embedding_model": {
-                        "type": "string"
+                        "type": "string",
+                        "description": "Name of the embedding model to use for vector generation"
                     },
                     "embedding_dimension": {
-                        "type": "integer"
+                        "type": "integer",
+                        "description": "Dimension of the embedding vectors"
                     }
                 },
                 "additionalProperties": false,
@@ -11406,7 +11408,8 @@
                     "embedding_model",
                     "embedding_dimension"
                 ],
-                "title": "VectorDB"
+                "title": "VectorDB",
+                "description": "Vector database resource for storing and querying vector embeddings."
             },
             "HealthInfo": {
                 "type": "object",
@@ -12306,14 +12309,16 @@
                         "type": "array",
                         "items": {
                             "$ref": "#/components/schemas/VectorDB"
-                        }
+                        },
+                        "description": "List of vector databases"
                     }
                 },
                 "additionalProperties": false,
                 "required": [
                     "data"
                 ],
-                "title": "ListVectorDBsResponse"
+                "title": "ListVectorDBsResponse",
+                "description": "Response from listing vector databases."
             },
             "Event": {
                 "oneOf": [

docs/_static/llama-stack-spec.yaml

@@ -8151,13 +8151,17 @@ components:
             - benchmark
             - tool
             - tool_group
-          title: ResourceType
           const: vector_db
           default: vector_db
+          description: >-
+            Type of resource, always 'vector_db' for vector databases
         embedding_model:
           type: string
+          description: >-
+            Name of the embedding model to use for vector generation
         embedding_dimension:
           type: integer
+          description: Dimension of the embedding vectors
       additionalProperties: false
       required:
         - identifier
@@ -8166,6 +8170,8 @@ components:
         - embedding_model
         - embedding_dimension
       title: VectorDB
+      description: >-
+        Vector database resource for storing and querying vector embeddings.
     HealthInfo:
       type: object
       properties:
@@ -8817,10 +8823,12 @@ components:
           type: array
           items:
             $ref: '#/components/schemas/VectorDB'
+          description: List of vector databases
       additionalProperties: false
       required:
         - data
       title: ListVectorDBsResponse
+      description: Response from listing vector databases.
     Event:
       oneOf:
         - $ref: '#/components/schemas/UnstructuredLogEvent'

llama_stack/apis/vector_dbs/vector_dbs.py

@@ -15,6 +15,12 @@ from llama_stack.schema_utils import json_schema_type, webmethod
 
 @json_schema_type
 class VectorDB(Resource):
+    """Vector database resource for storing and querying vector embeddings.
+
+    :param type: Type of resource, always 'vector_db' for vector databases
+    :param embedding_model: Name of the embedding model to use for vector generation
+    :param embedding_dimension: Dimension of the embedding vectors
+    """
     type: Literal[ResourceType.vector_db] = ResourceType.vector_db
 
     embedding_model: str
@@ -30,6 +36,13 @@ class VectorDB(Resource):
 
 
 class VectorDBInput(BaseModel):
+    """Input parameters for creating or configuring a vector database.
+
+    :param vector_db_id: Unique identifier for the vector database
+    :param embedding_model: Name of the embedding model to use for vector generation
+    :param embedding_dimension: Dimension of the embedding vectors
+    :param provider_vector_db_id: (Optional) Provider-specific identifier for the vector database
+    """
     vector_db_id: str
     embedding_model: str
     embedding_dimension: int
@@ -37,6 +50,10 @@ class VectorDBInput(BaseModel):
 
 
 class ListVectorDBsResponse(BaseModel):
+    """Response from listing vector databases.
+
+    :param data: List of vector databases
+    """
     data: list[VectorDB]