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API Reference
Agents

Folders

Attach Folder To Agent
agents.folders.attach(strfolder_id, FolderAttachParams**kwargs) -> AgentState
PATCH/v1/agents/{agent_id}/folders/attach/{folder_id}
Detach Folder From Agent
agents.folders.detach(strfolder_id, FolderDetachParams**kwargs) -> AgentState
PATCH/v1/agents/{agent_id}/folders/detach/{folder_id}
List Folders For Agent
agents.folders.list(stragent_id, FolderListParams**kwargs) -> SyncArrayPage[FolderListResponse]
GET/v1/agents/{agent_id}/folders
ModelsExpand Collapse
class FolderListResponse: …

(Deprecated: Use Folder) Representation of a source, which is a collection of files and passages.

id: str

The human-friendly ID of the Source

embedding_config: EmbeddingConfig

The embedding configuration used by the source.

embedding_dim: int

The dimension of the embedding.

embedding_endpoint_type: Literal["openai", "anthropic", "bedrock", 16 more]

The endpoint type for the model.

One of the following:
"openai"
"anthropic"
"bedrock"
"google_ai"
"google_vertex"
"azure"
"groq"
"ollama"
"webui"
"webui-legacy"
"lmstudio"
"lmstudio-legacy"
"llamacpp"
"koboldcpp"
"vllm"
"hugging-face"
"mistral"
"together"
"pinecone"
embedding_model: str

The model for the embedding.

azure_deployment: Optional[str]

The Azure deployment for the model.

azure_endpoint: Optional[str]

The Azure endpoint for the model.

azure_version: Optional[str]

The Azure version for the model.

batch_size: Optional[int]

The maximum batch size for processing embeddings.

embedding_chunk_size: Optional[int]

The chunk size of the embedding.

embedding_endpoint: Optional[str]

The endpoint for the model (None if local).

handle: Optional[str]

The handle for this config, in the format provider/model-name.

name: str

The name of the source.

created_at: Optional[datetime]

The timestamp when the source was created.

formatdate-time
created_by_id: Optional[str]

The id of the user that made this Tool.

description: Optional[str]

The description of the source.

instructions: Optional[str]

Instructions for how to use the source.

last_updated_by_id: Optional[str]

The id of the user that made this Tool.

metadata: Optional[Dict[str, object]]

Metadata associated with the source.

updated_at: Optional[datetime]

The timestamp when the source was last updated.

formatdate-time
vector_db_provider: Optional[VectorDBProvider]

The vector database provider used for this source’s passages

One of the following:
"native"
"tpuf"
"pinecone"