API Reference

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Archives

Create Archive

client.archives.create(ArchiveCreateParams { embedding_config, name, description } body, RequestOptionsoptions?): Archive { id, created_at, embedding_config, 7 more }

post/v1/archives/

List Archives

client.archives.list(ArchiveListParams { after, agent_id, before, 4 more } query?, RequestOptionsoptions?): ArrayPage<Archive { id, created_at, embedding_config, 7 more } >

get/v1/archives/

Modify Archive

client.archives.modify(stringarchiveID, ArchiveModifyParams { description, name } body, RequestOptionsoptions?): Archive { id, created_at, embedding_config, 7 more }

patch/v1/archives/{archive_id}

Get Archive By Id

client.archives.retrieve(stringarchiveID, RequestOptionsoptions?): Archive { id, created_at, embedding_config, 7 more }

get/v1/archives/{archive_id}

Delete Archive

client.archives.delete(stringarchiveID, RequestOptionsoptions?): Archive { id, created_at, embedding_config, 7 more }

delete/v1/archives/{archive_id}

ModelsExpand Collapse

Archive { id, created_at, embedding_config, 7 more }

Representation of an archive - a collection of archival passages that can be shared between agents.

id: string

The human-friendly ID of the Archive

created_at: string

The creation date of the archive

formatdate-time

embedding_config: EmbeddingConfig { embedding_dim, embedding_endpoint_type, embedding_model, 7 more }

Embedding configuration for passages in this archive

embedding_dim: number

The dimension of the embedding.

embedding_endpoint_type: "openai" | "anthropic" | "bedrock" | 16 more

The endpoint type for the model.

Accepts 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: string

The model for the embedding.

azure_deployment?: string | null

The Azure deployment for the model.

azure_endpoint?: string | null

The Azure endpoint for the model.

azure_version?: string | null

The Azure version for the model.

batch_size?: number

The maximum batch size for processing embeddings.

embedding_chunk_size?: number | null

The chunk size of the embedding.

embedding_endpoint?: string | null

The endpoint for the model (None if local).

handle?: string | null

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

name: string

The name of the archive

created_by_id?: string | null

The id of the user that made this object.

description?: string | null

A description of the archive

last_updated_by_id?: string | null

The id of the user that made this object.

metadata?: Record<string, unknown> | null

Additional metadata

updated_at?: string | null

The timestamp when the object was last updated.

formatdate-time

vector_db_provider?: VectorDBProvider

The vector database provider used for this archive's passages

Accepts one of the following:

"native"

"tpuf"

"pinecone"

VectorDBProvider = "native" | "tpuf" | "pinecone"

Supported vector database providers for archival memory

Accepts one of the following:

"native"

"tpuf"

"pinecone"

ArchivesPassages

Delete Passage From Archive

client.archives.passages.delete(stringpassageID, PassageDeleteParams { archive_id } params, RequestOptionsoptions?): void

delete/v1/archives/{archive_id}/passages/{passage_id}