Letta · Schema

EmbeddingConfig

Configuration for embedding model connection and processing parameters.

AIAgentsStateful AgentsMemoryMemGPTContinual LearningMCPMulti-AgentRAGOpen Source

Properties

Name	Type	Description
embedding_endpoint_type	string	The endpoint type for the model.
embedding_endpoint	object	The endpoint for the model (`None` if local).
embedding_model	string	The model for the embedding.
embedding_dim	integer	The dimension of the embedding.
embedding_chunk_size	object	The chunk size of the embedding.
handle	object	The handle for this config, in the format provider/model-name.
batch_size	integer	The maximum batch size for processing embeddings.
azure_endpoint	object	The Azure endpoint for the model.
azure_version	object	The Azure version for the model.
azure_deployment	object	The Azure deployment for the model.

View JSON Schema on GitHub

JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/EmbeddingConfig",
  "title": "EmbeddingConfig",
  "properties": {
    "embedding_endpoint_type": {
      "type": "string",
      "enum": [
        "openai",
        "anthropic",
        "bedrock",
        "google_ai",
        "google_vertex",
        "azure",
        "groq",
        "ollama",
        "webui",
        "webui-legacy",
        "lmstudio",
        "lmstudio-legacy",
        "llamacpp",
        "koboldcpp",
        "vllm",
        "hugging-face",
        "mistral",
        "together",
        "pinecone"
      ],
      "title": "Embedding Endpoint Type",
      "description": "The endpoint type for the model."
    },
    "embedding_endpoint": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Embedding Endpoint",
      "description": "The endpoint for the model (`None` if local)."
    },
    "embedding_model": {
      "type": "string",
      "title": "Embedding Model",
      "description": "The model for the embedding."
    },
    "embedding_dim": {
      "type": "integer",
      "title": "Embedding Dim",
      "description": "The dimension of the embedding."
    },
    "embedding_chunk_size": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "title": "Embedding Chunk Size",
      "description": "The chunk size of the embedding.",
      "default": 300
    },
    "handle": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Handle",
      "description": "The handle for this config, in the format provider/model-name."
    },
    "batch_size": {
      "type": "integer",
      "title": "Batch Size",
      "description": "The maximum batch size for processing embeddings.",
      "default": 32
    },
    "azure_endpoint": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Azure Endpoint",
      "description": "The Azure endpoint for the model."
    },
    "azure_version": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Azure Version",
      "description": "The Azure version for the model."
    },
    "azure_deployment": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "title": "Azure Deployment",
      "description": "The Azure deployment for the model."
    }
  },
  "type": "object",
  "required": [
    "embedding_endpoint_type",
    "embedding_model",
    "embedding_dim"
  ],
  "description": "Configuration for embedding model connection and processing parameters."
}