Add Memory

POST /memory/add

Add new memories from a conversation. Mem0 automatically extracts and stores relevant facts from the messages. The API can automatically classify the memory type using LLM-based classification.

Request Body

array

required

Array of message objects representing the conversation.

Show Message Object

string

required

The role of the message sender (e.g., “user”, “assistant”).

string

required

The content of the message.

string

required

Unique identifier for the user. All memories are associated with this user ID.

object

Optional metadata to attach to the memory. You can include custom fields like tags, timestamps, or manually specify memory_type.

boolean

default:"true"

Enable automatic memory type classification. When enabled, the API uses GPT-4.1-nano to classify the memory into one of five types: LONG_TERM, SHORT_TERM, EPISODIC, SEMANTIC, or PROCEDURAL.

Response

boolean

Indicates whether the operation was successful.

object

The result from mem0 containing memory IDs and extracted information.

Show Result Object

array

Array of created memory objects with IDs and extracted content.

string

The automatically classified memory type (LONG_TERM, SHORT_TERM, EPISODIC, SEMANTIC, or PROCEDURAL). Only present if auto_classify is enabled.

Example Request

curl -X POST http://localhost:8000/memory/add \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [
      {
        "role": "user",
        "content": "I prefer dark mode in all my applications"
      }
    ],
    "user_id": "user_123",
    "auto_classify": true
  }'

Example Response

{
  "success": true,
  "result": {
    "results": [
      {
        "id": "mem_abc123",
        "memory": "User prefers dark mode in applications",
        "event": "ADD"
      }
    ]
  },
  "classified_type": "LONG_TERM"
}

Manual Memory Type Override

You can manually specify the memory type by including it in the metadata:

curl -X POST http://localhost:8000/memory/add \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [
      {
        "role": "user",
        "content": "Yesterday I attended the React conference"
      }
    ],
    "user_id": "user_123",
    "metadata": {
      "memory_type": "EPISODIC",
      "tags": ["conference", "react"]
    }
  }'

Error Responses

string

Error message describing what went wrong.

500 Internal Server Error

{
  "detail": "Failed to connect to vector store"
}

Implementation Details

Source: backend/main.py:189
Classification Model: GPT-4.1-nano-2025-04-14
Default Classification: LONG_TERM (used as fallback on classification errors)
Memory Extraction: Powered by mem0, which intelligently extracts facts from conversations

Memory API

Backend API

Electron IPC

POST /memory/add

Request Body

Response

Example Request

Example Response

Manual Memory Type Override

Error Responses

Implementation Details

​POST /memory/add

​Request Body

​Response

​Example Request

​Example Response

​Manual Memory Type Override

​Error Responses

​Implementation Details

POST /memory/add

Request Body

Response

Example Request

Example Response

Manual Memory Type Override

Error Responses

Implementation Details