Get Memories
分页获取某个用户或 Agent 的记忆。
POST
import os
import requests
import json
# 替换成你的 API Key
os.environ["MEMOS_API_KEY"] = "YOUR_API_KEY"
os.environ["MEMOS_BASE_URL"] = "https://memos.memtensor.cn/api/openmem/v1"
data = {
"user_id": "memos_user_123"
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Token {os.environ['MEMOS_API_KEY']}"
}
url = f"{os.environ['MEMOS_BASE_URL']}/get/memory"
res = requests.post(url=url, headers=headers, data=json.dumps(data))
print(f"result: {res.json()}")
# 请确保已安装 MemOS (pip install MemoryOS -U)
from memos.api.client import MemOSClient
client = MemOSClient(api_key="YOUR_API_KEY")
res = client.get_memory(user_id="memos_user_123")
print(f"result: {res}")
curl --request POST \
--url https://memos.memtensor.cn/api/openmem/v1/get/memory \
--header 'Authorization: Token YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"user_id": "memos_user_123"
}'
{
"code": 0,
"data": {
"memory_detail_list": [
{
"id": "<string>",
"memory_key": "<string>",
"memory_value": "<string>",
"memory_type": "WorkingMemory",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"confidence": 0,
"tags": [
"<string>"
],
"update_time": "<string>",
"relativity": 0,
"sources": [
{}
],
"info": {}
}
],
"preference_detail_list": [
{
"id": "<string>",
"preference_type": "explicit_preference",
"preference": "<string>",
"reasoning": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"relativity": 0,
"sources": [
{}
],
"info": {}
}
],
"profile_detail_list": [
{
"id": "<string>",
"project_id": "<string>",
"profile_template_id": "<string>",
"properties": {},
"status": "activated",
"created_at": "<string>",
"updated_at": "<string>"
}
],
"event_detail_list": [
{
"id": "<string>",
"event_key": "<string>",
"event_value": "<string>",
"event_type": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"info": {},
"sources": [
{}
],
"event_time": [
"<string>"
],
"event_location": [
"<string>"
],
"event_roles": [
"<string>"
]
}
],
"tool_memory_detail_list": [
{
"id": "<string>",
"tool_type": "ToolTrajectoryMemory",
"tool_value": "<string>",
"tool_used_status": [
{
"used_tool": "<string>",
"error_type": "<string>",
"success_rate": 0,
"tool_experience": "<string>"
}
],
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"relativity": 0,
"source": "<string>",
"experience": "<string>",
"info": {}
}
],
"skill_detail_list": [
{
"id": "<string>",
"skill_value": {
"name": "<string>",
"description": "<string>",
"procedure": "<string>",
"experience": [
"<string>"
],
"preference": [
"<string>"
],
"examples": [
"<string>"
],
"script": {},
"others": {}
},
"skill_url": "<string>",
"skill_type": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"confidence": 0,
"tags": [
"<string>"
],
"update_time": "<string>",
"relativity": "<string>"
}
],
"total": 0,
"size": 0,
"current": 0,
"pages": 0
},
"message": "<string>"
}Authorizations
Authorization
string
header
required
Token API_key,可在 API 控制台>接口密钥 中查看
请求体
application/json
user_id
string
获取的记忆所关联用户的唯一标识符。
agent_id
string
获取的记忆所关联 Agent 的唯一标识符。仅开启「为 Agent 创建独立记忆」时可用,与 user_id 二选一。
page
number
default: 1
分页页码,用于在返回结果较多时进行分页控制。
size
number
default: 10
指定每一类记忆在当前页返回的条目数量,最大值为50。
filter
object
记忆过滤的条件,用于在获取记忆前精确限定记忆范围。可用字段包括:"agent_id", "app_id", "create_time", "update_time"以及"info"中的字段。支持逻辑运算符(and,or)和比较运算符(gte、lte、gt、lt)。对于"info"字段,支持过滤传入的"business_type", "biz_id", "scene"和其他自定义字段。
Example:
"{"and": [{"create_time":{"gte":"..."}}]}"
include_memory_view
string[]
允许获取的记忆种类,不传时默认获取所有种类的记忆。全部种类及取值说明见 记忆种类。
Enum:"detail_factual""preference""skill""profile""event""tool_memory"
响应体
application/json
Successful Response
code
number
required
接口状态码,更多内容可查阅错误码列表了解详情。
data
object
展示属性
message
string
required
接口提示信息。
import os
import requests
import json
# 替换成你的 API Key
os.environ["MEMOS_API_KEY"] = "YOUR_API_KEY"
os.environ["MEMOS_BASE_URL"] = "https://memos.memtensor.cn/api/openmem/v1"
data = {
"user_id": "memos_user_123"
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Token {os.environ['MEMOS_API_KEY']}"
}
url = f"{os.environ['MEMOS_BASE_URL']}/get/memory"
res = requests.post(url=url, headers=headers, data=json.dumps(data))
print(f"result: {res.json()}")
# 请确保已安装 MemOS (pip install MemoryOS -U)
from memos.api.client import MemOSClient
client = MemOSClient(api_key="YOUR_API_KEY")
res = client.get_memory(user_id="memos_user_123")
print(f"result: {res}")
curl --request POST \
--url https://memos.memtensor.cn/api/openmem/v1/get/memory \
--header 'Authorization: Token YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"user_id": "memos_user_123"
}'
{
"code": 0,
"data": {
"memory_detail_list": [
{
"id": "<string>",
"memory_key": "<string>",
"memory_value": "<string>",
"memory_type": "WorkingMemory",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"confidence": 0,
"tags": [
"<string>"
],
"update_time": "<string>",
"relativity": 0,
"sources": [
{}
],
"info": {}
}
],
"preference_detail_list": [
{
"id": "<string>",
"preference_type": "explicit_preference",
"preference": "<string>",
"reasoning": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"relativity": 0,
"sources": [
{}
],
"info": {}
}
],
"profile_detail_list": [
{
"id": "<string>",
"project_id": "<string>",
"profile_template_id": "<string>",
"properties": {},
"status": "activated",
"created_at": "<string>",
"updated_at": "<string>"
}
],
"event_detail_list": [
{
"id": "<string>",
"event_key": "<string>",
"event_value": "<string>",
"event_type": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"info": {},
"sources": [
{}
],
"event_time": [
"<string>"
],
"event_location": [
"<string>"
],
"event_roles": [
"<string>"
]
}
],
"tool_memory_detail_list": [
{
"id": "<string>",
"tool_type": "ToolTrajectoryMemory",
"tool_value": "<string>",
"tool_used_status": [
{
"used_tool": "<string>",
"error_type": "<string>",
"success_rate": 0,
"tool_experience": "<string>"
}
],
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"update_time": "<string>",
"relativity": 0,
"source": "<string>",
"experience": "<string>",
"info": {}
}
],
"skill_detail_list": [
{
"id": "<string>",
"skill_value": {
"name": "<string>",
"description": "<string>",
"procedure": "<string>",
"experience": [
"<string>"
],
"preference": [
"<string>"
],
"examples": [
"<string>"
],
"script": {},
"others": {}
},
"skill_url": "<string>",
"skill_type": "<string>",
"create_time": "<string>",
"conversation_id": "<string>",
"status": "activated",
"confidence": 0,
"tags": [
"<string>"
],
"update_time": "<string>",
"relativity": "<string>"
}
],
"total": 0,
"size": 0,
"current": 0,
"pages": 0
},
"message": "<string>"
}