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TencentDB-Agent-Memory/sdk/python/README_CN.md
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tencentdb-agent-memory-sdk-python

TencentDB Agent Memory v2 API 的 Python SDK。

提供同步客户端(MemoryClient)和异步客户端(AsyncMemoryClient)。

发布包名tencentdb-agent-memory-sdk-pythonPyPI / pip install 导入路径tencentdb_agent_memoryPython 模块)

安装

# 从 PyPI 安装(发布后)
pip install tencentdb-agent-memory-sdk-python

# 从本地 .whl 安装
pip install ./tencentdb_agent_memory_sdk_python-0.1.0-py3-none-any.whl

快速开始

from tencentdb_agent_memory import MemoryClient

client = MemoryClient(
    endpoint="http://127.0.0.1:8420",
    api_key="your-api-key",
    service_id="your-memory-space-id",
)

# L0: 添加对话
result = client.add_conversation(
    session_id="sess-1",
    messages=[
        {"role": "user", "content": "Hello"},
        {"role": "assistant", "content": "Hi!"},
    ],
)
print(result["accepted_ids"])

# L1: 搜索结构化记忆
hits = client.search_atomic(query="user preferences", limit=5)
print(hits["items"])

# L1: 更新一条记忆
client.update_atomic(id="note-xxx", content="updated content", background="context")

# L2: 列出场景文件
scenarios = client.list_scenarios(path_prefix="")
print(scenarios["entries"])

# L2: 读取场景文件
file = client.read_scenario("工作.md")
print(file["content"])

# L2: 更新场景文件(文件必须已存在)
client.write_scenario("工作.md", "# Updated content", summary="new summary")

# L3: 读取核心记忆(用户画像)
core = client.read_core()
print(core["content"])

# L3: 写入核心记忆
client.write_core("# User Profile\n...")

# Offload v2: 上报工具调用对,触发服务端 L1 异步处理(可 fire-and-forget
client.offload_ingest(
    session_id="agent_sess_123",
    tool_pairs=[
        {"tool_name": "search", "tool_call_id": "call_1", "params": {"q": "..."}, "result": "...", "timestamp": "..."},
    ],
)

# Offload v2: 服务端上下文压缩(同步等待结果)
compacted = client.offload_compact(
    session_id="agent_sess_123",
    messages=[...],
    ratio=0.7,
    context_window=128000,
)
print(compacted["messages"], compacted["report"])

# 读取记忆 pipeline 产物(如 persona.md、scene_blocks/*.md
raw = client.read_file("scene_blocks/工作.md")

异步用法

import asyncio
from tencentdb_agent_memory import AsyncMemoryClient

async def main():
    async with AsyncMemoryClient(
        endpoint="http://127.0.0.1:8420",
        api_key="your-api-key",
        service_id="your-memory-space-id",
    ) as client:
        result = await client.search_atomic(query="preferences")
        print(result["items"])

asyncio.run(main())

API 方法

层级 方法 接口
L0 add_conversation() POST /v2/conversation/add
L0 query_conversation() POST /v2/conversation/query
L0 search_conversation() POST /v2/conversation/search
L0 delete_conversation() POST /v2/conversation/delete
L1 update_atomic() POST /v2/atomic/update
L1 query_atomic() POST /v2/atomic/query
L1 search_atomic() POST /v2/atomic/search
L1 delete_atomic() POST /v2/atomic/delete
L2 list_scenarios() POST /v2/scenario/ls
L2 read_scenario() POST /v2/scenario/read
L2 write_scenario() POST /v2/scenario/write
L2 rm_scenario() POST /v2/scenario/rm
L3 read_core() POST /v2/core/read
L3 write_core() POST /v2/core/write
Offload offload_ingest() POST /v2/offload/ingest
Offload offload_compact() POST /v2/offload/compact
Offload offload_query_mmd() POST /v2/offload/query-mmd

错误处理

所有非零 code 的响应会抛出 TDAMError

from tencentdb_agent_memory import TDAMError

try:
    client.read_core()
except TDAMError as e:
    print(f"code={e.code} message={e.message} request_id={e.request_id}")

构建与打包

# 构建 wheel
python -m build
# → dist/tencentdb_agent_memory_sdk_python-0.1.0-py3-none-any.whl

# 或仅构建 wheel
pip wheel . --no-deps -w dist/

依赖

  • httpx>=0.24.0(支持异步的 HTTP 客户端)

许可证

MIT