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sdk-memory

sdk-memory

Use Mem0 SDKs for hosted Platform clients and local OSS memory in Python and TypeScript, including CRUD, search, async clients, entity filters, metadata, categories, export, feedback, and migration-sensitive API differences.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: sdk-memory description: "Use Mem0 SDKs for hosted Platform clients and local OSS memory in Python and TypeScript, including CRUD, search, async clients, entity filters, metadata, categories, export, feedback, and migration-sensitive API differences." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Mem0 SDK Memory

Use this sub-skill when the task asks for Mem0, mem0ai, a memory layer, memory CRUD/search, Platform SDK calls, OSS Memory() usage, TypeScript MemoryClient, mem0ai/oss, async memory calls, retrieve-generate-store flows, filters, metadata, categories, exports, feedback, or SDK migration debugging.

Route First

  • Use this sub-skill for Python MemoryClient, AsyncMemoryClient, Memory, AsyncMemory, TypeScript hosted MemoryClient, and TypeScript OSS Memory from mem0ai/oss.
  • Use Python SDK for imports, live signatures, sync/async Python examples, and Platform-vs-OSS differences.
  • Use TypeScript SDK for hosted MemoryClient, OSS Memory, camelCase/snake_case option differences, exports, and feedback.
  • Use Memory Operations for add/search/update/delete patterns, retrieve-generate-store workflows, filters, metadata, categories, export, feedback, and migration notes.
  • Use Troubleshooting for empty search results, import/install failures, API keys, optional backends, validation errors, and SDK misuse.

Sibling Boundaries

  • Route provider, vector store, embedder, LLM, reranker, graph-memory, and optional dependency selection to provider-configuration.
  • Route terminal commands, CLI config, JSON output, stdin/file workflows, import/export through commands, and mem0 init/add/search behavior to cli-memory.
  • Route REST server deployment, Docker Compose, OpenMemory, MCP server hosting, API keys for self-hosted services, migrations, and operational backups to self-hosted-openmemory.
  • Route editor/agent plugins, framework cookbooks, Vercel AI SDK provider wrapping, MCP plugin config, hooks, OpenClaw, and Pi Agent plugin tasks to integrations-plugins.

Fast Decision Tree

  1. Hosted Platform SDK? Use MemoryClient / AsyncMemoryClient in Python or MemoryClient in TypeScript; it needs a Mem0 API key and talks to https://api.mem0.ai by default.
  2. Local OSS memory? Use Python Memory / AsyncMemory or TypeScript Memory from mem0ai/oss; it needs provider/backend configuration, often OpenAI credentials by default.
  3. Search or list memories? Put entity scope in filters, for example filters={"user_id": "alice"} in Python and { filters: { user_id: "alice" } } in TypeScript.
  4. Add or bulk delete by entity? Follow the SDK-specific options in Memory Operations; current SDKs keep top-level entity options for add/delete-all, while search/get-all require filters.
  5. Debug before changing code? Run python scripts/inspect_mem0_sdk.py --json to inspect installed Python exports/signatures without credentials, then python scripts/mem0_sdk_smoke.py --mode plan --language both to generate safe smoke snippets.

Minimal Patterns

Python hosted Platform:

from mem0 import MemoryClient

client = MemoryClient(api_key=os.environ["MEM0_API_KEY"])
client.add("User prefers vegetarian meals", user_id="alice", metadata={"source": "chat"})
results = client.search("dietary preferences", filters={"user_id": "alice"}, top_k=5)

Python OSS:

from mem0 import Memory

memory = Memory()
memory.add("User prefers vegetarian meals", user_id="alice", metadata={"source": "chat"})
results = memory.search("dietary preferences", filters={"user_id": "alice"}, top_k=5)

TypeScript hosted Platform:

import { MemoryClient } from "mem0ai";

const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY! });
await client.add([{ role: "user", content: "User prefers vegetarian meals" }], { userId: "alice" });
const results = await client.search("dietary preferences", { filters: { user_id: "alice" }, topK: 5 });

TypeScript OSS:

import { Memory } from "mem0ai/oss";

const memory = new Memory();
await memory.add("User prefers vegetarian meals", { userId: "alice", metadata: { source: "chat" } });
const results = await memory.search("dietary preferences", { filters: { user_id: "alice" }, topK: 5 });

Safety Notes

  • Do not print API keys, provider keys, memory contents from production users, or full environment dumps.
  • Prefer read-only inspection before live API calls. The bundled scripts default to help/plan/inspection modes and do not require credentials unless explicitly requested.
  • Never instruct future agents to run source-repository tests or examples; use the bundled references and scripts here.
  • Treat reset, wildcard deletes, and scoped delete_all / deleteAll as destructive. Confirm scope and tenant before running them.
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