mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local `Memory` class) to the mem0 Platform / hosted / managed SDK (the `MemoryClient` class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g. "migrate my mem0 setup to the platform", "switch from self-hosted mem0 to MemoryClient", "use my mem0 API key instead of a local Qdrant", "move mem0 to the cloud/hosted/managed service", or "replace my local mem0 vector store + embedder config with the platform". Applies to Python (`from mem0 import Memory` → `from mem0 import MemoryClient`) and TypeScript/JavaScript (`import { Memory } from "mem0ai/oss"` → `import MemoryClient from "mem0ai"`). Trigger even when the user doesn't say the word "migrate" but clearly wants their existing mem0 integration to run against the hosted platform. It first produces a reviewable migration plan, then executes it after the developer approves. Strictly scoped to the mem0 integration — it does not refactor, restructure, or "improve" any unrelated code.
- License 许可
- Apache-2.0
- 最近更新
- 2026-08-12
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01 前言 Front Matter
- name
- mem0-oss-to-platform
- description
- Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local `Memory` class) to the mem0 Platform / hosted / managed SDK (the `MemoryClient` class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g. "migrate my mem0 setup to the platform", "switch from self-hosted mem0 to MemoryClient", "use my mem0 API key instead of a local Qdrant", "move mem0 to the cloud/hosted/managed service", or "replace my local mem0 vector store + embedder config with the platform". Applies to Python (`from mem0 import Memory` → `from mem0 import MemoryClient`) and TypeScript/JavaScript (`import { Memory } from "mem0ai/oss"` → `import MemoryClient from "mem0ai"`). Trigger even when the user doesn't say the word "migrate" but clearly wants their existing mem0 integration to run against the hosted platform. It first produces a reviewable migration plan, then executes it after the developer approves. Strictly scoped to the mem0 integration — it does not refactor, restructure, or "improve" any unrelated code.
02 资源文件 5
- 许可证LICENSE10.5 KB
- 参考文档README.md3.1 KB
- 参考文档references/api-mapping.md6.0 KB
- 参考文档references/gotchas.md3.9 KB
- 参考文档references/plan-template.md3.4 KB
03 SKILL.md 正文
Migrate mem0 OSS → mem0 Platform (hosted)
This skill migrates a project's memory layer from the self-hosted mem0 OSS SDK to the hosted mem0 Platform SDK, working for any project shape — an agent, a RAG pipeline, an API service, a chatbot, a background worker. You discover where mem0 is actually used, write a plan the developer reviews, and then execute it on approval.
The mental model (read this first — it's why the migration is shaped the way it is)
OSS mem0 means the developer runs the whole memory stack themselves: a vector store
(Qdrant/pgvector/Chroma/…), an embedder, an LLM for fact extraction, and a local history DB. All of
that is wired up in a config object passed to Memory.
The Platform means mem0 runs that stack for them. The developer just holds an API key. So
the migration is mostly subtraction: the local infrastructure config collapses into a single
MemoryClient(api_key=...). The method calls stay recognizable (add/search/get_all/…), but a
few parameter conventions tighten up and the return values are server responses.
So the core of every migration is:
Memory/Memory.from_config({...})→MemoryClient()(reads the API key from the env).- Delete the local
vector_store/llm/embedder/graph_store/history_db_pathconfig. - Fix up each call site to the hosted call convention (entity IDs into
filters, pagination, etc.). - Flag everything that isn't a clean 1:1 so the developer can decide (see
references/gotchas.md).
Scope discipline: touch only mem0-related code, config, dependencies, and env. Preserve the project's existing behavior, structure, and style. Do not rename things, "tidy" nearby code, or change the app's logic. The developer asked to swap a backend, not to refactor their project.
Workflow
Work through these phases in order. Phases 1–4 produce the plan; phase 5 runs only after approval.
Phase 0 — Prerequisite check
The hosted SDK needs a mem0 API key (MEM0_API_KEY, obtainable at https://app.mem0.ai). Confirm
the developer has one. You don't need the key value to write the plan, but flag in the plan that it
must be set (in .env / secrets manager, never hardcoded) before execution and verification.
Phase 1 — Discover the mem0 footprint
Do not assume the layout. Find every place mem0 appears. Detect the language and the installed version first, then sweep for usage. Concretely, search for:
- Imports / instantiation:
from mem0 import Memory,Memory.from_config,Memory(,import ... from "mem0ai",from "mem0ai/oss",new Memory(. - Config blocks: keys like
vector_store/vectorStore,embedder,llm,graph_store/graphStore,history_db_path,historyStore,custom_fact_extraction_prompt,custom_update_memory_prompt,enable_graph. - Every call site:
.add(,.search(,.get_all(/.getAll(,.delete_all(/.deleteAll(,.get(,.update(,.delete(,.reset(,.history(. - Dependencies & env:
requirements.txt/pyproject.toml/package.jsonformem0aiand any local-infra deps that exist only for mem0 (e.g.qdrant-client,chromadb);.env/config for things likeOPENAI_API_KEYused by the local embedder/LLM; any docker-compose service (e.g. a Qdrant container) that exists only to back mem0.
Use Grep/Glob broadly; a single missed call site is a runtime break later. Record file:line for
each finding — the plan's inventory is built from this.
Phase 2 — Verify the API against the installed SDK (don't guess)
Versions drift, and the OSS and hosted classes have subtly different signatures. Before mapping, confirm the real signatures of the installed package rather than trusting memory:
- Python:
python -c "import inspect; from mem0 import MemoryClient; print(inspect.signature(MemoryClient.search))"for each method you'll touch, and read the installed source undersite-packages/mem0/client/main.pyif anything is ambiguous (e.g. whether a method rejects top-level entity params). Also check the OSS side the project currently uses. - TypeScript: read the installed types/dist under
node_modules/mem0ai/to confirm option names (limitvstopK,userIdvs a nestedfilters) and the default vsmem0ai/ossexport.
This verification step is the single most important habit — it's what keeps the plan correct across
mem0 versions. Then consult references/api-mapping.md for the OSS→hosted translation of each
method (Python and TypeScript), and the official guide at https://docs.mem0.ai/migration/oss-v2-to-v3.
Phase 3 — Map each site and flag the gaps
For every call site and config block from Phase 1, determine the hosted equivalent using the
mapping. Most calls map cleanly. Some don't — and those matter more than the mechanical edits.
Read references/gotchas.md and flag anything that needs a human decision: self-hosted/data-
residency setups, local model choices moving server-side, graph-memory usage, custom prompts, hot-
path calls that now make network round-trips, and existing locally-stored memories not carrying
over (data migration is out of scope unless the developer asks — note it, don't silently attempt it).
Phase 4 — Write the plan and stop
Write the full plan to MEM0_MIGRATION_PLAN.md at the repo root, following the structure in
references/plan-template.md. It must be concrete enough to execute from and honest about the gaps.
Then stop and present it for review. Do not start editing code in the same turn — the whole
point is that the developer reads and approves the plan first.
Phase 5 — Execute on approval (guided)
Once the developer approves (they may ask for changes first — incorporate them), execute the plan:
- Make the edits file by file, staying strictly within mem0 scope.
- Update dependencies and env (
MEM0_API_KEY; remove now-dead local-infra deps/services only if they exist solely for mem0 and you're confident). - Verify, mirroring how you'd confirm any backend swap:
- It imports / type-checks / byte-compiles.
- A smoke test exercises
add→search/get_all→delete_allagainst the hosted API with a realMEM0_API_KEY, and the app's own entry point still runs. - No local mem0 storage directory gets created anymore (e.g. a
.mem0/, local Qdrant path) — proof the memory really lives on the platform now.
- Report what changed, what was verified, and any flagged concerns the developer still needs to act on (e.g. configuring custom instructions in the dashboard, migrating old data).
Reference files
references/api-mapping.md— exact OSS→hosted method/param/return mapping for Python and TypeScript, plus dependency and env changes. Read during Phase 2–3.references/gotchas.md— the things that aren't a clean 1:1 and need a human decision. Read during Phase 3 so the plan's "Concerns" section is complete.references/plan-template.md— the exact structure forMEM0_MIGRATION_PLAN.md. Use in Phase 4.
04 同仓库更多 Skills
mem0
Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also triggers for Next.js apps needing memory-augmented AI. DO NOT TRIGGER when: user asks about direct Python/TS SDK calls without Vercel (use mem0 skill), or CLI terminal commands (use mem0-cli skill).
mem0-test-integration
Verify a Mem0 integration produced by /mem0-integrate. Runs in the same workspace on the same branch (loose coupling) — installs dependencies, runs the repo's native test suite, then exercises a real end-to-end smoke flow against the user's API key. Produces a scorecard. TRIGGER when: user has just run /mem0-integrate and says "verify", "test the integration", "run /mem0-test-integration", or when a .mem0-integration/ directory exists and tests have not been run yet on the current branch. DO NOT TRIGGER when: the user wants to run general project tests (defer to the repo's native test command), or when no prior /mem0-integrate run exists in the current branch (ask them to run /mem0-integrate first). This skill ONLY catches compile and runtime bugs by design. Logical integration errors — wrong data stored, wrong time retrieved, wrong user scoping — are on the human reviewer.
mem0-integrate
Integrate Mem0 into an existing repository using a goal-driven, TDD pipeline. Detects the repo's language automatically and asks the user to pick between Mem0 Platform (managed) and Mem0 Open Source (self-hosted). Writes failing tests before any implementation. Produces a local feature branch plus `.mem0-integration/` artifacts consumed by the paired verification skill. TRIGGER when: user says "integrate mem0", "add mem0 to this repo", "wire mem0 into <repo>", or asks how to add memory to an existing project. DO NOT TRIGGER when: the user wants general SDK usage (use skill:mem0), CLI usage (use skill:mem0-cli), or Vercel AI SDK (use skill:mem0-vercel-ai-sdk). After success, invoke skill:mem0-test-integration to verify in the same workspace (loose coupling).
mem0-cli
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0 config, mem0 import). Also triggers when query includes CLI flags like --user-id, --output, --json, --agent, or describes bash/zsh/terminal/shell usage. DO NOT TRIGGER when: user asks about programmatic SDK integration in Python/TS code (use mem0 skill), or Vercel AI SDK provider (use mem0-vercel-ai-sdk skill).
tour
Browses all stored memories grouped by category with full content display. Use when reviewing all memories, exploring stored knowledge, onboarding to a new session, or getting an overview of what the agent remembers.