mem0
The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
Runs with mockssource: GitHubhomepagePythonApache-2.0commit 8d6c00196657
Python, Apache-2.0 licensed. The project labels itself: agentic memory, agentic memory system, agents, ai, ai agents, chatgpt, genai and llm.
mem0 runs, with stand-ins for the services it depends on. An Argusic agent installed it in 2 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
mem0ai 2.2.0 installed and tested: 1210 tests passing across the core SDK, LLM providers, embeddings, client, telemetry, proxy, configs, and Qdrant vector store, with one bugfix in proxy/main.py to guard against UnboundLocalError on memories_text
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- mem0/proxy/main.py _format_query_with_memories uses memories_text before assignment when isinstance check fails after module reload5 minutes
- OPENROUTER_API_KEY env var set in container causes openai test to fail (expects api.openai.com)1 minute
- Install time
- 2 minutes
- Cold machine to finish
- 23 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- pytest on 37 test files: 1210 passed, 23 skipped, 0 failures in batches (configs+utils+llms+memory+embeddings+rerankers+qdrant+client+tests)
- Model tokens used
- 179,197
- Exact commit tested
- 8d6c00196657
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 1, run . The verdict above comes from a different attempt, so read this as one session and not as the current result. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
179,197 Everything works. Here's my report. **Install:** Created a virtual env with Python 3.12, installed the package with `pip install -e ".[… **Bug found and fixed:** In `mem0/proxy/main.py`, `_format_query_with_memories()` referenced `memor… **Verified by running all non-external-service tests:** - Core unit tests: 1064 passed, 23 skipped - Embeddings tests: 146 passed - Reranker tests: 146 passed (included above) - Qdrant vector store tests: 96 passed - **Total: 1210 tests passed, 23 skipped, 0 failures** (in batches, since the full suite OOMs in on… The 3 failures that appear only with `MEM0_TELEMETRY=false` (2 oss-to-platform, 1 async notices) ar… Vector store tests beyond Qdrant (Chroma, Milvus, Pinecone, Weaviate, etc.) require running externa…
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Installed in 2 minutes.
- Recovered from all 2 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed Apache-2.0, as reported by its host.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Runs with mocks | 92.00 | 0.30 | |
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.23 |
Topics (from GitHub)
agentic-memoryagentic-memory-systemagentsaiai-agentschatgptgenaillmlong-term-memorymemorymemory-managementpythonragstate-management
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/mem0)Questions
- Does mem0 run?
- mem0 runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 2 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test mem0?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 8d6c00196657. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test mem0?
- The run that produced this verdict cost $0.30: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does mem0 take to install?
- 2 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does mem0 need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing mem0?
- 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for mem0?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.