py-xiaozhi
Open-source AI assistant ecosystem with MCP integrations, multimodal workflows, IoT support, and cross-platform voice interaction.
Runs with mockssource: GitHubhomepagePythonMITcommit 9bfc807d368c
Python, MIT licensed. The project labels itself: cross platform, edge computing, embodied ai, esp32, esp32 s3, iot, mcp and mcp client.
py-xiaozhi runs, with stand-ins for the services it depends on. An Argusic agent installed it in 3 minutes and hit 6 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
80 test cases pass in the project test suite; CLI help and CLI mode launch successfully
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.
- pip install failed with 'externally-managed-environment' (PEP 668)1 minute
- evdev wheel build failed: fatal error: Python.h: No such file or directory (python3-dev missing from container)1 minute
- pynput requires evdev which fails to build from source1 minute
- PortAudio library not found by sounddevice at import1 minute
- PySide6 missing for GUI-related test imports1 minute
- hatchling missing at editable-install metadata generation1 minute
- Install time
- 3 minutes
- Cold machine to finish
- 16 minutes
- Errors hit and fixed
- 6 hit, 6 fixed with no human help
- How the result was proved
- pytest tests/ exited 0, 80 passed; main.py --help printed usage; main.py --mode cli --skip-activation launched and logged config initialization
- Model tokens used
- 151,282
- Exact commit tested
- 9bfc807d368c
- 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
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
exec
/bin/sh -lc 'cd /work/repo && export LD_LIBRARY_PATH=/work/repo/.venv/lib && export QT_QPA_PLATFORM…
succeeded in 1523ms:
tests/test_resilience_fixes.py::test_event_bus_isolates_handler_errors PASSED [ 18%]
tests/test_resilience_fixes.py::test_plugin_mark_failed_skips_notify_only_for_failed PASSED [ 23%]
============================== 80 passed in 1.20s ==============================
Here is the final report.
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 3, "er…
tokens used
151,282
Here is the final report.
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 3, "er…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 3 minutes.
- Recovered from all 6 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed MIT, as reported by its host.
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.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
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 | 1/3 | Runs with mocks | 92.00 | 0.06 |
Topics (from GitHub)
cross-platformedge-computingembodied-aiesp32esp32-s3iotmcpmcp-clientmcp-servermulti-modalpythonraspberry-piroboticsvoice-assistantxiaozhi-esp32
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/py-xiaozhi)Questions
- Does py-xiaozhi run?
- py-xiaozhi runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 3 minutes, hitting 6 errors on the way, and recorded the session.
- How did Argusic test py-xiaozhi?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 9bfc807d368c. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test py-xiaozhi?
- The run that produced this verdict cost $0.06: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does py-xiaozhi take to install?
- 3 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 py-xiaozhi need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing py-xiaozhi?
- 6 things broke in the recorded run, and 6 were fixed without human help. Each one, and the time it cost, is listed on this page.
- Where is the evidence for py-xiaozhi?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.