Boltz fails due to Colabfold MSA server failure, cryptic error message about decompress failing

[goddard@…]

The following bug report has been submitted:
Platform:        macOS-26.6-arm64-arm-64bit-Mach-O
ChimeraX Version: 1.13.dev202607242253 (2026-07-24 22:53:46 UTC)
Description
Boltz prediction Colabfold MSA server failed producing a cryptic error message.  The result was put in output.tar.gz by the Boltz code but what was returned was uncompressed JSON giving an error message from the server that a directory was not found.  Error is about not being able to uncompress output.tar.gz from the python tarfile module.  I've seen this error before.  Might be Boltz is not properly handling the Colabfold MSA server errors, or possibly the MSA server handling errors badly.

I think in all cases if I rerun it works.  But maybe that is because it doesn't rerun MSA and ChimeraX instead caches the bad non-existent MSA?  Should detect this error or fix my RBVI Boltz to handle it better and also make sure bad MSA is not cached.

Log:
UCSF ChimeraX version: 1.13.dev202607242253 (2026-07-24)  
© 2016-2026 Regents of the University of California. All rights reserved.  
How to cite UCSF ChimeraX  

> open 8ef5 format mmcif fromDatabase pdb

8ef5 title:  
Fentanyl-bound mu-opioid receptor-Gi complex [more info...]  
  
Chain information for 8ef5 #1  
---  
Chain | Description | UniProt  
A F | Guanine nucleotide-binding protein G(i) subunit alpha-1 | GNAI1_HUMAN 1-354  
B | Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1 | GBB1_RAT 2-340  
C | Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-2 | GBG2_BOVIN 1-68  
E | scFv16 |   
M R | Mu-type opioid receptor | OPRM_HUMAN 2-368  
  
Non-standard residues in 8ef5 #1  
---  
7V7 — N-phenyl-N-[1-(2-phenylethyl)piperidin-4-yl]propanamide  
CLR — cholesterol  
  

> ui tool show Boltz

> boltz predict protein /R name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 367 residues on gpu  
Using cached multiple sequence alignment
/Users/goddard/Downloads/ChimeraX/BoltzMSA/8ef5_R  
Sending job request to server (1694374 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job ocnrbz3f  
Confidence score 0.78, pTM 0.80, ipTM 0.00, pLDDT 0.78  
Boltz prediction completed in 31 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  
Please cite Boltz-1 Democratizing Biomolecular Interaction Modeling. BioRxiv
https://doi.org/10.1101/2024.11.19.624167 if you use these predictions.  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_2/boltz_results_8ef5_R/predictions/8ef5_R/8ef5_R_model_0.cif
> logInfo false

Matchmaker 8ef5, chain M (#1) with 8ef5_R_model_0.cif, chain R (#2), sequence
alignment score = 1822.5  
RMSD between 226 pruned atom pairs is 0.968 angstroms; (across all 288 pairs:
3.065)  
  

> hide #!1 models

Populating font family aliases took 48 ms. Replace uses of missing font family
"Ui-sans-serif" with one that exists to avoid this cost.  

> boltz predict protein #1/R ligandSmiles
> CCC(=O)N(C1CCN(CC1)CCC2=CC=CC=C2)C3=CC=CC=C3 name 8ef5_R_fent useServer true
> serverHost minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 367 residues, 1 ligands
CCC(=O)N(C1CCN(CC1)CCC2=CC=CC=C2)C3=CC=CC=C3 on gpu  
Using cached multiple sequence alignment
/Users/goddard/Downloads/ChimeraX/BoltzMSA/8ef5_R  
Sending job request to server (1694443 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job 35x3n5x5  
Confidence score 0.88, pTM 0.91, ipTM 0.97, pLDDT 0.86  
Boltz prediction completed in 31 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_fent/boltz_results_8ef5_R_fent/predictions/8ef5_R_fent/8ef5_R_fent_model_0.cif
> logInfo false

Matchmaker 8ef5, chain M (#1) with 8ef5_R_fent_model_0.cif, chain R (#3),
sequence alignment score = 1822.5  
RMSD between 225 pruned atom pairs is 1.015 angstroms; (across all 288 pairs:
3.099)  
  

> hide #2 models

> show #!1 models

> boltz predict protein #1/A name 8ef5_R_fent useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 354 residues on gpu  
Using multiple sequence alignment server https://api.colabfold.com  
Sending job request to server (617 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job 9su18hd5  
Running boltz prediction failed with exit code 1:  
command:  
/Users/goddard/boltz22/bin/boltz predict
/Users/goddard/Desktop/boltz_8ef5_R_fent_1/8ef5_R_fent.yaml --use_msa_server
--accelerator gpu --no_kernels  
stdout:  
Boltz version 2.2.0  
MSA server enabled: https://api.colabfold.com  
MSA server authentication: no credentials provided  
Checking input data.  
Processing 1 inputs with 1 threads.  
Generating MSA for 8ef5_R_fent.yaml with 1 protein entities.  
Calling MSA server for target 8ef5_R_fent with 1 sequences  
MSA server URL: https://api.colabfold.com  
MSA pairing strategy: greedy  
No authentication provided for MSA server  
Failed to process 8ef5_R_fent.yaml. Skipping. Error: file could not be opened
successfully:  
\- method gz: ReadError('not a gzip file')  
\- method bz2: ReadError('not a bzip2 file')  
\- method xz: ReadError('not an lzma file')  
\- method tar: ReadError('truncated header').  
  
stderr:  
  
0%| | 0/1 [00:00<?, ?it/s]  
  
0%| | 0/150 [elapsed: 00:00 remaining: ?][A  
  
SUBMIT: 0%| | 0/150 [elapsed: 00:00 remaining: ?][A  
  
COMPLETE: 0%| | 0/150 [elapsed: 00:01 remaining: ?][A  
  
COMPLETE: 100%|██████████| 150/150 [elapsed: 00:01 remaining: 00:00][A  
COMPLETE: 100%|██████████| 150/150 [elapsed: 00:01 remaining: 00:00]  
Traceback (most recent call last):  
File "/home/goddard/boltz_py311/lib/python3.11/site-packages/boltz/main.py",
line 581, in process_input  
compute_msa(  
File "/home/goddard/boltz_py311/lib/python3.11/site-packages/boltz/main.py",
line 477, in compute_msa  
unpaired_msa = run_mmseqs2(  
^^^^^^^^^^^^  
File "/home/goddard/boltz_py311/lib/python3.11/site-
packages/boltz/data/msa/mmseqs2.py", line 266, in run_mmseqs2  
with tarfile.open(tar_gz_file) as tar_gz:  
^^^^^^^^^^^^^^^^^^^^^^^^^  
File "/home/goddard/boltz_py311/lib/python3.11/tarfile.py", line 1861, in open  
raise ReadError(f"file could not be opened
successfully:\n{error_msgs_summary}")  
tarfile.ReadError: file could not be opened successfully:  
\- method gz: ReadError('not a gzip file')  
\- method bz2: ReadError('not a bzip2 file')  
\- method xz: ReadError('not an lzma file')  
\- method tar: ReadError('truncated header')  
  
100%|██████████| 1/1 [00:01<00:00, 1.27s/it]  
100%|██████████| 1/1 [00:01<00:00, 1.27s/it]  
Using bfloat16 Automatic Mixed Precision (AMP)  
GPU available: True (cuda), used: True  
TPU available: False, using: 0 TPU cores  
HPU available: False, using: 0 HPUs  
/home/goddard/boltz_py311/lib/python3.11/site-
packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:76:
Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the
`pytorch_lightning` package, due to potential conflicts with other packages in
the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the
default logger, unless the `tensorboard` or `tensorboardX` packages are found.
Please `pip install lightning[extra]` or one of them to enable TensorBoard
support by default  
  

> boltz predict protein #1/R name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 367 residues on gpu  
Using cached multiple sequence alignment
/Users/goddard/Downloads/ChimeraX/BoltzMSA/8ef5_R  
Sending job request to server (1694374 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job tiq8tr8h  
Confidence score 0.78, pTM 0.78, ipTM 0.00, pLDDT 0.78  
Boltz prediction completed in 31 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_3/boltz_results_8ef5_R/predictions/8ef5_R/8ef5_R_model_0.cif
> logInfo false

Matchmaker 8ef5, chain M (#1) with 8ef5_R_model_0.cif, chain R (#4), sequence
alignment score = 1815.3  
RMSD between 214 pruned atom pairs is 0.999 angstroms; (across all 288 pairs:
3.171)  
  

> boltz predict protein #1/A name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 354 residues on gpu  
Using multiple sequence alignment server https://api.colabfold.com  
Sending job request to server (602 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job c3mvt174  
Confidence score 0.86, pTM 0.83, ipTM 0.00, pLDDT 0.87  
Boltz prediction completed in 30 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_4/boltz_results_8ef5_R/predictions/8ef5_R/8ef5_R_model_0.cif
> logInfo false

Matchmaker 8ef5, chain A (#1) with 8ef5_R_model_0.cif, chain A (#5), sequence
alignment score = 1573.7  
RMSD between 138 pruned atom pairs is 1.079 angstroms; (across all 225 pairs:
11.099)  
  

> boltz predict protein #1/B name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 353 residues on gpu  
Using multiple sequence alignment server https://api.colabfold.com  
Sending job request to server (596 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job 3lxs0o21  
Confidence score 0.93, pTM 0.90, ipTM 0.00, pLDDT 0.94  
Boltz prediction completed in 90 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_5/boltz_results_8ef5_R/predictions/8ef5_R/8ef5_R_model_0.cif
> logInfo false

Matchmaker 8ef5, chain B (#1) with 8ef5_R_model_0.cif, chain B (#6), sequence
alignment score = 1799.5  
RMSD between 326 pruned atom pairs is 0.714 angstroms; (across all 336 pairs:
0.973)  
  

> boltz predict protein #1/C name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 68 residues on gpu  
Using multiple sequence alignment server https://api.colabfold.com  
Sending job request to server (431 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job 6y8xywms  
Running boltz prediction failed with exit code 1:  
command:  
/Users/goddard/boltz22/bin/boltz predict
/Users/goddard/Desktop/boltz_8ef5_R_6/8ef5_R.yaml --use_msa_server
--accelerator gpu --no_kernels  
stdout:  
Boltz version 2.2.0  
MSA server enabled: https://api.colabfold.com  
MSA server authentication: no credentials provided  
Checking input data.  
Processing 1 inputs with 1 threads.  
Generating MSA for 8ef5_R.yaml with 1 protein entities.  
Calling MSA server for target 8ef5_R with 1 sequences  
MSA server URL: https://api.colabfold.com  
MSA pairing strategy: greedy  
No authentication provided for MSA server  
Failed to process 8ef5_R.yaml. Skipping. Error: file could not be opened
successfully:  
\- method gz: ReadError('not a gzip file')  
\- method bz2: ReadError('not a bzip2 file')  
\- method xz: ReadError('not an lzma file')  
\- method tar: ReadError('truncated header').  
  
stderr:  
  
0%| | 0/1 [00:00<?, ?it/s]  
  
0%| | 0/150 [elapsed: 00:00 remaining: ?][A  
  
SUBMIT: 0%| | 0/150 [elapsed: 00:00 remaining: ?][A  
  
COMPLETE: 0%| | 0/150 [elapsed: 00:01 remaining: ?][A  
  
COMPLETE: 100%|██████████| 150/150 [elapsed: 00:01 remaining: 00:00][A  
COMPLETE: 100%|██████████| 150/150 [elapsed: 00:01 remaining: 00:00]  
Traceback (most recent call last):  
File "/home/goddard/boltz_py311/lib/python3.11/site-packages/boltz/main.py",
line 581, in process_input  
compute_msa(  
File "/home/goddard/boltz_py311/lib/python3.11/site-packages/boltz/main.py",
line 477, in compute_msa  
unpaired_msa = run_mmseqs2(  
^^^^^^^^^^^^  
File "/home/goddard/boltz_py311/lib/python3.11/site-
packages/boltz/data/msa/mmseqs2.py", line 266, in run_mmseqs2  
with tarfile.open(tar_gz_file) as tar_gz:  
^^^^^^^^^^^^^^^^^^^^^^^^^  
File "/home/goddard/boltz_py311/lib/python3.11/tarfile.py", line 1861, in open  
raise ReadError(f"file could not be opened
successfully:\n{error_msgs_summary}")  
tarfile.ReadError: file could not be opened successfully:  
\- method gz: ReadError('not a gzip file')  
\- method bz2: ReadError('not a bzip2 file')  
\- method xz: ReadError('not an lzma file')  
\- method tar: ReadError('truncated header')  
  
100%|██████████| 1/1 [00:01<00:00, 1.22s/it]  
100%|██████████| 1/1 [00:01<00:00, 1.22s/it]  
Using bfloat16 Automatic Mixed Precision (AMP)  
GPU available: True (cuda), used: True  
TPU available: False, using: 0 TPU cores  
HPU available: False, using: 0 HPUs  
/home/goddard/boltz_py311/lib/python3.11/site-
packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:76:
Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the
`pytorch_lightning` package, due to potential conflicts with other packages in
the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the
default logger, unless the `tensorboard` or `tensorboardX` packages are found.
Please `pip install lightning[extra]` or one of them to enable TensorBoard
support by default  
  

> boltz predict protein #1/C name 8ef5_R useServer true serverHost
> minsky.cgl.ucsf.edu serverPort 30172

Running Boltz prediction of protein with 68 residues on gpu  
Using multiple sequence alignment server https://api.colabfold.com  
Sending job request to server (431 bytes)  
Server minsky.cgl.ucsf.edu:30172 queued job k76027u_  
Confidence score 0.79, pTM 0.48, ipTM 0.00, pLDDT 0.87  
Boltz prediction completed in 20 seconds (start boltz 0 sec, sequence search 0
sec, load weights 0 sec, structure inference 0 sec)  

> open
> /Users/goddard/Desktop/boltz_8ef5_R_7/boltz_results_8ef5_R/predictions/8ef5_R/8ef5_R_model_0.cif
> logInfo false

Matchmaker 8ef5, chain C (#1) with 8ef5_R_model_0.cif, chain C (#7), sequence
alignment score = 300.8  
RMSD between 33 pruned atom pairs is 1.043 angstroms; (across all 56 pairs:
8.368)  
  




OpenGL version: 4.1 Metal - 90.5
OpenGL renderer: Apple M4
OpenGL vendor: Apple

Python: 3.14.6
Locale: C.UTF-8
Qt version: PyQt6 6.10.2, Qt 6.10.0
Qt runtime version: 6.10.2
Qt platform: cocoa
Hardware:

    Hardware Overview:

      Model Name: MacBook Air
      Model Identifier: Mac16,12
      Model Number: MW0W3LL/A
      Chip: Apple M4
      Total Number of Cores: 10 (4 Performance and 6 Efficiency)
      Memory: 16 GB
      System Firmware Version: 18000.161.9
      OS Loader Version: 18000.161.9

Software:

    System Software Overview:

      System Version: macOS 26.6 (25G72)
      Kernel Version: Darwin 25.6.0
      Time since boot: 1 day, 59 minutes

Graphics/Displays:

    Apple M4:

      Chipset Model: Apple M4
      Type: GPU
      Bus: Built-In
      Total Number of Cores: 8
      Vendor: Apple (0x106b)
      Metal Support: Metal 4
      Displays:
        Color LCD:
          Display Type: Built-in Liquid Retina Display
          Resolution: 2560 x 1664 Retina
          Main Display: Yes
          Mirror: Off
          Online: Yes
          Automatically Adjust Brightness: Yes
          Connection Type: Internal


Installed Packages:
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    aiohappyeyeballs: 2.7.1
    aiohttp: 3.11.1
    aiosignal: 1.4.0
    alabaster: 1.0.0
    annotated-types: 0.8.0
    anyio: 4.14.2
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    appnope: 0.1.4
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    attrs: 26.1.0
    babel: 2.18.0
    beautifulsoup4: 4.13.5
    blockdiag: 3.0.0
    blosc2: 4.9.1
    build: 1.5.0
    certifi: 2026.7.22
    cffi: 2.1.0
    cftime: 1.6.5
    charset-normalizer: 3.4.9
    ChimeraX-AddCharge: 1.5.20
    ChimeraX-AddH: 2.3.1
    ChimeraX-AlignmentAlgorithms: 2.0.2
    ChimeraX-AlignmentHdrs: 3.6.2
    ChimeraX-AlignmentMatrices: 2.1
    ChimeraX-Alignments: 3.2.2
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    ChimeraX-AxesPlanes: 2.4
    ChimeraX-BasicActions: 1.1.3
    ChimeraX-BILD: 1.0
    ChimeraX-BlastProtein: 3.0.0
    ChimeraX-Boltz: 1.1
    ChimeraX-BondRot: 2.0.4
    ChimeraX-BugReporter: 1.0.2
    ChimeraX-BuildStructure: 2.13.1
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    ChimeraX-Shell: 1.0.1
    ChimeraX-Shortcuts: 1.2.1
    ChimeraX-ShowSequences: 1.0.3
    ChimeraX-SideView: 1.0.1
    ChimeraX-SimilarStructures: 1.0.1
    ChimeraX-Smiles: 2.1.2
    ChimeraX-SmoothLines: 1.0
    ChimeraX-SNFG: 1.0
    ChimeraX-SpaceNavigator: 1.0
    ChimeraX-StdCommands: 1.20
    ChimeraX-STL: 1.0.1
    ChimeraX-Storm: 1.0
    ChimeraX-StructMeasure: 1.2.1
    ChimeraX-Struts: 1.0.1
    ChimeraX-Surface: 1.0.1
    ChimeraX-SwapAA: 2.0.1
    ChimeraX-SwapRes: 2.5.3
    ChimeraX-TapeMeasure: 1.0
    ChimeraX-TaskManager: 1.0
    ChimeraX-Test: 1.0
    ChimeraX-Toolbar: 1.2.4
    ChimeraX-ToolshedUtils: 1.2.4
    ChimeraX-Topography: 1.0
    ChimeraX-ToQuest: 1.0
    ChimeraX-Tug: 1.0.1
    ChimeraX-UI: 1.53.2
    ChimeraX-Umap: 1.0
    ChimeraX-uniprot: 2.3.2
    ChimeraX-UnitCell: 1.0.1
    ChimeraX-ViewDock: 1.6.5
    ChimeraX-VIPERdb: 1.0
    ChimeraX-Vive: 1.1
    ChimeraX-VolumeMenu: 1.0.1
    ChimeraX-vrml: 1.0
    ChimeraX-VTK: 1.0
    ChimeraX-WavefrontOBJ: 1.0
    ChimeraX-WebCam: 1.0.2
    ChimeraX-WebServices: 1.1.5
    ChimeraX-Zone: 1.0.1
    click: 8.4.2
    colorama: 0.4.6
    comm: 0.2.3
    contourpy: 1.3.3
    coverage: 7.15.2
    cryptography: 49.0.0
    cxservices: 1.2.3
    cycler: 0.12.1
    Cython: 3.2.4
    debugpy: 1.8.21
    decorator: 5.3.1
    docutils: 0.21.2
    executing: 2.2.1
    filelock: 3.19.1
    fonttools: 4.63.0
    frozenlist: 1.8.0
    funcparserlib: 1.0.1
    glfw: 2.10.2
    grako: 3.16.5
    h11: 0.16.0
    h2: 4.4.0
    h5py: 3.16.0
    hpack: 4.2.0
    html2text: 2025.4.15
    httpcore: 1.0.9
    httpx: 0.28.1
    httpx-sse: 0.4.3
    hyperframe: 6.1.0
    idna: 3.18
    ihm: 2.2
    imagecodecs: 2026.6.26
    imagesize: 2.0.0
    iniconfig: 2.3.0
    ipykernel: 7.3.0
    ipython: 9.14.1
    ipython_pygments_lexers: 1.1.1
    jedi: 0.20.0
    Jinja2: 3.1.6
    jsonschema: 4.26.0
    jsonschema-specifications: 2025.9.1
    jupyter_client: 8.9.1
    jupyter_core: 5.9.1
    kiwisolver: 1.5.0
    line_profiler: 5.0.0
    lxml: 6.0.2
    lz4: 4.4.5
    Markdown: 3.8.2
    markdown-it-py: 4.2.0
    MarkupSafe: 3.0.3
    matplotlib: 3.10.7
    matplotlib-inline: 0.2.2
    mcp: 1.28.1
    mdurl: 0.1.2
    msgpack: 1.1.1
    multidict: 6.7.1
    ndindex: 1.10.1
    nest-asyncio2: 1.7.2
    netCDF4: 1.7.4
    networkx: 3.3
    numexpr: 2.14.2
    numpy: 2.4.6
    OpenMM: 8.4.0
    openvr: 1.26.701
    packaging: 25.0
    ParmEd: 4.2.2
    parso: 0.8.7
    pep517: 0.13.1
    pexpect: 4.9.0
    pickleshare: 0.7.5
    pillow: 12.3.0
    pip: 26.1.2
    pkginfo: 1.12.1.2
    platformdirs: 4.11.0
    pluggy: 1.6.0
    prompt_toolkit: 3.0.53
    propcache: 0.5.2
    psutil: 7.0.0
    ptyprocess: 0.7.0
    pure_eval: 0.2.3
    py-cpuinfo: 9.0.0
    pybind11: 3.0.1
    pycollada: 0.8
    pycparser: 3.0
    pydantic: 2.13.4
    pydantic-settings: 2.14.2
    pydantic_core: 2.46.4
    pydata-sphinx-theme: 0.20.0
    Pygments: 2.18.0
    PyJWT: 2.13.0
    pynmrstar: 3.5.1
    PyOpenGL: 3.1.10
    PyOpenGL-accelerate: 3.1.10
    pyopenxr: 1.1.4501
    pyparsing: 3.3.2
    pyproject_hooks: 1.2.0
    PyQt6-commercial: 6.10.2
    PyQt6-Qt6: 6.10.2
    PyQt6-WebEngine-commercial: 6.10.0
    PyQt6-WebEngine-Qt6: 6.10.2
    PyQt6_sip: 13.10.3
    pytest: 9.1.1
    pytest-cov: 7.1.0
    python-dateutil: 2.9.0.post0
    python-dotenv: 1.2.2
    python-multipart: 0.0.32
    pyzmq: 27.1.0
    qtconsole: 5.7.2
    QtPy: 2.4.3
    qtshim: 1.2.2
    RandomWords: 0.4.0
    referencing: 0.37.0
    requests: 2.32.5
    rich: 15.0.0
    roman-numerals: 4.1.0
    rpds-py: 2026.6.3
    scipy: 1.18.0
    setuptools: 82.0.1
    sfftk-rw: 0.8.1
    six: 1.17.0
    snowballstemmer: 3.1.1
    sortedcontainers: 2.4.0
    soupsieve: 2.9.1
    Sphinx: 9.0.4
    sphinx-autodoc-typehints: 3.6.1
    sphinxcontrib-applehelp: 2.0.0
    sphinxcontrib-blockdiag: 3.0.0
    sphinxcontrib-devhelp: 2.0.0
    sphinxcontrib-htmlhelp: 2.1.0
    sphinxcontrib-jsmath: 1.0.1
    sphinxcontrib-qthelp: 2.0.0
    sphinxcontrib-serializinghtml: 2.0.0
    sse-starlette: 3.4.6
    stack-data: 0.6.3
    starlette: 1.3.1
    superqt: 0.7.6
    tables: 3.11.1
    threadpoolctl: 3.6.0
    tifffile: 2025.3.13
    tinyarray: 1.2.5
    tornado: 6.5.7
    tqdm: 4.69.1
    traitlets: 5.15.1
    typing-inspection: 0.4.2
    typing_extensions: 4.16.0
    urllib3: 2.7.0
    uv: 0.11.26
    uvicorn: 0.51.0
    wcwidth: 0.8.2
    webcolors: 24.11.1
    wheel: 0.47.0
    wheel-filename: 1.4.2
    yarl: 1.24.5

[Tom Goddard]

This is the file returned by Colabfold MSA server, not really tar.gz, really plain JSON containing an error message.

[Tom Goddard]

Here is the JSON found in the non-tar file out.tar.gz giving an error message on the MSA server:

{"message":"Route GET:/compute/v1/msa/result/download/1e30d8814ed4786493d3bffb781bdb19f7434638c62f8cee2416775363d929cb not found","error":"Not Found","statusCode":404}

[Tom Goddard]

Reading the Boltz mmseqs2.py code it appears the Colabfold MSA server reports the jobs completed successfully. This looks like a bug in the MSA server. Probably the best way to handle it is to detect "tarfile.ReadError: file could not be opened successfully" in ChimeraX and report that this is a probable MSA server failure and rerunning the prediction usually succeeds.

[Tom Goddard]

Fixed.

Added clear error message about what went wrong. Tested with several chains of PDB 9s2g and MSA server failed on third chain tried K and rerunning then succeeded, and cached MSA looked fine with 101 matching sequences.