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python后端源码方式启动报错Segmentation fault #691

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opened 2026-02-21 17:28:02 -05:00 by yindo · 4 comments
yindo commented 2026-02-21 17:28:02 -05:00
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Originally created by @TomorJM on GitHub (Nov 14, 2023).

Dify version

0.3.21

Cloud or Self Hosted

Self Hosted

Steps to reproduce

环境
Python 3.10.13
Flask 2.3.3
Werkzeug 2.3.7

正常按照文档步骤进行源码方式启动, 启动报错。
正常看不到堆栈, 仅在app.py添加以下代码看到堆栈, 截图如下

import faulthandler
faulthandler.enable()

image

✔️ Expected Behavior

服务正常运行

❌ Actual Behavior

(dify) ➜  api git:(main) ✗ flask run --host 0.0.0.0 --port=5001 --debug 
 * Debug mode: on
INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
 * Running on all addresses (0.0.0.0)
 * Running on http://127.0.0.1:5001
 * Running on http://30.5.187.152:5001
INFO:werkzeug:Press CTRL+C to quit
INFO:werkzeug: * Restarting with stat
WARNING:werkzeug: * Debugger is active!
INFO:werkzeug: * Debugger PIN: 233-829-709
Fatal Python error: Segmentation fault

Thread 0x00007000102fe000 (most recent call first):
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 39 in acquire_with_timeout
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 99 in wait
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 220 in get
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/threadpool.py", line 195 in run

Current thread 0x000000011a7ace00 (most recent call first):
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/select.py", line 314 in poll
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/selectors.py", line 416 in select
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/socketserver.py", line 232 in serve_forever
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/werkzeug/serving.py", line 804 in serve_forever
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 953 in run
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 1016 in _bootstrap_inner
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 973 in _bootstrap

Extension modules: markupsafe._speedups, greenlet._greenlet, zope.interface._zope_interface_coptimizations, gevent.libev.corecext, gevent._gevent_c_greenlet_primitives, gevent._gevent_c_hub_local, gevent._gevent_c_waiter, gevent._gevent_c_hub_primitives, gevent._gevent_c_ident, gevent._gevent_cgreenlet, gevent._gevent_c_abstract_linkable, gevent._gevent_c_semaphore, gevent._gevent_clocal, gevent._gevent_cevent, gevent._gevent_cqueue, pydantic.typing, pydantic.errors, pydantic.version, pydantic.utils, pydantic.class_validators, pydantic.config, pydantic.color, pydantic.datetime_parse, pydantic.validators, pydantic.networks, pydantic.types, pydantic.json, pydantic.error_wrappers, pydantic.fields, pydantic.parse, pydantic.schema, pydantic.main, pydantic.dataclasses, pydantic.annotated_types, pydantic.decorator, pydantic.env_settings, pydantic.tools, pydantic, yaml._yaml, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, charset_normalizer.md, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, sqlalchemy.cimmutabledict, sqlalchemy.cprocessors, sqlalchemy.cresultproxy, _cffi_backend, numexpr.interpreter, gevent._gevent_c_imap, regex._regex, grpc._cython.cygrpc, google._upb._message, lxml._elementpath, lxml.etree, PIL._imaging, psycopg2._psycopg, lxml.html.clean, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.tslib, pandas._libs.lib, pandas._libs.hashing, pandas._libs.ops, pandas._libs.arrays, pandas._libs.index, pandas._libs.join, pandas._libs.sparse, pandas._libs.reduction, pandas._libs.indexing, pandas._libs.internals, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.tslibs.strptime, pandas._libs.groupby, pandas._libs.testing, pandas._libs.parsers, pandas._libs.json, sklearn.__check_build._check_build, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.sparse.linalg._isolve._iterative, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.linalg._flinalg, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, sklearn.utils.murmurhash, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.optimize._minpack2, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize.__nnls, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap, scipy.optimize._direct, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.special.cython_special, scipy.stats._stats, scipy.stats.beta_ufunc, scipy.stats._boost.beta_ufunc, scipy.stats.binom_ufunc, scipy.stats._boost.binom_ufunc, scipy.stats.nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, scipy.stats.hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats.ncf_ufunc, scipy.stats._boost.ncf_ufunc, scipy.stats.ncx2_ufunc, scipy.stats._boost.ncx2_ufunc, scipy.stats.nct_ufunc, scipy.stats._boost.nct_ufunc, scipy.stats.skewnorm_ufunc, scipy.stats._boost.skewnorm_ufunc, scipy.stats.invgauss_ufunc, scipy.stats._boost.invgauss_ufunc, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, scipy.stats._biasedurn, scipy.stats._levy_stable.levyst, scipy.stats._stats_pythran, scipy._lib._uarray._uarray, scipy.stats._statlib, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont, sklearn.utils._isfinite, sklearn.utils._openmp_helpers, sklearn.utils._logistic_sigmoid, sklearn.utils.sparsefuncs_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.utils._typedefs, sklearn.utils._readonly_array_wrapper, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._base, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.utils._random, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.linear_model._cd_fast, sklearn._loss._loss, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.decomposition._online_lda_fast, sklearn._isotonic, sklearn.manifold._utils, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne (total: 261)
Fatal Python error: Segmentation fault

Current thread 0x00000001167fbe00 (most recent call first):
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/os.py", line 247 in _on_child
  File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/hub.py", line 647 in run

Extension modules: markupsafe._speedups, greenlet._greenlet, zope.interface._zope_interface_coptimizations, gevent.libev.corecext, gevent._gevent_c_greenlet_primitives, gevent._gevent_c_hub_local, gevent._gevent_c_waiter, gevent._gevent_c_hub_primitives, gevent._gevent_c_ident, gevent._gevent_cgreenlet, gevent._gevent_c_abstract_linkable, gevent._gevent_c_semaphore, gevent._gevent_clocal, gevent._gevent_cevent, gevent._gevent_cqueue, pydantic.typing, pydantic.errors, pydantic.version, pydantic.utils, pydantic.class_validators, pydantic.config, pydantic.color, pydantic.datetime_parse, pydantic.validators, pydantic.networks, pydantic.types, pydantic.json, pydantic.error_wrappers, pydantic.fields, pydantic.parse, pydantic.schema, pydantic.main, pydantic.dataclasses, pydantic.annotated_types, pydantic.decorator, pydantic.env_settings, pydantic.tools, pydantic, yaml._yaml, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, charset_normalizer.md, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, sqlalchemy.cimmutabledict, sqlalchemy.cprocessors, sqlalchemy.cresultproxy, _cffi_backend, numexpr.interpreter, gevent._gevent_c_imap, regex._regex, grpc._cython.cygrpc, google._upb._message, lxml._elementpath, lxml.etree, PIL._imaging, psycopg2._psycopg, lxml.html.clean, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.tslib, pandas._libs.lib, pandas._libs.hashing, pandas._libs.ops, pandas._libs.arrays, pandas._libs.index, pandas._libs.join, pandas._libs.sparse, pandas._libs.reduction, pandas._libs.indexing, pandas._libs.internals, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.tslibs.strptime, pandas._libs.groupby, pandas._libs.testing, pandas._libs.parsers, pandas._libs.json, sklearn.__check_build._check_build, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.sparse.linalg._isolve._iterative, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.linalg._flinalg, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, sklearn.utils.murmurhash, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.optimize._minpack2, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize.__nnls, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap, scipy.optimize._direct, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.special.cython_special, scipy.stats._stats, scipy.stats.beta_ufunc, scipy.stats._boost.beta_ufunc, scipy.stats.binom_ufunc, scipy.stats._boost.binom_ufunc, scipy.stats.nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, scipy.stats.hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats.ncf_ufunc, scipy.stats._boost.ncf_ufunc, scipy.stats.ncx2_ufunc, scipy.stats._boost.ncx2_ufunc, scipy.stats.nct_ufunc, scipy.stats._boost.nct_ufunc, scipy.stats.skewnorm_ufunc, scipy.stats._boost.skewnorm_ufunc, scipy.stats.invgauss_ufunc, scipy.stats._boost.invgauss_ufunc, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, scipy.stats._biasedurn, scipy.stats._levy_stable.levyst, scipy.stats._stats_pythran, scipy._lib._uarray._uarray, scipy.stats._statlib, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont, sklearn.utils._isfinite, sklearn.utils._openmp_helpers, sklearn.utils._logistic_sigmoid, sklearn.utils.sparsefuncs_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.utils._typedefs, sklearn.utils._readonly_array_wrapper, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._base, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.utils._random, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.linear_model._cd_fast, sklearn._loss._loss, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.decomposition._online_lda_fast, sklearn._isotonic, sklearn.manifold._utils, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne (total: 261)
[1]    2275 segmentation fault  flask run --host 0.0.0.0 --port=5001 --debug
Originally created by @TomorJM on GitHub (Nov 14, 2023). ### Dify version 0.3.21 ### Cloud or Self Hosted Self Hosted ### Steps to reproduce ``` 环境 Python 3.10.13 Flask 2.3.3 Werkzeug 2.3.7 ``` 正常按照[文档](https://docs.dify.ai/v/zh-hans/getting-started/install-self-hosted/local-source-code#fu-wu-duan-bu-shu)步骤进行源码方式启动, 启动报错。 正常看不到堆栈, 仅在app.py添加以下代码看到堆栈, 截图如下 ``` import faulthandler faulthandler.enable() ``` ![image](https://github.com/langgenius/dify/assets/11410549/031c33f4-7612-4999-9bda-26e7af362765) ### ✔️ Expected Behavior 服务正常运行 ### ❌ Actual Behavior ``` (dify) ➜ api git:(main) ✗ flask run --host 0.0.0.0 --port=5001 --debug * Debug mode: on INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on all addresses (0.0.0.0) * Running on http://127.0.0.1:5001 * Running on http://30.5.187.152:5001 INFO:werkzeug:Press CTRL+C to quit INFO:werkzeug: * Restarting with stat WARNING:werkzeug: * Debugger is active! INFO:werkzeug: * Debugger PIN: 233-829-709 Fatal Python error: Segmentation fault Thread 0x00007000102fe000 (most recent call first): File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 39 in acquire_with_timeout File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 99 in wait File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/_threading.py", line 220 in get File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/threadpool.py", line 195 in run Current thread 0x000000011a7ace00 (most recent call first): File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/select.py", line 314 in poll File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/selectors.py", line 416 in select File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/socketserver.py", line 232 in serve_forever File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/werkzeug/serving.py", line 804 in serve_forever File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 953 in run File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 1016 in _bootstrap_inner File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/threading.py", line 973 in _bootstrap Extension modules: markupsafe._speedups, greenlet._greenlet, zope.interface._zope_interface_coptimizations, gevent.libev.corecext, gevent._gevent_c_greenlet_primitives, gevent._gevent_c_hub_local, gevent._gevent_c_waiter, gevent._gevent_c_hub_primitives, gevent._gevent_c_ident, gevent._gevent_cgreenlet, gevent._gevent_c_abstract_linkable, gevent._gevent_c_semaphore, gevent._gevent_clocal, gevent._gevent_cevent, gevent._gevent_cqueue, pydantic.typing, pydantic.errors, pydantic.version, pydantic.utils, pydantic.class_validators, pydantic.config, pydantic.color, pydantic.datetime_parse, pydantic.validators, pydantic.networks, pydantic.types, pydantic.json, pydantic.error_wrappers, pydantic.fields, pydantic.parse, pydantic.schema, pydantic.main, pydantic.dataclasses, pydantic.annotated_types, pydantic.decorator, pydantic.env_settings, pydantic.tools, pydantic, yaml._yaml, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, charset_normalizer.md, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, sqlalchemy.cimmutabledict, sqlalchemy.cprocessors, sqlalchemy.cresultproxy, _cffi_backend, numexpr.interpreter, gevent._gevent_c_imap, regex._regex, grpc._cython.cygrpc, google._upb._message, lxml._elementpath, lxml.etree, PIL._imaging, psycopg2._psycopg, lxml.html.clean, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.tslib, pandas._libs.lib, pandas._libs.hashing, pandas._libs.ops, pandas._libs.arrays, pandas._libs.index, pandas._libs.join, pandas._libs.sparse, pandas._libs.reduction, pandas._libs.indexing, pandas._libs.internals, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.tslibs.strptime, pandas._libs.groupby, pandas._libs.testing, pandas._libs.parsers, pandas._libs.json, sklearn.__check_build._check_build, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.sparse.linalg._isolve._iterative, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.linalg._flinalg, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, sklearn.utils.murmurhash, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.optimize._minpack2, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize.__nnls, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap, scipy.optimize._direct, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.special.cython_special, scipy.stats._stats, scipy.stats.beta_ufunc, scipy.stats._boost.beta_ufunc, scipy.stats.binom_ufunc, scipy.stats._boost.binom_ufunc, scipy.stats.nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, scipy.stats.hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats.ncf_ufunc, scipy.stats._boost.ncf_ufunc, scipy.stats.ncx2_ufunc, scipy.stats._boost.ncx2_ufunc, scipy.stats.nct_ufunc, scipy.stats._boost.nct_ufunc, scipy.stats.skewnorm_ufunc, scipy.stats._boost.skewnorm_ufunc, scipy.stats.invgauss_ufunc, scipy.stats._boost.invgauss_ufunc, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, scipy.stats._biasedurn, scipy.stats._levy_stable.levyst, scipy.stats._stats_pythran, scipy._lib._uarray._uarray, scipy.stats._statlib, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont, sklearn.utils._isfinite, sklearn.utils._openmp_helpers, sklearn.utils._logistic_sigmoid, sklearn.utils.sparsefuncs_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.utils._typedefs, sklearn.utils._readonly_array_wrapper, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._base, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.utils._random, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.linear_model._cd_fast, sklearn._loss._loss, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.decomposition._online_lda_fast, sklearn._isotonic, sklearn.manifold._utils, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne (total: 261) Fatal Python error: Segmentation fault Current thread 0x00000001167fbe00 (most recent call first): File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/os.py", line 247 in _on_child File "/Users/jaimezhang/anaconda3/envs/dify/lib/python3.10/site-packages/gevent/hub.py", line 647 in run Extension modules: markupsafe._speedups, greenlet._greenlet, zope.interface._zope_interface_coptimizations, gevent.libev.corecext, gevent._gevent_c_greenlet_primitives, gevent._gevent_c_hub_local, gevent._gevent_c_waiter, gevent._gevent_c_hub_primitives, gevent._gevent_c_ident, gevent._gevent_cgreenlet, gevent._gevent_c_abstract_linkable, gevent._gevent_c_semaphore, gevent._gevent_clocal, gevent._gevent_cevent, gevent._gevent_cqueue, pydantic.typing, pydantic.errors, pydantic.version, pydantic.utils, pydantic.class_validators, pydantic.config, pydantic.color, pydantic.datetime_parse, pydantic.validators, pydantic.networks, pydantic.types, pydantic.json, pydantic.error_wrappers, pydantic.fields, pydantic.parse, pydantic.schema, pydantic.main, pydantic.dataclasses, pydantic.annotated_types, pydantic.decorator, pydantic.env_settings, pydantic.tools, pydantic, yaml._yaml, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, charset_normalizer.md, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, sqlalchemy.cimmutabledict, sqlalchemy.cprocessors, sqlalchemy.cresultproxy, _cffi_backend, numexpr.interpreter, gevent._gevent_c_imap, regex._regex, grpc._cython.cygrpc, google._upb._message, lxml._elementpath, lxml.etree, PIL._imaging, psycopg2._psycopg, lxml.html.clean, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.tslib, pandas._libs.lib, pandas._libs.hashing, pandas._libs.ops, pandas._libs.arrays, pandas._libs.index, pandas._libs.join, pandas._libs.sparse, pandas._libs.reduction, pandas._libs.indexing, pandas._libs.internals, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.tslibs.strptime, pandas._libs.groupby, pandas._libs.testing, pandas._libs.parsers, pandas._libs.json, sklearn.__check_build._check_build, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.sparse.linalg._isolve._iterative, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.linalg._flinalg, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, sklearn.utils.murmurhash, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.optimize._minpack2, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize.__nnls, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap, scipy.optimize._direct, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.special.cython_special, scipy.stats._stats, scipy.stats.beta_ufunc, scipy.stats._boost.beta_ufunc, scipy.stats.binom_ufunc, scipy.stats._boost.binom_ufunc, scipy.stats.nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, scipy.stats.hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats.ncf_ufunc, scipy.stats._boost.ncf_ufunc, scipy.stats.ncx2_ufunc, scipy.stats._boost.ncx2_ufunc, scipy.stats.nct_ufunc, scipy.stats._boost.nct_ufunc, scipy.stats.skewnorm_ufunc, scipy.stats._boost.skewnorm_ufunc, scipy.stats.invgauss_ufunc, scipy.stats._boost.invgauss_ufunc, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, scipy.stats._biasedurn, scipy.stats._levy_stable.levyst, scipy.stats._stats_pythran, scipy._lib._uarray._uarray, scipy.stats._statlib, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont, sklearn.utils._isfinite, sklearn.utils._openmp_helpers, sklearn.utils._logistic_sigmoid, sklearn.utils.sparsefuncs_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.utils._typedefs, sklearn.utils._readonly_array_wrapper, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._base, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.utils._random, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.linear_model._cd_fast, sklearn._loss._loss, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.decomposition._online_lda_fast, sklearn._isotonic, sklearn.manifold._utils, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne (total: 261) [1] 2275 segmentation fault flask run --host 0.0.0.0 --port=5001 --debug ```
yindo added the 🐞 bug🤔 cant-reproduce labels 2026-02-21 17:28:02 -05:00
yindo closed this issue 2026-02-21 17:28:02 -05:00
yindo commented 2026-02-21 17:28:03 -05:00
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@crazywoola commented on GitHub (Nov 14, 2023):

You can try to reinstall the required dependencies pip install -r requirements.txt --upgrade --force-reinstall.
This seems something wrong with you memory maybe.

@crazywoola commented on GitHub (Nov 14, 2023): You can try to reinstall the required dependencies `pip install -r requirements.txt --upgrade --force-reinstall`. This seems something wrong with you memory maybe.
yindo commented 2026-02-21 17:28:03 -05:00
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@oopslink commented on GitHub (Nov 21, 2023):

I had the same problem, I upgraded MacOS from Big Sur v11.7.4 to Sonoma v14.1.1 and the problem has not recurred.

@oopslink commented on GitHub (Nov 21, 2023): I had the same problem, I upgraded MacOS from Big Sur v11.7.4 to Sonoma v14.1.1 and the problem has not recurred.
yindo commented 2026-02-21 17:28:03 -05:00
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@takatost commented on GitHub (Nov 22, 2023):

Give it a try by adding the environment variable DEBUG=true to block gevent from running as a worker.

@takatost commented on GitHub (Nov 22, 2023): Give it a try by adding the environment variable `DEBUG=true` to block gevent from running as a worker.
yindo commented 2026-02-21 17:28:03 -05:00
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@TomorJM commented on GitHub (Nov 24, 2023):

Give it a try by adding the environment variable DEBUG=true to block gevent from running as a worker.

thanks, it worked!

@TomorJM commented on GitHub (Nov 24, 2023): > Give it a try by adding the environment variable `DEBUG=true` to block gevent from running as a worker. thanks, it worked!
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Reference: langgenius/dify#691
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