更新环境配置,添加gevent和gunicorn依赖;新增chat_dify_by_workorder.py文件以处理工单对话逻辑;优化PgSql类中的异常处理,确保连接失败时抛出异常;改进意图识别API,使用单例模式管理意图识别器实例,增强线程安全性;新增workflow_chat.py文件以支持新工作流对话功能。

This commit is contained in:
2025-06-05 10:52:31 +08:00
parent 01dc1c3c91
commit c715fca5ef
8 changed files with 784 additions and 42 deletions
+1 -1
View File
@@ -1,5 +1,5 @@
OPENAI_API_KEY=sk-xxaiabmfhzwwpijuledllkmkzhzwsqeicjxmjwnvriqpwmpk OPENAI_API_KEY=sk-xxaiabmfhzwwpijuledllkmkzhzwsqeicjxmjwnvriqpwmpk
OPENAI_API_BASE=https://api.siliconflow.cn/v1/ OPENAI_API_BASE=https://api.siliconflow.cn/v1/
LLM_MODEL_NAME=deepseek-ai/DeepSeek-V3 LLM_MODEL_NAME=deepseek-ai/DeepSeek-V3
# LLM_MODEL_NAME=deepseek-ai/DeepSeek-R1
RERANKER_MODEL_NAME=bge-reranker-v2-m3 RERANKER_MODEL_NAME=bge-reranker-v2-m3
Generated
+200 -1
View File
@@ -753,6 +753,72 @@ type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple" url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors" reference = "ali-mirrors"
[[package]]
name = "gevent"
version = "25.5.1"
description = "Coroutine-based network library"
optional = false
python-versions = ">=3.9"
files = [
{file = "gevent-25.5.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:8e5a0fab5e245b15ec1005b3666b0a2e867c26f411c8fe66ae1afe07174a30e9"},
{file = "gevent-25.5.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c7b80a37f2fb45ee4a8f7e64b77dd8a842d364384046e394227b974a4e9c9a52"},
{file = "gevent-25.5.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:29ab729d50ae85077a68e0385f129f5b01052d01a0ae6d7fdc1824f5337905e4"},
{file = "gevent-25.5.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:80d20592aeabcc4e294fd441fd43d45cb537437fd642c374ea9d964622fad229"},
{file = "gevent-25.5.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8ba0257542ccbb72a8229dc34d00844ccdfba110417e4b7b34599548d0e20e9"},
{file = "gevent-25.5.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cad0821dff998c7c60dd238f92cd61380342c47fb9e92e1a8705d9b5ac7c16e8"},
{file = "gevent-25.5.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:017a7384c0cd1a5907751c991535a0699596e89725468a7fc39228312e10efa1"},
{file = "gevent-25.5.1-cp310-cp310-win_amd64.whl", hash = "sha256:469c86d02fccad7e2a3d82fe22237e47ecb376fbf4710bc18747b49c50716817"},
{file = "gevent-25.5.1-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:12380aba5c316e9ff53cc21d8ab80f4a91c0df3ada58f65d4f5eb2cf693db00e"},
{file = "gevent-25.5.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f0694daab1a041b69a53f53c2141c12994892b2503870515cabe6a5dbd2a928"},
{file = "gevent-25.5.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2797885e9aeffdc98e1846723e5aa212e7ce53007dbef40d6fd2add264235c41"},
{file = "gevent-25.5.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cde6aaac36b54332e10ea2a5bc0de6a8aba6c205c92603fe4396e3777c88e05d"},
{file = "gevent-25.5.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24484f80f14befb8822bf29554cfb3a26a26cb69cd1e5a8be9e23b4bd7a96e25"},
{file = "gevent-25.5.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8fdc7446895fa184890d8ca5ea61e502691114f9db55c9b76adc33f3086c4368"},
{file = "gevent-25.5.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:5b6106e2414b1797133786258fa1962a5e836480e4d5e861577f9fc63b673a5a"},
{file = "gevent-25.5.1-cp311-cp311-win_amd64.whl", hash = "sha256:bc899212d90f311784c58938a9c09c59802fb6dc287a35fabdc36d180f57f575"},
{file = "gevent-25.5.1-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:d87c0a1bd809d8f70f96b9b229779ec6647339830b8888a192beed33ac8d129f"},
{file = "gevent-25.5.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b87a4b66edb3808d4d07bbdb0deed5a710cf3d3c531e082759afd283758bb649"},
{file = "gevent-25.5.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f076779050029a82feb0cb1462021d3404d22f80fa76a181b1a7889cd4d6b519"},
{file = "gevent-25.5.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bb673eb291c19370f69295f7a881a536451408481e2e3deec3f41dedb7c281ec"},
{file = "gevent-25.5.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c1325ed44225c8309c0dd188bdbbbee79e1df8c11ceccac226b861c7d52e4837"},
{file = "gevent-25.5.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:fcd5bcad3102bde686d0adcc341fade6245186050ce14386d547ccab4bd54310"},
{file = "gevent-25.5.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1a93062609e8fa67ec97cd5fb9206886774b2a09b24887f40148c9c37e6fb71c"},
{file = "gevent-25.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:2534c23dc32bed62b659ed4fd9e198906179e68b26c9276a897e04163bdde806"},
{file = "gevent-25.5.1-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:a022a9de9275ce0b390b7315595454258c525dc8287a03f1a6cacc5878ab7cbc"},
{file = "gevent-25.5.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3fae8533f9d0ef3348a1f503edcfb531ef7a0236b57da1e24339aceb0ce52922"},
{file = "gevent-25.5.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c7b32d9c3b5294b39ea9060e20c582e49e1ec81edbfeae6cf05f8ad0829cb13d"},
{file = "gevent-25.5.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7b95815fe44f318ebbfd733b6428b4cb18cc5e68f1c40e8501dd69cc1f42a83d"},
{file = "gevent-25.5.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2d316529b70d325b183b2f3f5cde958911ff7be12eb2b532b5c301f915dbbf1e"},
{file = "gevent-25.5.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f6ba33c13db91ffdbb489a4f3d177a261ea1843923e1d68a5636c53fe98fa5ce"},
{file = "gevent-25.5.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:37ee34b77c7553777c0b8379915f75934c3f9c8cd32f7cd098ea43c9323c2276"},
{file = "gevent-25.5.1-cp313-cp313-win_amd64.whl", hash = "sha256:9fa6aa0da224ed807d3b76cdb4ee8b54d4d4d5e018aed2478098e685baae7896"},
{file = "gevent-25.5.1-cp314-cp314-macosx_11_0_universal2.whl", hash = "sha256:0bacf89a65489d26c7087669af89938d5bfd9f7afb12a07b57855b9fad6ccbd0"},
{file = "gevent-25.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e30169ef9cc0a57930bfd8fe14d86bc9d39fb96d278e3891e85cbe7b46058a97"},
{file = "gevent-25.5.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e72ad5f8d9c92df017fb91a1f6a438cfb63b0eff4b40904ff81b40cb8150078c"},
{file = "gevent-25.5.1-cp39-cp39-win32.whl", hash = "sha256:e5f358e81e27b1a7f2fb2f5219794e13ab5f59ce05571aa3877cfac63adb97db"},
{file = "gevent-25.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:b83aff2441c7d4ee93e519989713b7c2607d4510abe990cd1d04f641bc6c03af"},
{file = "gevent-25.5.1-pp310-pypy310_pp73-macosx_11_0_universal2.whl", hash = "sha256:60ad4ca9ca2c4cc8201b607c229cd17af749831e371d006d8a91303bb5568eb1"},
{file = "gevent-25.5.1.tar.gz", hash = "sha256:582c948fa9a23188b890d0bc130734a506d039a2e5ad87dae276a456cc683e61"},
]
[package.dependencies]
cffi = {version = ">=1.17.1", markers = "platform_python_implementation == \"CPython\" and sys_platform == \"win32\""}
greenlet = {version = ">=3.2.2", markers = "platform_python_implementation == \"CPython\""}
"zope.event" = "*"
"zope.interface" = "*"
[package.extras]
dnspython = ["dnspython (>=1.16.0,<2.0)", "idna"]
docs = ["furo", "repoze.sphinx.autointerface", "sphinx", "sphinxcontrib-programoutput", "zope.schema"]
monitor = ["psutil (>=5.7.0)"]
recommended = ["cffi (>=1.17.1)", "dnspython (>=1.16.0,<2.0)", "idna", "psutil (>=5.7.0)"]
test = ["cffi (>=1.17.1)", "coverage (>=5.0)", "dnspython (>=1.16.0,<2.0)", "idna", "objgraph", "psutil (>=5.7.0)", "requests"]
[package.source]
type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors"
[[package]] [[package]]
name = "greenlet" name = "greenlet"
version = "3.2.2" version = "3.2.2"
@@ -826,6 +892,32 @@ type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple" url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors" reference = "ali-mirrors"
[[package]]
name = "gunicorn"
version = "23.0.0"
description = "WSGI HTTP Server for UNIX"
optional = false
python-versions = ">=3.7"
files = [
{file = "gunicorn-23.0.0-py3-none-any.whl", hash = "sha256:ec400d38950de4dfd418cff8328b2c8faed0edb0d517d3394e457c317908ca4d"},
{file = "gunicorn-23.0.0.tar.gz", hash = "sha256:f014447a0101dc57e294f6c18ca6b40227a4c90e9bdb586042628030cba004ec"},
]
[package.dependencies]
packaging = "*"
[package.extras]
eventlet = ["eventlet (>=0.24.1,!=0.36.0)"]
gevent = ["gevent (>=1.4.0)"]
setproctitle = ["setproctitle"]
testing = ["coverage", "eventlet", "gevent", "pytest", "pytest-cov"]
tornado = ["tornado (>=0.2)"]
[package.source]
type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors"
[[package]] [[package]]
name = "h11" name = "h11"
version = "0.16.0" version = "0.16.0"
@@ -2412,6 +2504,31 @@ type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple" url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors" reference = "ali-mirrors"
[[package]]
name = "setuptools"
version = "80.9.0"
description = "Easily download, build, install, upgrade, and uninstall Python packages"
optional = false
python-versions = ">=3.9"
files = [
{file = "setuptools-80.9.0-py3-none-any.whl", hash = "sha256:062d34222ad13e0cc312a4c02d73f059e86a4acbfbdea8f8f76b28c99f306922"},
{file = "setuptools-80.9.0.tar.gz", hash = "sha256:f36b47402ecde768dbfafc46e8e4207b4360c654f1f3bb84475f0a28628fb19c"},
]
[package.extras]
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.8.0)"]
core = ["importlib_metadata (>=6)", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
cover = ["pytest-cov"]
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
enabler = ["pytest-enabler (>=2.2)"]
test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.14.*)", "pytest-mypy"]
[package.source]
type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors"
[[package]] [[package]]
name = "six" name = "six"
version = "1.17.0" version = "1.17.0"
@@ -2912,6 +3029,88 @@ type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple" url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors" reference = "ali-mirrors"
[[package]]
name = "zope-event"
version = "5.0"
description = "Very basic event publishing system"
optional = false
python-versions = ">=3.7"
files = [
{file = "zope.event-5.0-py3-none-any.whl", hash = "sha256:2832e95014f4db26c47a13fdaef84cef2f4df37e66b59d8f1f4a8f319a632c26"},
{file = "zope.event-5.0.tar.gz", hash = "sha256:bac440d8d9891b4068e2b5a2c5e2c9765a9df762944bda6955f96bb9b91e67cd"},
]
[package.dependencies]
setuptools = "*"
[package.extras]
docs = ["Sphinx"]
test = ["zope.testrunner"]
[package.source]
type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors"
[[package]]
name = "zope-interface"
version = "7.2"
description = "Interfaces for Python"
optional = false
python-versions = ">=3.8"
files = [
{file = "zope.interface-7.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ce290e62229964715f1011c3dbeab7a4a1e4971fd6f31324c4519464473ef9f2"},
{file = "zope.interface-7.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:05b910a5afe03256b58ab2ba6288960a2892dfeef01336dc4be6f1b9ed02ab0a"},
{file = "zope.interface-7.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:550f1c6588ecc368c9ce13c44a49b8d6b6f3ca7588873c679bd8fd88a1b557b6"},
{file = "zope.interface-7.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0ef9e2f865721553c6f22a9ff97da0f0216c074bd02b25cf0d3af60ea4d6931d"},
{file = "zope.interface-7.2-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:27f926f0dcb058211a3bb3e0e501c69759613b17a553788b2caeb991bed3b61d"},
{file = "zope.interface-7.2-cp310-cp310-win_amd64.whl", hash = "sha256:144964649eba4c5e4410bb0ee290d338e78f179cdbfd15813de1a664e7649b3b"},
{file = "zope.interface-7.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1909f52a00c8c3dcab6c4fad5d13de2285a4b3c7be063b239b8dc15ddfb73bd2"},
{file = "zope.interface-7.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:80ecf2451596f19fd607bb09953f426588fc1e79e93f5968ecf3367550396b22"},
{file = "zope.interface-7.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:033b3923b63474800b04cba480b70f6e6243a62208071fc148354f3f89cc01b7"},
{file = "zope.interface-7.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a102424e28c6b47c67923a1f337ede4a4c2bba3965b01cf707978a801fc7442c"},
{file = "zope.interface-7.2-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:25e6a61dcb184453bb00eafa733169ab6d903e46f5c2ace4ad275386f9ab327a"},
{file = "zope.interface-7.2-cp311-cp311-win_amd64.whl", hash = "sha256:3f6771d1647b1fc543d37640b45c06b34832a943c80d1db214a37c31161a93f1"},
{file = "zope.interface-7.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:086ee2f51eaef1e4a52bd7d3111a0404081dadae87f84c0ad4ce2649d4f708b7"},
{file = "zope.interface-7.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:21328fcc9d5b80768bf051faa35ab98fb979080c18e6f84ab3f27ce703bce465"},
{file = "zope.interface-7.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f6dd02ec01f4468da0f234da9d9c8545c5412fef80bc590cc51d8dd084138a89"},
{file = "zope.interface-7.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e7da17f53e25d1a3bde5da4601e026adc9e8071f9f6f936d0fe3fe84ace6d54"},
{file = "zope.interface-7.2-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cab15ff4832580aa440dc9790b8a6128abd0b88b7ee4dd56abacbc52f212209d"},
{file = "zope.interface-7.2-cp312-cp312-win_amd64.whl", hash = "sha256:29caad142a2355ce7cfea48725aa8bcf0067e2b5cc63fcf5cd9f97ad12d6afb5"},
{file = "zope.interface-7.2-cp313-cp313-macosx_10_9_x86_64.whl", hash = "sha256:3e0350b51e88658d5ad126c6a57502b19d5f559f6cb0a628e3dc90442b53dd98"},
{file = "zope.interface-7.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:15398c000c094b8855d7d74f4fdc9e73aa02d4d0d5c775acdef98cdb1119768d"},
{file = "zope.interface-7.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:802176a9f99bd8cc276dcd3b8512808716492f6f557c11196d42e26c01a69a4c"},
{file = "zope.interface-7.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:eb23f58a446a7f09db85eda09521a498e109f137b85fb278edb2e34841055398"},
{file = "zope.interface-7.2-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a71a5b541078d0ebe373a81a3b7e71432c61d12e660f1d67896ca62d9628045b"},
{file = "zope.interface-7.2-cp313-cp313-win_amd64.whl", hash = "sha256:4893395d5dd2ba655c38ceb13014fd65667740f09fa5bb01caa1e6284e48c0cd"},
{file = "zope.interface-7.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d3a8ffec2a50d8ec470143ea3d15c0c52d73df882eef92de7537e8ce13475e8a"},
{file = "zope.interface-7.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:31d06db13a30303c08d61d5fb32154be51dfcbdb8438d2374ae27b4e069aac40"},
{file = "zope.interface-7.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e204937f67b28d2dca73ca936d3039a144a081fc47a07598d44854ea2a106239"},
{file = "zope.interface-7.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:224b7b0314f919e751f2bca17d15aad00ddbb1eadf1cb0190fa8175edb7ede62"},
{file = "zope.interface-7.2-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baf95683cde5bc7d0e12d8e7588a3eb754d7c4fa714548adcd96bdf90169f021"},
{file = "zope.interface-7.2-cp38-cp38-win_amd64.whl", hash = "sha256:7dc5016e0133c1a1ec212fc87a4f7e7e562054549a99c73c8896fa3a9e80cbc7"},
{file = "zope.interface-7.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7bd449c306ba006c65799ea7912adbbfed071089461a19091a228998b82b1fdb"},
{file = "zope.interface-7.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a19a6cc9c6ce4b1e7e3d319a473cf0ee989cbbe2b39201d7c19e214d2dfb80c7"},
{file = "zope.interface-7.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:72cd1790b48c16db85d51fbbd12d20949d7339ad84fd971427cf00d990c1f137"},
{file = "zope.interface-7.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:52e446f9955195440e787596dccd1411f543743c359eeb26e9b2c02b077b0519"},
{file = "zope.interface-7.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ad9913fd858274db8dd867012ebe544ef18d218f6f7d1e3c3e6d98000f14b75"},
{file = "zope.interface-7.2-cp39-cp39-win_amd64.whl", hash = "sha256:1090c60116b3da3bfdd0c03406e2f14a1ff53e5771aebe33fec1edc0a350175d"},
{file = "zope.interface-7.2.tar.gz", hash = "sha256:8b49f1a3d1ee4cdaf5b32d2e738362c7f5e40ac8b46dd7d1a65e82a4872728fe"},
]
[package.dependencies]
setuptools = "*"
[package.extras]
docs = ["Sphinx", "furo", "repoze.sphinx.autointerface"]
test = ["coverage[toml]", "zope.event", "zope.testing"]
testing = ["coverage[toml]", "zope.event", "zope.testing"]
[package.source]
type = "legacy"
url = "http://mirrors.aliyun.com/pypi/simple"
reference = "ali-mirrors"
[[package]] [[package]]
name = "zstandard" name = "zstandard"
version = "0.23.0" version = "0.23.0"
@@ -3032,4 +3231,4 @@ reference = "ali-mirrors"
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.11,<3.13" python-versions = ">=3.11,<3.13"
content-hash = "9c8317a7a8b141b864d0bbac4c482445339c928cb9cc55bc7a5a86f63b7e39fd" content-hash = "2b34e52cba181483fd7ab37d7d9ed92b4703aecc604befbd150d831e84de535d"
+2
View File
@@ -22,6 +22,8 @@ tqdm = "^4.67.1"
xlsxwriter = "^3.2.3" xlsxwriter = "^3.2.3"
flask = "^3.1.1" flask = "^3.1.1"
psycopg2 = "^2.9.10" psycopg2 = "^2.9.10"
gunicorn = "^23.0.0"
gevent = "^25.5.1"
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
+151
View File
@@ -0,0 +1,151 @@
from rag2_0.dify.workflow_chat import NewWorkflowChat
import pandas as pd
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm
import concurrent.futures
class ChatDifyByWorkorder:
def __init__(self, api_key=None, base_url="https://api.dify.ai/v1") -> None:
"""
初始化ChatDifyByWorkorder类
Args:
api_key: Dify API密钥,默认为None
base_url: Dify API的基础URL,默认为"https://api.dify.ai/v1"
"""
baseurl = "http://172.20.0.145/v1"
new_workflow_api_key = "app-qxsSybCs7ABiKlC1JabTYVn6"
self.new_chat = NewWorkflowChat(api_key=new_workflow_api_key, base_url=baseurl)
self.new_chat_answer = NewWorkflowChat(api_key=new_workflow_api_key, base_url=baseurl)
def get_soft_name(self, row) -> str:
if "博微配网计价通D3" in row["产品线"]:
return "博微配网计价通D3"
elif "博微电力建设计价通软件" in row["产品线"]:
return "电力建设计价通软件"
elif "新能源系列" in row["产品线"] and "博微新型储能电站建设计价通C1软件" in row["产品名称"]:
return "储能C1软件"
elif "博微西藏计价通Z1" in row["产品线"]:
return "西藏计价通Z1"
elif "博微技改检修计价通T1软件" in row["产品线"] and "技改检修计价通T1软件-概预算" in row["产品名称"]:
return "技改检修工程计价通T1"
elif "博微技改检修计价通T1软件" in row["产品线"] and "技改检修计价通T1软件-清单" in row["产品名称"]:
return "检修清单计价通T1"
return ""
def process_query(self, q:str) -> dict:
"""
发送问题并获取回答及相关工作流信息
Args:
q: 用户问题
Returns:
dict: 包含问题、回答和工作流信息的字典
"""
retry_count = 0
max_retries = 2
while retry_count <= max_retries:
try:
# 发送问题获取回答和消息ID
result = self.new_chat.process_question(q)
return result
except Exception as e:
retry_count += 1
if retry_count <= max_retries:
continue
else:
raise e
def process_answer(self, q:str) -> dict:
"""
发送问题并获取回答及相关工作流信息
Args:
q: 用户问题
Returns:
dict: 包含问题、回答和工作流信息的字典
"""
retry_count = 0
max_retries = 2
while retry_count <= max_retries:
try:
# 发送问题获取回答和消息ID
result = self.new_chat_answer.process_question(q)
return result
except Exception as e:
retry_count += 1
if retry_count <= max_retries:
continue
else:
raise
def process_row(self, row):
"""处理单行数据"""
soft_name = self.get_soft_name(row=row)
if soft_name == "":
return None
# 使用线程池并发执行查询
with ThreadPoolExecutor() as executor:
try:
# 提交两个任务并获取Future对象
query_future = executor.submit(self.process_query, q=f"{soft_name},{row['客户问题']}")
answer_future = executor.submit(self.process_answer, q=f"{soft_name},{row['解决方案']}")
# 获取结果
query_result = query_future.result()
answer_result = answer_future.result()
except Exception as e:
print(f"处理工单 {row.get('工单编号', '未知')} 时发生错误: {str(e)}")
return None
worker_id = str(row["工单编号"])
if query_result is None or answer_result is None:
print("处理对话出现错误")
return None
worker_order_info = {
"工单编号": worker_id,
"用户问题": row['客户问题'],
"解决方案": row['解决方案'],
"AI回答": query_result["新流程答案"],
"用户问题检索到的词条": query_result["新检索词条"],
"解决方案检索到的词条": answer_result["新检索词条"],
}
return worker_order_info
def run(self, excel_path:str):
df_data = pd.read_excel(excel_path)
list_worker_order_info = []
# 创建进度条
with tqdm(total=len(df_data), desc="处理工单") as pbar:
# 创建线程池,最大并发数可以根据需要调整
with ThreadPoolExecutor(max_workers=5) as executor:
# 提交所有任务
future_to_row = {executor.submit(self.process_row, row): idx for idx, row in df_data.iterrows()}
# 处理完成的任务
for future in concurrent.futures.as_completed(future_to_row):
result = future.result()
if result is not None:
list_worker_order_info.append(result)
pbar.update(1)
return list_worker_order_info
if __name__=="__main__":
worker_chat = ChatDifyByWorkorder()
result = worker_chat.run(excel_path="data/excel/工单记录_均衡提取2000条.xlsx")
# 可以选择保存结果到Excel
if result:
pd.DataFrame(result).to_excel("data/excel/工单处理结果.xlsx", index=False)
+22 -9
View File
@@ -23,7 +23,7 @@ class PgSql:
连接到 PostgreSQL 数据库。 连接到 PostgreSQL 数据库。
使用预定义的凭据连接到 'dify' 数据库。 使用预定义的凭据连接到 'dify' 数据库。
如果连接失败,会打印错误信息 如果连接失败,会抛出异常
""" """
try: try:
# 连接数据库 # 连接数据库
@@ -36,17 +36,16 @@ class PgSql:
) )
except (Exception, psycopg2.Error) as error: except (Exception, psycopg2.Error) as error:
print("Error while connecting to PostgreSQL", error) raise Exception(f"Error while connecting to PostgreSQL: {error}")
def close_connection(self): def close_connection(self):
""" """
关闭当前的 PostgreSQL 数据库连接。 关闭当前的 PostgreSQL 数据库连接。
如果存在活动的连接,则关闭它并打印确认信息 如果存在活动的连接,则关闭它。
""" """
if self.connection: if self.connection:
self.connection.close() self.connection.close()
print("PostgreSQL connection is closed")
def get_appinfo(self, appid:str)->dict | None: def get_appinfo(self, appid:str)->dict | None:
@@ -74,7 +73,7 @@ class PgSql:
return dict(zip(colnames, result)) return dict(zip(colnames, result))
return None return None
except (Exception, psycopg2.Error) as error: except (Exception, psycopg2.Error) as error:
print("Error while getting tenant_id by appid", error) raise Exception(f"Error while getting tenant_id by appid: {error}")
def get_messages_info(self, appid:str, query:str)->dict | None: def get_messages_info(self, appid:str, query:str)->dict | None:
@@ -103,7 +102,7 @@ class PgSql:
return dict(zip(colnames, result)) return dict(zip(colnames, result))
return None return None
except (Exception, psycopg2.Error) as error: except (Exception, psycopg2.Error) as error:
print("Error while getting messages_info", error) raise Exception(f"Error while getting messages_info: {error}")
def get_messages_info_by_id(self, message_id:str)->dict | None: def get_messages_info_by_id(self, message_id:str)->dict | None:
""" """
@@ -123,7 +122,7 @@ class PgSql:
return dict(zip(colnames, result)) return dict(zip(colnames, result))
return None return None
except (Exception, psycopg2.Error) as error: except (Exception, psycopg2.Error) as error:
print("Error while getting messages_info", error) raise Exception(f"Error while getting messages_info by id: {error}")
def get_workflow_node_executions_info(self, workflow_run_id:str)->list[dict] | None: def get_workflow_node_executions_info(self, workflow_run_id:str)->list[dict] | None:
""" """
@@ -150,7 +149,7 @@ class PgSql:
return [dict(zip(colnames, row)) for row in result] return [dict(zip(colnames, row)) for row in result]
return None return None
except (Exception, psycopg2.Error) as error: except (Exception, psycopg2.Error) as error:
print("Error while getting workflow_node_executions_info", error) raise Exception(f"Error while getting workflow_node_executions_info: {error}")
class DifyTool: class DifyTool:
""" """
@@ -165,6 +164,7 @@ class DifyTool:
根据消息 ID 从 'messages' 表中获取消息信息。 根据消息 ID 从 'messages' 表中获取消息信息。
""" """
dify_pgsql = PgSql() dify_pgsql = PgSql()
try:
messages_info = dify_pgsql.get_messages_info_by_id(message_id) messages_info = dify_pgsql.get_messages_info_by_id(message_id)
if not messages_info: if not messages_info:
return None return None
@@ -175,6 +175,10 @@ class DifyTool:
"messages_info": messages_info, "messages_info": messages_info,
"workflow_node_executions_info": workflow_node_executions_info "workflow_node_executions_info": workflow_node_executions_info
} }
except Exception as e:
raise Exception(f"Error in get_message_debug_info_by_id: {e}")
finally:
dify_pgsql.close_connection()
@staticmethod @staticmethod
@@ -195,6 +199,7 @@ class DifyTool:
查询到的应用数据、消息数据和节点执行数据。 查询到的应用数据、消息数据和节点执行数据。
""" """
dify_pgsql = PgSql() dify_pgsql = PgSql()
try:
appinfo = dify_pgsql.get_appinfo(appid) appinfo = dify_pgsql.get_appinfo(appid)
if not appinfo: if not appinfo:
return None return None
@@ -209,7 +214,15 @@ class DifyTool:
"messages_info": messages_info, "messages_info": messages_info,
"workflow_node_executions_info": workflow_node_executions_info "workflow_node_executions_info": workflow_node_executions_info
} }
except Exception as e:
raise Exception(f"Error in get_message_debug_info_by_query: {e}")
finally:
dify_pgsql.close_connection()
if __name__ == "__main__": if __name__ == "__main__":
print(DifyTool.get_message_debug_info_by_query("ccf92b97-2789-4a3f-90e0-135a869a37c5", "电力建设计价通软件,导入结算后没有暂列金怎么办?要手动添加么?")) try:
result = DifyTool.get_message_debug_info_by_query("ccf92b97-2789-4a3f-90e0-135a869a37c5", "电力建设计价通软件,导入结算后没有暂列金怎么办?要手动添加么?")
print(result)
except Exception as e:
print(f"执行出错: {e}")
+29 -4
View File
@@ -4,16 +4,32 @@ from dotenv import load_dotenv
from rag2_0.intent_recognition import IntentRecognizer from rag2_0.intent_recognition import IntentRecognizer
import json import json
import time import time
import threading
import datetime
# 加载环境变量 # 加载环境变量
load_dotenv() load_dotenv()
app = Flask(__name__) app = Flask(__name__)
# 初始化意图识别器 # 创建线程锁,用于保护共享资源
recognizer_lock = threading.Lock()
# 使用单例模式创建意图识别器
class RecognizerSingleton:
_instance = None
_lock = threading.Lock()
@classmethod
def get_instance(cls):
if cls._instance is None:
with cls._lock:
if cls._instance is None:
api_key = os.getenv("OPENAI_API_KEY") api_key = os.getenv("OPENAI_API_KEY")
base_url = os.getenv("OPENAI_API_BASE") base_url = os.getenv("OPENAI_API_BASE")
model_name = os.getenv("LLM_MODEL_NAME", "gpt-3.5-turbo") model_name = os.getenv("LLM_MODEL_NAME", "gpt-3.5-turbo")
recognizer = IntentRecognizer(api_key=api_key, base_url=base_url, model_name=model_name) cls._instance = IntentRecognizer(api_key=api_key, base_url=base_url, model_name=model_name)
return cls._instance
@app.route('/intent_recognize', methods=['POST']) @app.route('/intent_recognize', methods=['POST'])
def intent_recognize(): def intent_recognize():
@@ -22,10 +38,16 @@ def intent_recognize():
query = data.get('query') query = data.get('query')
if not query: if not query:
return Response(json.dumps({"error": "缺少query参数"}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=400) return Response(json.dumps({"error": "缺少query参数"}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=400)
start_time = time.time() start_time = time.time()
# 获取单例实例并使用线程锁保护关键操作
recognizer = RecognizerSingleton.get_instance()
result = recognizer.process_query_with_slots(query) result = recognizer.process_query_with_slots(query)
end_time = time.time() end_time = time.time()
print(f"意图识别耗时: {end_time - start_time:.2f}") current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S %z")
print(f"[{current_time}] [{os.getpid()}] [INFO] 意图识别耗时: {end_time - start_time:.2f}")
# 提取分类信息 # 提取分类信息
classification = result["classification"] classification = result["classification"]
@@ -63,7 +85,10 @@ def intent_recognize():
} }
return Response(json.dumps(response_result, ensure_ascii=False), content_type='application/json; charset=utf-8') return Response(json.dumps(response_result, ensure_ascii=False), content_type='application/json; charset=utf-8')
except Exception as e: except Exception as e:
print(f"意图识别出错: {str(e)}")
return Response(json.dumps({"error": str(e)}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=500) return Response(json.dumps({"error": str(e)}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=500)
if __name__ == "__main__": if __name__ == "__main__":
app.run(host="0.0.0.0", port=8001) # 开发环境使用Flask内置服务器
# 生产环境使用gunicorn支持高并发 poetry run gunicorn -w 10 -k gevent -b 0.0.0.0:8001 rag2_0.dify.intent_recognition_api:app
app.run(host="0.0.0.0", port=8001, threaded=True)
+310
View File
@@ -0,0 +1,310 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import json
from concurrent.futures import ThreadPoolExecutor, as_completed
from rag2_0.dify.dify_client import ChatClient, DifyClient
from rag2_0.dify.dify_tool import DifyTool
from pydantic import BaseModel, Field
from langchain.output_parsers import PydanticOutputParser
from threading import Lock
class ContentSource(BaseModel):
score: int = Field(description="相关性分数")
reason: str = Field(description="评分理由")
class BaseWorkflowChat:
"""
工作流对话基类,封装了与Dify API交互的基本功能
"""
def __init__(self, api_key: str, base_url: str):
"""
初始化工作流对话基类
Args:
api_key: Dify API的密钥
base_url: Dify API的基础URL
"""
self.chat_client = ChatClient(api_key=api_key, base_url=base_url)
self.content_source_parser = PydanticOutputParser(pydantic_object=ContentSource)
def create_chat_message(self, query: str):
"""
创建聊天消息
Args:
query: 问题内容
Returns:
tuple: (聊天响应, 消息ID)
"""
try:
response = self.chat_client.create_chat_message(inputs={}, query=query, user="AutoTestDifyChat").json()
return response, response["message_id"]
except Exception as e:
raise e
def calculate_score(self, query: str, content: str) -> int:
"""
使用LLM判断query与content之间的相关性分数
Args:
query (str): 用户问题
content (str): 检索内容
Returns:
int: 相关性分数,1-10分,10代表完全相关,1代表完全不相关;-1表示评分失败
"""
from rag2_0.tool.ModelTool import OpenAiLLM
try:
prompt = f"""你是一个专业的信息相关性评估助手。请根据以下标准对用户query和检索内容的相关性进行1-10评分(10=完全相关,1=完全不相关),并按指定格式输出JSON结果。
【评分标准】
10分:完全契合,主题/意图完全一致且涵盖所有关键信息
8-9分:高度相关,核心要素匹配但存在少量信息缺失
6-7分:部分相关,涉及相同主题但存在重要信息缺失
4-5分:弱相关,仅次要信息点匹配
1-3分:完全不相关或信息冲突
【评估维度】
1. 主题一致性:核心主题/意图的匹配程度
2. 内容覆盖度:是否涵盖query的关键要素
3. 信息准确性:是否存在矛盾/错误信息
4. 细节丰富度:是否提供query要求的详细信息
【输出格式】
{{
"score": 评分,
"reason": "简明扼要的评分理由(中文)"
}}
【示例】
query: "新冠疫苗的常见副作用"
内容: "辉瑞疫苗常见反应包括注射部位疼痛(84.1%)、疲劳(62.9%)"
输出: {{"score":8,"reason":"主题完全匹配,涵盖主要副作用但未提及发热等常见反应"}}
现在评估:
query: "{query}"
content: "{content}"
"""
api_key = os.getenv("OPENAI_API_KEY")
base_url = os.getenv("OPENAI_API_BASE")
model = os.getenv("LLM_MODEL_NAME")
llm = OpenAiLLM(api_key=api_key, base_url=base_url, model=model)
response = llm.invoke(user_prompt=prompt, need_retry=True)
# 解析JSON响应
try:
parsed_output = self.content_source_parser.parse(response.content)
return parsed_output.score
except Exception as e:
return -1
except Exception as e:
return -1
def get_retrieve_info(self, query: str, outputs: dict) -> tuple:
"""
获取检索信息并计算分数
Args:
query (str): 用户问题
outputs (dict): 检索输出结果
Returns:
tuple: (检索内容列表, 最高分, 最低分, 平均分)
"""
max_score = 0
min_score = 10
total_score = 0
valid_scores = 0
retrieve_content = []
# 使用线程池并发计算分数
with ThreadPoolExecutor() as executor:
# 创建任务列表
future_to_content = {}
for result in outputs["result"]:
content = result["content"].strip()
future = executor.submit(self.calculate_score, query=query, content=content)
future_to_content[future] = content
# 收集结果
for future in as_completed(future_to_content):
content = future_to_content[future]
score = future.result()
content_title = content.split("\n")[0]
if score != -1:
max_score = max(max_score, score)
min_score = min(min_score, score)
total_score += score
valid_scores += 1
if content_title:
retrieve_content.append(content_title + f"--相关性得分({score}分)")
avg_score = total_score / valid_scores if valid_scores > 0 else 0
return retrieve_content, max_score, min_score, avg_score
class NewWorkflowChat(BaseWorkflowChat):
"""
新工作流对话类,用于调用新工作流发送对话并解析获取相关数据
"""
def process_question(self, query: str) -> dict:
"""
处理问题,获取新工作流的回答和相关信息
Args:
query: 问题内容
Returns:
dict: 包含问题、回答和相关信息的字典
"""
response, message_id = self.create_chat_message(query)
if isinstance(response, str) and response.startswith("error:"):
raise RuntimeError(f"create_chat_message 出错:{response}")
answer = response["answer"]
workflow_info = self.get_workflow_info(query, message_id)
if workflow_info is None:
return None
result = {
"问题": query,
"新流程答案": answer,
"新问题改写": workflow_info["问题改写"],
"新问题分类": workflow_info["问题分类"],
"槽点信息": workflow_info["槽点信息"],
"新检索词条": workflow_info["检索词条"],
"检索内容": workflow_info["检索内容"],
"message_id":message_id
}
return result
def get_workflow_info(self, query: str, message_id: str) -> dict:
"""
获取新工作流的问题分类和检索信息
Args:
query (str): 用户问题
message_id (str): 新工作流的消息ID
Returns:
dict: 包含问题分类结果的字典
"""
retrieve_title = []
retrieve_content = []
max_score = 0
min_score = 0
avg_score = 0
rewrite_query = ""
vertical_classification = ""
sub_classification = ""
slot_info = ""
try:
message_info = DifyTool.get_message_debug_info_by_id(message_id=message_id)
for workflow_node in message_info["workflow_node_executions_info"]:
if workflow_node["title"] == "知识检索结果后处理":
outputs = json.loads(workflow_node["outputs"])
retrieve_title, max_score, min_score, avg_score = self.get_retrieve_info(query=query, outputs=outputs)
retrieve_content = outputs["result"]
elif workflow_node["title"] == "问题优化结果解析":
outputs = json.loads(workflow_node["outputs"])
rewrite_query = outputs["optimize_query"]
llm_result_json = json.loads(workflow_node['inputs'])["llm_result"]
json_result = json.loads(llm_result_json)
vertical_classification = json_result['vertical_classification']
sub_classification = json_result['sub_classification']
slot_info = json.dumps(json_result["slot_filling"], ensure_ascii=False, indent=2)
except Exception as e:
raise e
return {
"问题改写": rewrite_query,
"检索词条": "\n".join(retrieve_title) if retrieve_title else "未检索知识库",
"检索内容": retrieve_content,
"问题分类": f"{vertical_classification} - {sub_classification}",
"槽点信息": slot_info,
}
class OldWorkFlowChat(BaseWorkflowChat):
"""
旧工作流对话类,用于调用旧工作流发送对话并解析获取相关数据
"""
def process_question(self, query: str) -> dict:
"""
处理问题,获取旧工作流的回答和相关信息
Args:
query: 问题内容
Returns:
dict: 包含问题、回答和相关信息的字典
"""
response, message_id = self.create_chat_message(query)
if isinstance(response, str) and response.startswith("error:"):
return None
answer = response["answer"]
workflow_info = self.get_workflow_info(query, message_id)
if workflow_info is None:
return None
result = {
"问题": query,
"旧流程答案": answer,
"旧问题改写": workflow_info["问题改写"],
"旧检索词条": workflow_info["检索词条"],
"检索内容": workflow_info["检索内容"],
"message_id":message_id
}
return result
def get_workflow_info(self, query: str, message_id: str) -> dict:
"""
获取旧工作流的问题改写和检索信息
Args:
query (str): 用户问题
message_id (str): 旧工作流的消息ID
Returns:
dict: 包含问题改写和检索信息的字典
"""
retrieve_title = []
retrieve_content = []
max_score = 0
min_score = 0
avg_score = 0
rewrite_query = ""
try:
message_info = DifyTool.get_message_debug_info_by_id(message_id=message_id)
for workflow_node in message_info["workflow_node_executions_info"]:
if workflow_node["title"] == "知识检索结果后处理":
outputs = json.loads(workflow_node["outputs"])
retrieve_title, max_score, min_score, avg_score = self.get_retrieve_info(query=query, outputs=outputs)
retrieve_content = outputs["result"]
elif workflow_node["title"] == "问题优化结果解析":
outputs = json.loads(workflow_node["outputs"])
rewrite_query = outputs["optimize_query"]
except Exception as e:
return None
return {
"问题改写": rewrite_query,
"检索词条": "\n".join(retrieve_title) if retrieve_title else "未检索知识库",
"检索内容": retrieve_content,
}
+42
View File
@@ -5,6 +5,18 @@ from typing import List, Optional, Dict
from threading import Lock from threading import Lock
import requests import requests
# 4090dify 中用的硅基流动 apikey
# sk-iuyfpcewztavgnivrllwnegffvrrsyeiuwvjrabngtejsqwy
# sk-skynrwfqvipknbcvjsxkhjaqlivmocpkdppkocjndbyulado
# sk-gjeanmnxtfcqezqagixyexarlxeztkazbrsciqescrfxrgpw
# sk-uapywdmjaylwwyufaivraqwbpqtxjpbsbkltlrmwqftvfech
# sk-dwmxnhaeephbxgsfncbonyajubuhuyhsfqwfsxahlepkiwas
# sk-lnxedlpzufrurrmvylugpccnppwyqdccgeiicoijrqnslcgm
# sk-duccaryfxcrpvwrbwvjbuwjwazyqleyebumhvrutksuqbxug
# sk-njcrhxpvevtxkzbmhkxshxcpwpnjzmccjgfdykdncaxjicez
# sk-bdagppigfxexcofiossccywvcqggbpywjapkdbtqycbgvqpz
# sk-dvbaktabkdwdpjgxyoozlwnejosjyhdgqwllfeborqahndxs
API_KEY_LIST=[ API_KEY_LIST=[
"sk-hrojkkkrrkmsajtnizokbcgexsfggdiqavbtvbayuwqbnmom", "sk-hrojkkkrrkmsajtnizokbcgexsfggdiqavbtvbayuwqbnmom",
"sk-kkdklmnyompoiotzkfqahpayzlkgogfudjkyaebehtsowvid", "sk-kkdklmnyompoiotzkfqahpayzlkgogfudjkyaebehtsowvid",
@@ -56,6 +68,36 @@ API_KEY_LIST=[
"sk-zjwbwyocnuqxfshlpgfzdwlgjjrpewzgvoqwzyhufisidnos", "sk-zjwbwyocnuqxfshlpgfzdwlgjjrpewzgvoqwzyhufisidnos",
"sk-kjxpzjbteiurpzhwjbbjqpjjfoewsahpjtmyqwectdubxhgf", "sk-kjxpzjbteiurpzhwjbbjqpjjfoewsahpjtmyqwectdubxhgf",
"sk-sqdcnhapyzudneipdsuqlfawusrndxqkuwoaoumtonwdnppo", "sk-sqdcnhapyzudneipdsuqlfawusrndxqkuwoaoumtonwdnppo",
"sk-yvyvoiegjrdlgihnxlaaznzdhnvpmfowtwmofomcodaoeaqs",
"sk-vccwuaomxhjcszjhheipoqqmsnuetasiveombkyrptstesbi",
"sk-mxbapcczwjsyrictwgigxgcvdgptyfrlynrewqioegqwrggv",
"sk-dujjzxrknevesbagqgqmuffxsosjoueviubnmodoormlmlzt",
"sk-rpptsvdeifcnyfkkrwnphgkrlchrqrbkglxrmztdzvfutdor",
"sk-lsukfggzghmdhtfhqcbmlfqabbtapwpuxnvtwshqqqlaesie",
"sk-aulumxzhvaladchcwgmsxidtdsvzytbpvzqgfuvcxlwbwcgl",
"sk-tzdqzroakecvseclcmrbhdnepveatybhhzxfpzxzgirpqcdy",
"sk-otxxemniwhxkdvroszmmkitswwuykosnqoldrkzdoflqpgvw",
"sk-zlruqobfdbjebyyvkmehakpcvfgnlfbdlbfrepusazzckbnv",
"sk-zryimztrlkgvcaiolarhvbcewmhwruhqfcndbylonzlqvdox",
"sk-rczjqufgdisqplkrmvhaxmdgcboluvxympvzljlreuqeeviq",
"sk-xfnvcksdgwufsktvmhpqrwpgovsxxtaeehtxnaqjtxmubqzl",
"sk-gcostftlutooxzsnqefcgyfxqytidvfjpxhbuxppgatwczoq",
"sk-wwonvjnowbcxmoyoluynnkjwerghspzdulyidskunkordaft",
"sk-rbuykocecbdoqteveeggwzvrhbvisgaerffexjsnyvjefhdk",
"sk-qmrkfvvbbfssuoreyvwqawoveyowuvxviqzqknotyweqmuog",
"sk-nprpuknjmikvoaxnwgyshwwwtnifvixpuqtzkzmcacdnvoib",
"sk-xanwnicepdxfqrfejzuxjcrhdsglfypkoxlcmmtamrtjkork",
"sk-lvtdgodiaurqyiwdxtdrgxifguychhccqlqkhqctscvqbfgi",
"sk-aedlbtlmqcttxwnvlfmxzaysamocamqxjceoyqjfgpcowybw",
"sk-fahdvndjblyjlizamvwcrxnilsgmbgbvwssxgquhkezgpqne",
"sk-tzludgttzxvpvwayazdbppbauvathdtccafjrhojpemucgyi",
"sk-hrbroidbfusidwnsmxenuzljxgdzzxiimlezygxplavnxjik",
"sk-ylgoiqxmtxeojdnonthxtweungyzldaqarvjxlqyztlvyrff",
"sk-asuqbqwdhjcqnvtjlwufyrkrwkobnrbmukzarvcctsgjipdp",
"sk-dpgpymiydutoexgvkajwgahagnfmcqzafwulccudnzvleifz",
"sk-nbksjgcngsayoumnsdbkcpnqivnvxjenwpzuazzrkhnsgeoo",
"sk-iaafvpjyqiocgzchbdldbkgcffqniahkcbgoviuevuogulcm",
"sk-muvjguqeshyimzowqnqgxwpsgujlpkqgrisxsimthtyrpypx",
] ]
class APIKeyManager: class APIKeyManager: