updater and web server are separated in two docker containers

2024-11-01 15:19:44 +03:00 · 2024-11-01 15:19:44 +03:00 · 3ad7a72515
commit 3ad7a72515
parent 80ad566469
23 changed files with 738 additions and 39 deletions
--- a/.gitignore
+++ b/.gitignore
@ -2,3 +2,5 @@ env
 env/**
 .idea
 .idea/**
+models
+models/**
--- a/.idea/csv-editor.xml
+++ b/.idea/csv-editor.xml
@ -0,0 +1,30 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="CsvFileAttributes">
+    <option name="attributeMap">
+      <map>
+        <entry key="/spam-ru.csv">
+          <value>
+            <Attribute>
+              <option name="separator" value="," />
+            </Attribute>
+          </value>
+        </entry>
+        <entry key="/spam.csv">
+          <value>
+            <Attribute>
+              <option name="separator" value="," />
+            </Attribute>
+          </value>
+        </entry>
+        <entry key="/spam_Emails_data-ru.csv">
+          <value>
+            <Attribute>
+              <option name="separator" value="," />
+            </Attribute>
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>
--- a/.idea/inspectionProfiles/profiles_settings.xml
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Poetry (spam-detector-1)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Poetry (spam-detector-1)" project-jdk-type="Python SDK" />
+</project>
--- a/.idea/modules.xml
+++ b/.idea/modules.xml
@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/spam-detector-1.iml" filepath="$PROJECT_DIR$/.idea/spam-detector-1.iml" />
+    </modules>
+  </component>
+</project>
--- a/.idea/vcs.xml
+++ b/.idea/vcs.xml
@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>
--- a/47
+++ b/47
@ -0,0 +1,47 @@
+# https://stackoverflow.com/a/57374374/2798461
+
+FROM python:3.10-alpine AS dist
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+COPY lib /app/lib
+COPY requirements.txt /app
+COPY src /app/src
+
+
+FROM dist AS installation
+
+RUN apk update
+RUN pip install --upgrade pip
+RUN pip install --no-index --find-links /app/lib nvidia-nccl-cu12
+RUN apk add curl bash gcc g++ cmake make musl-dev
+
+
+FROM installation AS building
+
+RUN pip install -r requirements.txt
+RUN apk del gcc g++ cmake make musl-dev
+
+
+FROM building AS runner
+
+RUN apk add libgomp libstdc++
+
+RUN mkdir /app/nltk_data
+RUN ln -s /app/nltk_data /root/nltk_data
+
+ENV PYTHONPATH=/app
+
+ARG DATASET
+ARG PORT
+
+ENV PORT=${PORT} \
+    DATASET=${DATASET} \
+    WORKING_DIR=/app/nltk_data \
+    FUCKING_DIR=/usr/local/lib/python3.10/site-packages/spam_detector_ai/models \
+    MODELS_DIR=/app/models
+
+RUN python3 -m src.preparer
+
+ENTRYPOINT [ "bash", "-c", "while true; do sleep 1; done" ]
--- a/before-build.sh
+++ b/before-build.sh
@ -0,0 +1,3 @@
+#!/usr/bin/env bash
+
+poetry export -f requirements.txt > requirements.txt
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@ -0,0 +1,26 @@
+services:
+
+  decision-maker:
+    build: ./
+    container_name: spam-detector-decision-maker
+    environment:
+      - PORT=${PORT:-8080}
+    entrypoint: [ "python", "-m", "src.app", "-m" ]
+    volumes:
+      - type: bind
+        source: $DATASET
+        target: /app/dataset.csv
+      - ${MODELS_DIR}:/app/models
+
+  model-updater:
+    build: ./
+    container_name: spam-detector-model-updater
+    environment:
+      - NONE=1
+#    entrypoint: [ "python", "-m", "src.app", "-u", "-d", "/app/dataset.csv" ]
+    entrypoint: [ "bash", "-c", "while true; do sleep 1; done" ]
+    volumes:
+      - type: bind
+        source: $DATASET
+        target: /app/dataset.csv
+      - ${MODELS_DIR}:/app/models/
--- a/lib/nvidia_nccl_cu12-2.23.4-py3-none-any.whl
+++ b/lib/nvidia_nccl_cu12-2.23.4-py3-none-any.whl
--- a/pyproject.toml
+++ b/pyproject.toml
@ -1,12 +1,15 @@
 [tool.poetry]
-name = "spam-detector-1"
+name = "spam-detector"
 version = "0.1.0"
 description = ""
 authors = ["bvn13 <from.github@bvn13.me>"]
 readme = "README.md"
+packages = [
+    { include = "src" }
+]

 [tool.poetry.dependencies]
-python = "^3.12"
+python = "^3.10"
 scikit-learn = "^1.5.2"
 numpy = "^2.1.2"
 spam-detector-ai = "^2.1.18"
@ -19,7 +22,11 @@ googletrans = "^4.0.0rc1"
 tqdm = "^4.66.5"
 tornado = "^6.4.1"
 asyncio = "^3.4.3"
+exceptiongroup = "^1.0.0rc8"
+scheduler = "^0.8.7"

+[tool.poetry.scripts]
+app = "src.app:start"

 [build-system]
 requires = ["poetry-core"]
--- a/requirements.txt
+++ b/requirements.txt
@ -0,0 +1,498 @@
+asyncio==3.4.3 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:83360ff8bc97980e4ff25c964c7bd3923d333d177aa4f7fb736b019f26c7cb41 \
+    --hash=sha256:b62c9157d36187eca799c378e572c969f0da87cd5fc42ca372d92cdb06e7e1de \
+    --hash=sha256:c46a87b48213d7464f22d9a497b9eef8c1928b68320a2fa94240f969f6fec08c \
+    --hash=sha256:c4d18b22701821de07bd6aea8b53d21449ec0ec5680645e5317062ea21817d2d
+certifi==2024.8.30 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8 \
+    --hash=sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9
+chardet==3.0.4 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae \
+    --hash=sha256:fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691
+charset-normalizer==3.4.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:0099d79bdfcf5c1f0c2c72f91516702ebf8b0b8ddd8905f97a8aecf49712c621 \
+    --hash=sha256:0713f3adb9d03d49d365b70b84775d0a0d18e4ab08d12bc46baa6132ba78aaf6 \
+    --hash=sha256:07afec21bbbbf8a5cc3651aa96b980afe2526e7f048fdfb7f1014d84acc8b6d8 \
+    --hash=sha256:0b309d1747110feb25d7ed6b01afdec269c647d382c857ef4663bbe6ad95a912 \
+    --hash=sha256:0d99dd8ff461990f12d6e42c7347fd9ab2532fb70e9621ba520f9e8637161d7c \
+    --hash=sha256:0de7b687289d3c1b3e8660d0741874abe7888100efe14bd0f9fd7141bcbda92b \
+    --hash=sha256:1110e22af8ca26b90bd6364fe4c763329b0ebf1ee213ba32b68c73de5752323d \
+    --hash=sha256:130272c698667a982a5d0e626851ceff662565379baf0ff2cc58067b81d4f11d \
+    --hash=sha256:136815f06a3ae311fae551c3df1f998a1ebd01ddd424aa5603a4336997629e95 \
+    --hash=sha256:14215b71a762336254351b00ec720a8e85cada43b987da5a042e4ce3e82bd68e \
+    --hash=sha256:1db4e7fefefd0f548d73e2e2e041f9df5c59e178b4c72fbac4cc6f535cfb1565 \
+    --hash=sha256:1ffd9493de4c922f2a38c2bf62b831dcec90ac673ed1ca182fe11b4d8e9f2a64 \
+    --hash=sha256:2006769bd1640bdf4d5641c69a3d63b71b81445473cac5ded39740a226fa88ab \
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+    --hash=sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de
+colorama==0.4.6 ; python_version >= "3.10" and python_version < "4.0" and (platform_system == "Windows" or sys_platform == "win32") \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+exceptiongroup==1.2.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \
+    --hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc
+googletrans==4.0.0rc1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:74df47b092e2d566522019d149e3f1d75732570ad76eaf8e14aebeffc126c372
+h11==0.9.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:33d4bca7be0fa039f4e84d50ab00531047e53d6ee8ffbc83501ea602c169cae1 \
+    --hash=sha256:4bc6d6a1238b7615b266ada57e0618568066f57dd6fa967d1290ec9309b2f2f1
+h2==3.2.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:61e0f6601fa709f35cdb730863b4e5ec7ad449792add80d1410d4174ed139af5 \
+    --hash=sha256:875f41ebd6f2c44781259005b157faed1a5031df3ae5aa7bcb4628a6c0782f14
+hpack==3.0.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:0edd79eda27a53ba5be2dfabf3b15780928a0dff6eb0c60a3d6767720e970c89 \
+    --hash=sha256:8eec9c1f4bfae3408a3f30500261f7e6a65912dc138526ea054f9ad98892e9d2
+hstspreload==2024.10.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:2859a6b52253743ddddad468d8c9570ba650170ca49ac416336826915ee409b8 \
+    --hash=sha256:3ab481036cbdff095cb411dafe33ee7924492319cf6ddaf4e776a159537541b3
+httpcore==0.9.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:9850fe97a166a794d7e920590d5ec49a05488884c9fc8b5dba8561effab0c2a0 \
+    --hash=sha256:ecc5949310d9dae4de64648a4ce529f86df1f232ce23dcfefe737c24d21dfbe9
+httpx==0.13.3 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:32d930858eab677bc29a742aaa4f096de259f1c78c68a90ad11f5c3c04f08335 \
+    --hash=sha256:3642bd13e90b80ba8a243a730275eb10a4c26ec96f5fc16b87e458d4ab21efae
+hyperframe==5.2.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:5187962cb16dcc078f23cb5a4b110098d546c3f41ff2d4038a9896893bbd0b40 \
+    --hash=sha256:a9f5c17f2cc3c719b917c4f33ed1c61bd1f8dfac4b1bd23b7c80b3400971b41f
+idna==2.10 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:b307872f855b18632ce0c21c5e45be78c0ea7ae4c15c828c20788b26921eb3f6 \
+    --hash=sha256:b97d804b1e9b523befed77c48dacec60e6dcb0b5391d57af6a65a312a90648c0
+imbalanced-learn==0.12.4 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:8153ba385d296b07d97e0901a2624a86c06b48c94c2f92da3a5354827697b7a3 \
+    --hash=sha256:d47fc599160d3ea882e712a3a6b02bdd353c1a6436d8d68d41b1922e6ee4a703
+imblearn==0.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:d42c2d709d22c00d2b9a91e638d57240a8b79b4014122d92181fcd2549a2f79a \
+    --hash=sha256:d8fbb662919c1b16f438ad91a8256220e53bcf6815c9ad5502c518b798de34f2
+iniconfig==2.0.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3 \
+    --hash=sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374
+joblib==1.4.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6 \
+    --hash=sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e
+nltk==3.9.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:4fa26829c5b00715afe3061398a8989dc643b92ce7dd93fb4585a70930d168a1 \
+    --hash=sha256:87d127bd3de4bd89a4f81265e5fa59cb1b199b27440175370f7417d2bc7ae868
+numpy==2.1.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:05b2d4e667895cc55e3ff2b56077e4c8a5604361fc21a042845ea3ad67465aa8 \
+    --hash=sha256:12edb90831ff481f7ef5f6bc6431a9d74dc0e5ff401559a71e5e4611d4f2d466 \
+    --hash=sha256:13311c2db4c5f7609b462bc0f43d3c465424d25c626d95040f073e30f7570e35 \
+    --hash=sha256:13532a088217fa624c99b843eeb54640de23b3414b14aa66d023805eb731066c \
+    --hash=sha256:13602b3174432a35b16c4cfb5de9a12d229727c3dd47a6ce35111f2ebdf66ff4 \
+    --hash=sha256:1600068c262af1ca9580a527d43dc9d959b0b1d8e56f8a05d830eea39b7c8af6 \
+    --hash=sha256:1b8cde4f11f0a975d1fd59373b32e2f5a562ade7cde4f85b7137f3de8fbb29a0 \
+    --hash=sha256:1c193d0b0238638e6fc5f10f1b074a6993cb13b0b431f64079a509d63d3aa8b7 \
+    --hash=sha256:1ebec5fd716c5a5b3d8dfcc439be82a8407b7b24b230d0ad28a81b61c2f4659a \
+    --hash=sha256:242b39d00e4944431a3cd2db2f5377e15b5785920421993770cddb89992c3f3a \
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+    --hash=sha256:2abbf905a0b568706391ec6fa15161fad0fb5d8b68d73c461b3c1bab6064dd62 \
+    --hash=sha256:2cbba4b30bf31ddbe97f1c7205ef976909a93a66bb1583e983adbd155ba72ac2 \
+    --hash=sha256:2ffef621c14ebb0188a8633348504a35c13680d6da93ab5cb86f4e54b7e922b5 \
+    --hash=sha256:30d53720b726ec36a7f88dc873f0eec8447fbc93d93a8f079dfac2629598d6ee \
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+    --hash=sha256:43cca367bf94a14aca50b89e9bc2061683116cfe864e56740e083392f533ce7a \
+    --hash=sha256:456e3b11cb79ac9946c822a56346ec80275eaf2950314b249b512896c0d2505e \
+    --hash=sha256:4d6ec0d4222e8ffdab1744da2560f07856421b367928026fb540e1945f2eeeaf \
+    --hash=sha256:5006b13a06e0b38d561fab5ccc37581f23c9511879be7693bd33c7cd15ca227c \
+    --hash=sha256:675c741d4739af2dc20cd6c6a5c4b7355c728167845e3c6b0e824e4e5d36a6c3 \
+    --hash=sha256:6cdb606a7478f9ad91c6283e238544451e3a95f30fb5467fbf715964341a8a86 \
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+    --hash=sha256:c82af4b2ddd2ee72d1fc0c6695048d457e00b3582ccde72d8a1c991b808bb20f \
+    --hash=sha256:d666cb72687559689e9906197e3bec7b736764df6a2e58ee265e360663e9baf7 \
+    --hash=sha256:d7bf0a4f9f15b32b5ba53147369e94296f5fffb783db5aacc1be15b4bf72f43b \
+    --hash=sha256:d82075752f40c0ddf57e6e02673a17f6cb0f8eb3f587f63ca1eaab5594da5b17 \
+    --hash=sha256:da65fb46d4cbb75cb417cddf6ba5e7582eb7bb0b47db4b99c9fe5787ce5d91f5 \
+    --hash=sha256:e2b49c3c0804e8ecb05d59af8386ec2f74877f7ca8fd9c1e00be2672e4d399b1 \
+    --hash=sha256:e585c8ae871fd38ac50598f4763d73ec5497b0de9a0ab4ef5b69f01c6a046142 \
+    --hash=sha256:e8d3ca0a72dd8846eb6f7dfe8f19088060fcb76931ed592d29128e0219652884 \
+    --hash=sha256:ef444c57d664d35cac4e18c298c47d7b504c66b17c2ea91312e979fcfbdfb08a \
+    --hash=sha256:f1eb068ead09f4994dec71c24b2844f1e4e4e013b9629f812f292f04bd1510d9 \
+    --hash=sha256:f2ded8d9b6f68cc26f8425eda5d3877b47343e68ca23d0d0846f4d312ecaa445 \
+    --hash=sha256:f751ed0a2f250541e19dfca9f1eafa31a392c71c832b6bb9e113b10d050cb0f1 \
+    --hash=sha256:faa88bc527d0f097abdc2c663cddf37c05a1c2f113716601555249805cf573f1 \
+    --hash=sha256:fc44e3c68ff00fd991b59092a54350e6e4911152682b4782f68070985aa9e648
+nvidia-nccl-cu12==2.23.4 ; platform_system == "Linux" and platform_machine != "aarch64" and python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:aa946c8327e22ced28e7cef508a334673abc42064ec85f02d005ba1785ea4cec \
+    --hash=sha256:b097258d9aab2fa9f686e33c6fe40ae57b27df60cedbd15d139701bb5509e0c1
+packaging==24.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002 \
+    --hash=sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124
+pandas==2.2.3 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:062309c1b9ea12a50e8ce661145c6aab431b1e99530d3cd60640e255778bd43a \
+    --hash=sha256:15c0e1e02e93116177d29ff83e8b1619c93ddc9c49083f237d4312337a61165d \
+    --hash=sha256:1948ddde24197a0f7add2bdc4ca83bf2b1ef84a1bc8ccffd95eda17fd836ecb5 \
+    --hash=sha256:1db71525a1538b30142094edb9adc10be3f3e176748cd7acc2240c2f2e5aa3a4 \
+    --hash=sha256:22a9d949bfc9a502d320aa04e5d02feab689d61da4e7764b62c30b991c42c5f0 \
+    --hash=sha256:29401dbfa9ad77319367d36940cd8a0b3a11aba16063e39632d98b0e931ddf32 \
+    --hash=sha256:31d0ced62d4ea3e231a9f228366919a5ea0b07440d9d4dac345376fd8e1477ea \
+    --hash=sha256:3508d914817e153ad359d7e069d752cdd736a247c322d932eb89e6bc84217f28 \
+    --hash=sha256:37e0aced3e8f539eccf2e099f65cdb9c8aa85109b0be6e93e2baff94264bdc6f \
+    --hash=sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348 \
+    --hash=sha256:38cf8125c40dae9d5acc10fa66af8ea6fdf760b2714ee482ca691fc66e6fcb18 \
+    --hash=sha256:3b71f27954685ee685317063bf13c7709a7ba74fc996b84fc6821c59b0f06468 \
+    --hash=sha256:3fc6873a41186404dad67245896a6e440baacc92f5b716ccd1bc9ed2995ab2c5 \
+    --hash=sha256:4850ba03528b6dd51d6c5d273c46f183f39a9baf3f0143e566b89450965b105e \
+    --hash=sha256:4f18ba62b61d7e192368b84517265a99b4d7ee8912f8708660fb4a366cc82667 \
+    --hash=sha256:56534ce0746a58afaf7942ba4863e0ef81c9c50d3f0ae93e9497d6a41a057645 \
+    --hash=sha256:59ef3764d0fe818125a5097d2ae867ca3fa64df032331b7e0917cf5d7bf66b13 \
+    --hash=sha256:5dbca4c1acd72e8eeef4753eeca07de9b1db4f398669d5994086f788a5d7cc30 \
+    --hash=sha256:5de54125a92bb4d1c051c0659e6fcb75256bf799a732a87184e5ea503965bce3 \
+    --hash=sha256:61c5ad4043f791b61dd4752191d9f07f0ae412515d59ba8f005832a532f8736d \
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+    --hash=sha256:63cc132e40a2e084cf01adf0775b15ac515ba905d7dcca47e9a251819c575ef3 \
+    --hash=sha256:66108071e1b935240e74525006034333f98bcdb87ea116de573a6a0dccb6c039 \
+    --hash=sha256:6dfcb5ee8d4d50c06a51c2fffa6cff6272098ad6540aed1a76d15fb9318194d8 \
+    --hash=sha256:7c2875855b0ff77b2a64a0365e24455d9990730d6431b9e0ee18ad8acee13dbd \
+    --hash=sha256:7eee9e7cea6adf3e3d24e304ac6b8300646e2a5d1cd3a3c2abed9101b0846761 \
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+    --hash=sha256:8cd6d7cc958a3910f934ea8dbdf17b2364827bb4dafc38ce6eef6bb3d65ff09c \
+    --hash=sha256:99df71520d25fade9db7c1076ac94eb994f4d2673ef2aa2e86ee039b6746d20c \
+    --hash=sha256:a5a1595fe639f5988ba6a8e5bc9649af3baf26df3998a0abe56c02609392e0a4 \
+    --hash=sha256:ad5b65698ab28ed8d7f18790a0dc58005c7629f227be9ecc1072aa74c0c1d43a \
+    --hash=sha256:b1d432e8d08679a40e2a6d8b2f9770a5c21793a6f9f47fdd52c5ce1948a5a8a9 \
+    --hash=sha256:b8661b0238a69d7aafe156b7fa86c44b881387509653fdf857bebc5e4008ad42 \
+    --hash=sha256:ba96630bc17c875161df3818780af30e43be9b166ce51c9a18c1feae342906c2 \
+    --hash=sha256:bc6b93f9b966093cb0fd62ff1a7e4c09e6d546ad7c1de191767baffc57628f39 \
+    --hash=sha256:c124333816c3a9b03fbeef3a9f230ba9a737e9e5bb4060aa2107a86cc0a497fc \
+    --hash=sha256:cd8d0c3be0515c12fed0bdbae072551c8b54b7192c7b1fda0ba56059a0179698 \
+    --hash=sha256:d9c45366def9a3dd85a6454c0e7908f2b3b8e9c138f5dc38fed7ce720d8453ed \
+    --hash=sha256:f00d1345d84d8c86a63e476bb4955e46458b304b9575dcf71102b5c705320015 \
+    --hash=sha256:f3a255b2c19987fbbe62a9dfd6cff7ff2aa9ccab3fc75218fd4b7530f01efa24 \
+    --hash=sha256:fffb8ae78d8af97f849404f21411c95062db1496aeb3e56f146f0355c9989319
+pluggy==1.5.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1 \
+    --hash=sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669
+pytest==8.3.3 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181 \
+    --hash=sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2
+python-dateutil==2.9.0.post0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
+    --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
+pytz==2024.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a \
+    --hash=sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725
+regex==2024.9.11 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:01c2acb51f8a7d6494c8c5eafe3d8e06d76563d8a8a4643b37e9b2dd8a2ff623 \
+    --hash=sha256:02087ea0a03b4af1ed6ebab2c54d7118127fee8d71b26398e8e4b05b78963199 \
+    --hash=sha256:040562757795eeea356394a7fb13076ad4f99d3c62ab0f8bdfb21f99a1f85664 \
+    --hash=sha256:042c55879cfeb21a8adacc84ea347721d3d83a159da6acdf1116859e2427c43f \
+    --hash=sha256:079400a8269544b955ffa9e31f186f01d96829110a3bf79dc338e9910f794fca \
+    --hash=sha256:07f45f287469039ffc2c53caf6803cd506eb5f5f637f1d4acb37a738f71dd066 \
+    --hash=sha256:09d77559e80dcc9d24570da3745ab859a9cf91953062e4ab126ba9d5993688ca \
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+    --hash=sha256:fef8c87f8abfb884dac04e97824b61299880c43f4ce675dd2cbeadd3c9b466d2
+six==1.16.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926 \
+    --hash=sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254
+sniffio==1.3.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2 \
+    --hash=sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc
+spam-detector-ai==2.1.18 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:315c789255db8966bd3d6b2510affd6e229401c31349c00435fa2bec0dd4fee4 \
+    --hash=sha256:809dda6a5edee72d4cd7c22129d1fea92d94d706772ff135051abe7b40839de7
+threadpoolctl==3.5.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:082433502dd922bf738de0d8bcc4fdcbf0979ff44c42bd40f5af8a282f6fa107 \
+    --hash=sha256:56c1e26c150397e58c4926da8eeee87533b1e32bef131bd4bf6a2f45f3185467
+tomli==2.0.2 ; python_version >= "3.10" and python_version < "3.11" \
+    --hash=sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38 \
+    --hash=sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed
+tornado==6.4.1 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8 \
+    --hash=sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f \
+    --hash=sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4 \
+    --hash=sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3 \
+    --hash=sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14 \
+    --hash=sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842 \
+    --hash=sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9 \
+    --hash=sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698 \
+    --hash=sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7 \
+    --hash=sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d \
+    --hash=sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4
+tqdm==4.66.6 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:223e8b5359c2efc4b30555531f09e9f2f3589bcd7fdd389271191031b49b7a63 \
+    --hash=sha256:4bdd694238bef1485ce839d67967ab50af8f9272aab687c0d7702a01da0be090
+typeguard==4.4.0 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:463bd8697a65a4aa576a63767c369b1ecfba8a5ba735edfe3223127b6ecfa28c \
+    --hash=sha256:8ca34c14043f53b2caae7040549ba431770869bcd6287cfa8239db7ecb882b4a
+typing-extensions==4.12.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \
+    --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8
+tzdata==2024.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc \
+    --hash=sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd
+urllib3==2.2.3 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac \
+    --hash=sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9
+xgboost==2.1.2 ; python_version >= "3.10" and python_version < "4.0" \
+    --hash=sha256:151071c22d0f5637739ccaf057f57d05983caaba557cc3d8191c2cb8ce8ae659 \
+    --hash=sha256:30a23db30a7c958917fce9f0467eab8920480d064a4bb74de693e0680528163f \
+    --hash=sha256:69f1e1038e594d28d6f74252685495eba9de4983e95c87d1e93706fa5f720b02 \
+    --hash=sha256:93782c35e8a2c2eb124eb68186c3238f270ee868c654f65b47f0d594376b25d6 \
+    --hash=sha256:9efbdb262cce5e6d71123748ee8c0c4e6cf66d9c9207dae71f645116717c1f00 \
+    --hash=sha256:a8abdcc48d68cad22812df43a16cfc8314dcf771064b63ada9d73399129c8fdc \
+    --hash=sha256:bfa7e6cecf7b62319379f0d4b04b966e84a933adcde0405061b9ddb0d0aef6b1 \
+    --hash=sha256:ec49df8017e729244e08ffb4904659f3f0b6f3c8ca11c90a5ca501ab9cc8c8ce
--- a/src/main.py
+++ b/src/main.py
@ -0,0 +1,3 @@
+import src.app
+
+src.app.start()
--- a/src/app.py
+++ b/src/app.py
@ -1,27 +1,36 @@
 import argparse
 import os
-from dataset.preparer import download_words
-from model.trainer import train
-import web.server
-import model.updater
+import src.model.trainer as model_trainer
+import src.web.server as web_server
+import src.model.updater as model_updater


-parser = argparse.ArgumentParser(prog='Antispam complex')
+parser = argparse.ArgumentParser(prog='app.py')
 parser.add_argument('-i', '--init', action=argparse.BooleanOptionalAction, help='Initializing, must be run beforehand, --dataset is required')
 parser.add_argument('-m', '--decision-maker', action=argparse.BooleanOptionalAction, help='Start as Decision maker')
 parser.add_argument('-d', '--dataset', required=False, help='Path to CSV (ham/spam) dataset')
-parser.add_argument('-u', '--model-updater', required=False, help='Start as Model updater')
+parser.add_argument('-u', '--model-updater', action=argparse.BooleanOptionalAction, help='Start as Model updater')
 args = parser.parse_args()

+assert (args.init is not None
+        or args.decision_maker is not None
+        or args.model_updater is not None), "No mode set. Run --help"

 _port = 8080 if os.getenv('PORT') is None else os.getenv('PORT')
+_models_dir = os.getenv("MODELS_DIR")
+_fucking_dir = os.getenv("FUCKING_DIR")
+
+def start():
+    if args.init:
+        assert args.dataset is not None, "Dataset is required, run --help"
+        model_trainer.train(args.dataset, fucking_path=_fucking_dir, backup_path=_models_dir)
+    elif args.decision_maker:
+        model_trainer.apply_latest(fucking_path=_fucking_dir, backup_path=_models_dir)
+        web_server.start(port=_port)
+    elif args.model_updater:
+        assert args.dataset is not None, "Dataset is required, run --help"
+        model_updater.start(fucking_path=_fucking_dir, models_dir=_models_dir, dataset_path=args.dataset)
+

 if __name__ == '__main__':
-    if args.init:
-        assert args.dataset is not None, "Dataset is required, show --help"
-        download_words()
-        train(args.dataset)
-    elif args.decision_maker:
-        web.server.start(port=_port)
-    elif args.model_updater:
-        model.updater.start()
+    start()
--- a/src/dataset/preparer.py
+++ b/src/dataset/preparer.py
@ -1,5 +0,0 @@
-import nltk
-
-def download_words() -> None:
-    nltk.download('wordnet')
-    nltk.download('stopwords')
--- a/src/l/init.py
+++ b/src/l/init.py
--- a/src/logging/logger.py
+++ b/src/logging/logger.py
--- a/src/logging/init.py
+++ b/src/logging/init.py
--- a/src/model/trainer.py
+++ b/src/model/trainer.py
@ -1,12 +1,27 @@
 # spam_detector_ai/trainer.py
 import os
-import sys
-from pathlib import Path
+import shutil
+from os.path import isfile, join
+from src.l.logger import logger
+
+
+def _does_file_exist_in_dir(path):
+    return any(isfile(join(path, i)) for i in os.listdir(path))
+
+def apply_latest(fucking_path: str, backup_path: str) -> None:
+    logger.info("Applying models...")
+    if _does_file_exist_in_dir(backup_path):
+        files = os.listdir(fucking_path)
+        for file in files:
+            shutil.rmtree(os.path.join(fucking_path, file))
+        shutil.copytree(backup_path, fucking_path,
+                        copy_function=shutil.copy2,
+                        dirs_exist_ok=True)
+
+def train(dataset_path: str, fucking_path: str, backup_path: str) -> None:
    from sklearn.model_selection import train_test_split
    from spam_detector_ai.classifiers.classifier_types import ClassifierType
    from spam_detector_ai.training.train_models import ModelTrainer
-from src.logging.logger import logger
-

    def _train_model(classifier_type, model_filename, vectoriser_filename, X_train, y_train):
        logger.info(f'Training {classifier_type}')
@ -14,11 +29,10 @@ def _train_model(classifier_type, model_filename, vectoriser_filename, X_train,
        trainer_.train(X_train, y_train)
        trainer_.save_model(model_filename, vectoriser_filename)

-
-def train(data_path: str) -> None:
+    logger.info(f"Starting to train using data_path={dataset_path}")
    # Load and preprocess data once
    # data_path = os.path.join(project_root, 'spam.csv')
-    initial_trainer = ModelTrainer(data_path=data_path, logger=logger)
+    initial_trainer = ModelTrainer(data_path=dataset_path, logger=logger)
    processed_data = initial_trainer.preprocess_data_()

    # Split the data once
@ -38,3 +52,12 @@ def train(data_path: str) -> None:
    logger.info(f"Train each model with the pre-split data\n")
    for ct, mf, vf in configurations:
        _train_model(ct, mf, vf, X__train, y__train)
+
+    logger.info("Backing up...")
+    files = os.listdir(backup_path)
+    for file in files:
+        shutil.rmtree(os.path.join(backup_path, file))
+    shutil.copytree(fucking_path, backup_path,
+                    copy_function=shutil.copy2,
+                    dirs_exist_ok=True)
+    logger.info("Backing up - done")
--- a/src/model/updater.py
+++ b/src/model/updater.py
@ -1,5 +1,27 @@
-from src.logging.logger import logger
+import datetime as dt
+from src.l.logger import logger
+import src.model.trainer as trainer
+from scheduler import Scheduler
+from os import listdir
+import time


-def start() -> None:
+def _does_file_exist_in_dir(path):
+    return len(listdir(path)) > 0
+
+def start(fucking_path: str, models_dir: str, dataset_path: str) -> None:
    logger.info("Starting...")
+
+    def train() -> None:
+        trainer.train(dataset_path, fucking_path=fucking_path, backup_path=models_dir)
+
+    tz_moscow = dt.timezone(dt.timedelta(hours=3))
+    scheduler = Scheduler(tzinfo=dt.timezone.utc)
+    if not _does_file_exist_in_dir(models_dir):
+        logger.info("Will be updated in 5 seconds...")
+        scheduler.once(dt.timedelta(seconds=5), train)
+    scheduler.daily(dt.time(hour=3, minute=0, tzinfo=tz_moscow), train)
+    print(scheduler)
+    while True:
+        scheduler.exec_jobs()
+        time.sleep(1)
--- a/src/preparer.py
+++ b/src/preparer.py
@ -0,0 +1,7 @@
+import nltk
+import os
+
+_working_dir = os.getenv("WORKING_DIR")
+
+nltk.download('wordnet', download_dir=_working_dir)
+nltk.download('stopwords', download_dir=_working_dir)
--- a/src/translate-dataset.py
+++ b/src/translate-dataset.py
@ -15,7 +15,7 @@ parser = argparse.ArgumentParser(prog='translate-dataset')
 parser.add_argument('-i', '--input', help='Source file')
 parser.add_argument('-o', '--output', help='Destination file')
 args = parser.parse_args()
-#/home/bvn13/develop/spam-detector-1/spam.csv
+#/home/bvn13/develop/spam-detector/spam.csv

 translator = Translator()

--- a/src/web/server.py
+++ b/src/web/server.py
@ -3,7 +3,7 @@ import json
 import os
 import tornado
 from spam_detector_ai.prediction.predict import VotingSpamDetector
-from src.logging.logger import logger
+from src.l.logger import logger


 _spam_detector = VotingSpamDetector()