update

poetry.lock

@@ -162,24 +162,25 @@ doc = ["docutils", "geopandas", "jinja2", "myst-parser", "numpydoc", "pillow", "
 
 [[package]]
 name = "anyio"
-version = "3.6.2"
+version = "3.7.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 category = "main"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7"
 files = [
-    {file = "anyio-3.6.2-py3-none-any.whl", hash = "sha256:fbbe32bd270d2a2ef3ed1c5d45041250284e31fc0a4df4a5a6071842051a51e3"},
-    {file = "anyio-3.6.2.tar.gz", hash = "sha256:25ea0d673ae30af41a0c442f81cf3b38c7e79fdc7b60335a4c14e05eb0947421"},
+    {file = "anyio-3.7.0-py3-none-any.whl", hash = "sha256:eddca883c4175f14df8aedce21054bfca3adb70ffe76a9f607aef9d7fa2ea7f0"},
+    {file = "anyio-3.7.0.tar.gz", hash = "sha256:275d9973793619a5374e1c89a4f4ad3f4b0a5510a2b5b939444bee8f4c4d37ce"},
 ]
 
 [package.dependencies]
+exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"]
-trio = ["trio (>=0.16,<0.22)"]
+doc = ["Sphinx (>=6.1.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme", "sphinxcontrib-jquery"]
+test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (<0.22)"]
 
 [[package]]
 name = "async-timeout"
@@ -573,6 +574,21 @@ tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
 tests = ["Werkzeug (>=1.0.1)", "absl-py", "bert-score (>=0.3.6)", "cer (>=1.2.0)", "charcut (>=1.1.1)", "jiwer", "mauve-text", "nltk", "pytest", "pytest-datadir", "pytest-xdist", "requests-file (>=1.5.1)", "rouge-score (>=0.1.2)", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1,<=2.10)", "texttable (>=1.6.3)", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "torch", "transformers", "trectools", "unidecode (>=1.3.4)"]
 torch = ["torch"]
 
+[[package]]
+name = "exceptiongroup"
+version = "1.1.1"
+description = "Backport of PEP 654 (exception groups)"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "exceptiongroup-1.1.1.tar.gz", hash = "sha256:d484c3090ba2889ae2928419117447a14daf3c1231d5e30d0aae34f354f01785"},
+]
+
+[package.extras]
+test = ["pytest (>=6)"]
+
 [[package]]
 name = "fastapi"
 version = "0.95.2"
@@ -1780,37 +1796,37 @@ files = [
 
 [[package]]
 name = "pandas"
-version = "2.0.1"
+version = "2.0.2"
 description = "Powerful data structures for data analysis, time series, and statistics"
 category = "main"
 optional = false
 python-versions = ">=3.8"
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+    {file = "pandas-2.0.2.tar.gz", hash = "sha256:dd5476b6c3fe410ee95926873f377b856dbc4e81a9c605a0dc05aaccc6a7c6c6"},
 ]
 
 [package.dependencies]
@@ -2420,6 +2436,28 @@ dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
 doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
 test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
+[[package]]
+name = "seaborn"
+version = "0.12.2"
+description = "Statistical data visualization"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "seaborn-0.12.2-py3-none-any.whl", hash = "sha256:ebf15355a4dba46037dfd65b7350f014ceb1f13c05e814eda2c9f5fd731afc08"},
+    {file = "seaborn-0.12.2.tar.gz", hash = "sha256:374645f36509d0dcab895cba5b47daf0586f77bfe3b36c97c607db7da5be0139"},
+]
+
+[package.dependencies]
+matplotlib = ">=3.1,<3.6.1 || >3.6.1"
+numpy = ">=1.17,<1.24.0 || >1.24.0"
+pandas = ">=0.25"
+
+[package.extras]
+dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest-cov", "pytest-xdist"]
+docs = ["ipykernel", "nbconvert", "numpydoc", "pydata_sphinx_theme (==0.10.0rc2)", "pyyaml", "sphinx-copybutton", "sphinx-design", "sphinx-issues"]
+stats = ["scipy (>=1.3)", "statsmodels (>=0.10)"]
+
 [[package]]
 name = "semantic-version"
 version = "2.10.0"
@@ -3152,4 +3190,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "bbcc8691c60f1af515c94a083d2e159fb63c0c5e6af04af7021532b35ebc70d3"
+content-hash = "3a1cc93d8a90f71cb72ce8fdbbb3cbb80392c5a6c983239a3091e6542977dc5c"

src/app.py

@@ -97,9 +97,9 @@ def gradio_predict(url: str):
 with gr.Blocks() as demo:
     gr.Markdown(
         """
-      # Haber sitelerinin başlık, açıklama (spot), tarih ve içerik bilgilerinin Yapay Zeka modeli kullanılarak çıkarılması.
+    # Haber sitelerinin başlık, açıklama (spot), tarih ve içerik bilgilerinin Yapay Zeka modeli kullanılarak çıkarılması.
       Bu çalışmada, belirli haber sitelerinden otomatik olarak başlık, açıklama (spot), tarih ve içerik bilgilerini çıkarabilen bir yapay zeka modeli geliştirilmeye odaklanılmıştır. Bu geliştirme sürecinde, modelin haber sitelerinin içeriklerini anlaması ve ilgili bilgileri doğru bir şekilde tanıması ve çıkarabilmesi için derinlemesine eğitimler gerçekleştirilmiştir. Bu kapsamlı çalışma, haber sitelerinin veri içeriklerinin otomatik çıkarılması ve analizi konusunda önemli bir adımı temsil etmektedir.
-      """
+    """
     )
     with gr.Row():
         with gr.Column():