From 4b5bd41a887a4084feee48d48ff05976383fd6bb Mon Sep 17 00:00:00 2001 From: Erick Vivas <88099754+erickvivas415@users.noreply.github.com> Date: Mon, 11 Nov 2024 01:12:23 +0000 Subject: [PATCH 1/4] Main --- app.py | 63 +++- models/tokenizer.pickle | Bin 0 -> 206104 bytes models/uci_sentimentanalysis.h5 | Bin 0 -> 1631944 bytes notebooks/US_02.ipynb | 577 ++++++++++++++++++++++++++++++++ templates/form.html | 34 +- 5 files changed, 666 insertions(+), 8 deletions(-) create mode 100644 models/tokenizer.pickle create mode 100644 models/uci_sentimentanalysis.h5 create mode 100644 notebooks/US_02.ipynb diff --git a/app.py b/app.py index c48f6d9..9d6559a 100644 --- a/app.py +++ b/app.py @@ -1,9 +1,64 @@ +import pickle +from tensorflow.keras.models import load_model +from tensorflow.keras.preprocessing import sequence + from flask import Flask, render_template, request +from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer + app = Flask(__name__) + +model = None +tokenizer = None +loaded = False # Flag to ensure loading happens only once + +def load_keras_model(): + global model + try: + model = load_model('models/uci_sentimentanalysis.h5') + print("Model loaded successfully.") + except Exception as e: + print(f"Error loading model: {e}") + +def load_tokenizer(): + global tokenizer + try: + with open('models/tokenizer.pickle', 'rb') as handle: + tokenizer = pickle.load(handle) + print("Tokenizer loaded successfully.") + except Exception as e: + print(f"Error loading tokenizer: {e}") + +# Befor_first_request was not working with the keras version i have isntalled +@app.before_request +def before_request(): + global loaded + if not loaded: + load_keras_model() + load_tokenizer() + loaded = True # Set the flag to True to prevent reloading + +def sentiment_analysis(input_text): + if tokenizer is None or model is None: + return "Model or tokenizer not loaded." + + user_sequences = tokenizer.texts_to_sequences([input_text]) + user_sequences_matrix = sequence.pad_sequences(user_sequences, maxlen=1225) + prediction = model.predict(user_sequences_matrix) + + return round(float(prediction[0][0]), 2) + @app.route("/", methods=["GET", "POST"]) def index(): - # TODO: Write the code that calls the sentiment analysis functions here. - # hint: use request.method == "POST" - return render_template('form.html') + sentiment = {} + if request.method == "POST": + text = request.form.get("user_text") # Get user input + if text: + analyzer = SentimentIntensityAnalyzer() + sentiment = analyzer.polarity_scores(text) # VADER analysis + sentiment["custom model positive"] = sentiment_analysis(text) # Custom model analysis + + return render_template('form.html', sentiment=sentiment) + if __name__ == "__main__": - app.run() + app.run(debug=True) + diff --git a/models/tokenizer.pickle b/models/tokenizer.pickle new file mode 100644 index 0000000000000000000000000000000000000000..bcc876a78025bb7964bbb62240fb7112c51cee6b GIT binary patch literal 206104 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"wDR9jCIVpck3", + "outputId": "f2d5cb78-b1cc-49b0-ed4f-8ca8f5d349c6" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "100 84188 0 84188 0 0 143k 0 --:--:-- --:--:-- --:--:-- 143k\n", + "Archive: uci-labelled-sentences.zip\n", + " creating: sentiment labelled sentences/\n", + " inflating: sentiment labelled sentences/.DS_Store \n", + " creating: __MACOSX/\n", + " creating: __MACOSX/sentiment labelled sentences/\n", + " inflating: __MACOSX/sentiment labelled sentences/._.DS_Store \n", + " inflating: sentiment labelled sentences/amazon_cells_labelled.txt \n", + " inflating: sentiment labelled sentences/imdb_labelled.txt \n", + " inflating: __MACOSX/sentiment labelled sentences/._imdb_labelled.txt \n", + " inflating: sentiment labelled sentences/readme.txt \n", + " inflating: __MACOSX/sentiment labelled sentences/._readme.txt \n", + " inflating: sentiment labelled sentences/yelp_labelled.txt \n", + " inflating: __MACOSX/._sentiment labelled sentences \n" + ] + } + ], + "source": [ + "# download dataset from the UCI website\n", + "!curl -o uci-labelled-sentences.zip https://archive.ics.uci.edu/static/public/331/sentiment+labelled+sentences.zip\n", + "\n", + "# unzip dataset in Colab\n", + "!unzip uci-labelled-sentences.zip" + ] + }, + { + "cell_type": "code", + "source": [ + "import pandas as pd\n", + "import pickle\n", + "from sklearn.model_selection import train_test_split\n", + "from tensorflow.keras.preprocessing.text import Tokenizer\n", + "from keras.preprocessing.sequence import pad_sequences\n", + "from keras.models import Sequential\n", + "from keras.layers import Dense, Embedding, LSTM\n", + "from keras.callbacks import EarlyStopping" + ], + "metadata": { + "id": "hl25OnZ7pmAz" + }, + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# download dataset from the UCI website\n", + "!curl -o uci-labelled-sentences.zip https://archive.ics.uci.edu/static/public/331/sentiment+labelled+sentences.zip\n", + "\n", + "# unzip dataset in Colab\n", + "!unzip uci-labelled-sentences.zip" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ObzFyA7diey3", + "outputId": "283c3183-a803-4731-eebf-d0b7e9ba817f" + }, + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + "\r 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r100 84188 0 84188 0 0 646k 0 --:--:-- --:--:-- --:--:-- 647k\n", + "Archive: uci-labelled-sentences.zip\n", + " creating: sentiment labelled sentences/\n", + " inflating: sentiment labelled sentences/.DS_Store \n", + " creating: __MACOSX/\n", + " creating: __MACOSX/sentiment labelled sentences/\n", + " inflating: __MACOSX/sentiment labelled sentences/._.DS_Store \n", + " inflating: sentiment labelled sentences/amazon_cells_labelled.txt \n", + " inflating: sentiment labelled sentences/imdb_labelled.txt \n", + " inflating: __MACOSX/sentiment labelled sentences/._imdb_labelled.txt \n", + " inflating: sentiment labelled sentences/readme.txt \n", + " inflating: __MACOSX/sentiment labelled sentences/._readme.txt \n", + " inflating: sentiment labelled sentences/yelp_labelled.txt \n", + " inflating: __MACOSX/._sentiment labelled sentences \n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "df_list = []\n", + "\n", + "# Yelp\n", + "df_yelp = pd.read_csv('sentiment labelled sentences/yelp_labelled.txt', names=['sentence', 'label'], sep='\\t')\n", + "df_yelp['source'] = 'yelp'\n", + "df_list.append(df_yelp)\n", + "\n", + "# Amazon\n", + "df_amazon = pd.read_csv('sentiment labelled sentences/amazon_cells_labelled.txt', names=['sentence', 'label'], sep='\\t')\n", + "df_amazon['source'] = 'amazon'\n", + "df_list.append(df_amazon)\n", + "\n", + "# IMDB\n", + "df_imdb = pd.read_csv('sentiment labelled sentences/imdb_labelled.txt', names=['sentence', 'label'], sep='\\t')\n", + "df_imdb['source'] = 'imdb'\n", + "df_list.append(df_imdb)\n", + "\n", + "# Concatenate the dataframes\n", + "df = pd.concat(df_list)\n", + "\n", + "df.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 206 + }, + "id": "ym148xwIild2", + "outputId": "271905f5-4fa5-4f25-c7d6-6ea16746bc6a" + }, + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " sentence label source\n", + "0 Wow... Loved this place. 1 yelp\n", + "1 Crust is not good. 0 yelp\n", + "2 Not tasty and the texture was just nasty. 0 yelp\n", + "3 Stopped by during the late May bank holiday of... 1 yelp\n", + "4 The selection on the menu was great and so wer... 1 yelp" + ], + "text/html": [ + "\n", + "

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0Wow... Loved this place.1yelp
1Crust is not good.0yelp
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3Stopped by during the late May bank holiday of...1yelp
4The selection on the menu was great and so wer...1yelp
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\n", + "\n", + "
\n", + "
\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "df", + "summary": "{\n \"name\": \"df\",\n \"rows\": 2748,\n \"fields\": [\n {\n \"column\": \"sentence\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 2731,\n \"samples\": [\n \"Tied to charger for conversations lasting more than 45 minutes.MAJOR PROBLEMS!!\",\n \"It was too predictable, even for a chick flick. \",\n \"The bose noise cancelling is amazing, which is very important for a NYC commuter.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"label\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"source\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"yelp\",\n \"amazon\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 3 + } + ] + }, + { + "cell_type": "code", + "source": [ + "max_features = 2000\n", + "tokenizer = Tokenizer(num_words=max_features, split=' ')\n", + "tokenizer.fit_on_texts(df['sentence'].values)\n", + "X = tokenizer.texts_to_sequences(df['sentence'].values)\n", + "X = pad_sequences(X)\n", + "y = df['label'].values" + ], + "metadata": { + "id": "F_qjw9IVi2Bs" + }, + "execution_count": 4, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.12)\n" + ], + "metadata": { + "id": "q60NFtcri5BJ" + }, + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def create_model():\n", + " model = Sequential()\n", + " model.add(Embedding(max_features, 64, input_length=X.shape[1]))\n", + " model.add(LSTM(16))\n", + " model.add(Dense(1, activation='sigmoid'))\n", + " model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n", + " return model\n", + "\n", + "model = create_model()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "V2GCbbHSi8K_", + "outputId": "522a67d2-288b-471d-aef6-fcde5c882d32" + }, + "execution_count": 6, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.10/dist-packages/keras/src/layers/core/embedding.py:90: UserWarning: Argument `input_length` is deprecated. Just remove it.\n", + " warnings.warn(\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "model.fit(X_train, y_train, epochs=6, batch_size=16, validation_data=(X_test, y_test), callbacks = [EarlyStopping(monitor='val_accuracy', min_delta=0.001, patience=2, verbose=1)])" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PePtblNTi-9l", + "outputId": "5782e609-6492-4709-d160-288eb1ae3c60" + }, + "execution_count": 7, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m77s\u001b[0m 488ms/step - accuracy: 0.5971 - loss: 0.6729 - val_accuracy: 0.7606 - val_loss: 0.5231\n", + "Epoch 2/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m75s\u001b[0m 491ms/step - accuracy: 0.8629 - loss: 0.3859 - val_accuracy: 0.8061 - val_loss: 0.4332\n", + "Epoch 3/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m79s\u001b[0m 470ms/step - accuracy: 0.9335 - loss: 0.2057 - val_accuracy: 0.8121 - val_loss: 0.4459\n", + "Epoch 4/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m72s\u001b[0m 472ms/step - accuracy: 0.9587 - loss: 0.1486 - val_accuracy: 0.8333 - val_loss: 0.4730\n", + "Epoch 5/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m82s\u001b[0m 472ms/step - accuracy: 0.9692 - loss: 0.1114 - val_accuracy: 0.8121 - val_loss: 0.5696\n", + "Epoch 6/6\n", + "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m82s\u001b[0m 472ms/step - accuracy: 0.9772 - loss: 0.0743 - val_accuracy: 0.8333 - val_loss: 0.5894\n", + "Epoch 6: early stopping\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 7 + } + ] + }, + { + "cell_type": "code", + "source": [ + "model.save(\"uci_sentimentanalysis.h5\")\n", + "\n", + "with open('tokenizer.pickle', 'wb') as handle:\n", + " pickle.dump(tokenizer, handle, protocol=pickle.DEFAULT_PROTOCOL)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "VaMeW7CYjBPj", + "outputId": "013e87ee-8f9c-4fb3-bcab-93679a999334" + }, + "execution_count": 8, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n" + ] + } + ] + } + ] +} \ No newline at end of file diff --git a/templates/form.html b/templates/form.html index f1890b6..39ea74e 100644 --- a/templates/form.html +++ b/templates/form.html @@ -1,12 +1,38 @@ + + + + + Sentiment Analysis -
- - -
+
+

SentimentScope Analyzer

+
+
+ +
+ +
+
+ {% if sentiment %} +

Sentiment Analysis Results:

+

Positive: {{ sentiment['pos'] * 100 }}%

+

Neutral: {{ sentiment['neu'] * 100 }}%

+

Negative: {{ sentiment['neg'] * 100 }}%

+

Compound: {{ sentiment['compound'] * 100 }}%

+

Customm Keras model: {{ sentiment['custom model positive'] }}

+ {% endif %} +
+ +
+ From 9ce40b0c6d63a5f607e92a04685d1e7fe78464a2 Mon Sep 17 00:00:00 2001 From: Erick Vivas <88099754+erickvivas415@users.noreply.github.com> Date: Sun, 10 Nov 2024 17:15:24 -0800 Subject: [PATCH 2/4] Update form.html --- templates/form.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/templates/form.html b/templates/form.html index 39ea74e..34ce15b 100644 --- a/templates/form.html +++ b/templates/form.html @@ -28,7 +28,7 @@

Sentiment Analysis Results:

Neutral: {{ sentiment['neu'] * 100 }}%

Negative: {{ sentiment['neg'] * 100 }}%

Compound: {{ sentiment['compound'] * 100 }}%

-

Customm Keras model: {{ sentiment['custom model positive'] }}

+

Custom Keras model: {{ sentiment['custom model positive'] }}

{% endif %} From c9501ab956350139b8e9d65b8e69af25d9b50e26 Mon Sep 17 00:00:00 2001 From: Erick Vivas <88099754+erickvivas415@users.noreply.github.com> Date: Sun, 10 Nov 2024 18:03:05 -0800 Subject: [PATCH 3/4] Update requirements.txt --- requirements.txt | 160 ++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 150 insertions(+), 10 deletions(-) diff --git a/requirements.txt b/requirements.txt index a55b9cf..a47da43 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,11 +1,151 @@ -Flask==2.2.5 -Flask-SQLAlchemy==2.5.1 -numpy==1.23.5 -keras==2.13.1 -sqlalchemy==1.4.20 -psycopg2-binary==2.9.1 -pytest==7.4.2 -scikit-learn==1.2.2 -tensorflow==2.13.0 +absl-py==2.1.0 +anyio==4.6.0 +argon2-cffi==23.1.0 +argon2-cffi-bindings==21.2.0 +arrow==1.3.0 +asttokens==2.4.1 +astunparse==1.6.3 +async-lru==2.0.4 +attrs==24.2.0 +babel==2.16.0 +beautifulsoup4==4.12.3 +bleach==6.1.0 +blinker==1.8.2 +certifi==2024.8.30 +cffi==1.17.1 +charset-normalizer==3.3.2 +click==8.1.7 +colorama==0.4.6 +comm==0.2.2 +contourpy==1.3.0 +cycler==0.12.1 +debugpy==1.8.6 +decorator==5.1.1 +defusedxml==0.7.1 +executing==2.1.0 +fastjsonschema==2.20.0 +filelock==3.13.1 +Flask==3.0.3 +flatbuffers==24.3.25 +fonttools==4.54.1 +fqdn==1.5.1 +fsspec==2024.2.0 +gast==0.6.0 +gitdb==4.0.11 +GitPython==3.1.43 +google-pasta==0.2.0 +grpcio==1.67.1 +h11==0.14.0 +h5py==3.12.1 +httpcore==1.0.5 +httpx==0.27.2 +idna==3.10 +ipykernel==6.29.5 +ipython==8.27.0 +isoduration==20.11.0 +itsdangerous==2.2.0 +jedi==0.19.1 +Jinja2==3.1.4 +joblib==1.4.2 +json5==0.9.25 +jsonpointer==3.0.0 +jsonschema==4.23.0 +jsonschema-specifications==2023.12.1 +jupyter-events==0.10.0 +jupyter-lsp==2.2.5 +jupyter-server-mathjax==0.2.6 +jupyter_client==8.6.3 +jupyter_core==5.7.2 +jupyter_server==2.14.2 +jupyter_server_terminals==0.5.3 +jupyterlab==4.2.5 +jupyterlab_git==0.50.1 +jupyterlab_pygments==0.3.0 +jupyterlab_server==2.27.3 +keras==3.6.0 +kiwisolver==1.4.7 +libclang==18.1.1 +Markdown==3.7 +markdown-it-py==3.0.0 +MarkupSafe==2.1.5 +matplotlib==3.9.2 +matplotlib-inline==0.1.7 +mdurl==0.1.2 +mistune==3.0.2 +ml-dtypes==0.4.1 +mpmath==1.3.0 +namex==0.0.8 +nbclient==0.10.0 +nbconvert==7.16.4 +nbdime==4.0.2 +nbformat==5.10.4 +nest-asyncio==1.6.0 +networkx==3.2.1 +notebook_shim==0.2.4 +numpy==2.0.2 +opt_einsum==3.4.0 +optree==0.13.0 +overrides==7.7.0 +packaging==24.1 +pandas==2.2.3 +pandocfilters==1.5.1 +parso==0.8.4 +pexpect==4.9.0 +pillow==10.4.0 +platformdirs==4.3.6 +plotly==5.24.1 +prometheus_client==0.21.0 +prompt_toolkit==3.0.48 +protobuf==5.28.3 +psutil==6.0.0 +ptyprocess==0.7.0 +pure_eval==0.2.3 +pycparser==2.22 +Pygments==2.18.0 +pyparsing==3.1.4 +python-dateutil==2.9.0.post0 +python-json-logger==2.0.7 +pytz==2024.2 +PyYAML==6.0.2 +pyzmq==26.2.0 +referencing==0.35.1 +requests==2.32.3 +rfc3339-validator==0.1.4 +rfc3986-validator==0.1.1 +rich==13.9.4 +rpds-py==0.20.0 +scikit-learn==1.5.2 +scipy==1.14.1 +seaborn==0.13.2 +Send2Trash==1.8.3 +setuptools==75.1.0 +six==1.16.0 +smmap==5.0.1 +sniffio==1.3.1 +soupsieve==2.6 +stack-data==0.6.3 +sympy==1.12 +tenacity==9.0.0 +tensorboard==2.18.0 +tensorboard-data-server==0.7.2 +tensorflow==2.18.0 +termcolor==2.5.0 +terminado==0.18.1 +threadpoolctl==3.5.0 +tinycss2==1.3.0 +torch==2.4.1+cpu +tornado==6.4.1 +traitlets==5.14.3 +types-python-dateutil==2.9.0.20240906 +typing_extensions==4.9.0 +tzdata==2024.2 +uri-template==1.3.0 +urllib3==2.2.3 vaderSentiment==3.3.2 -gunicorn==19.3.0 \ No newline at end of file +wcwidth==0.2.13 +webcolors==24.8.0 +webencodings==0.5.1 +websocket-client==1.8.0 +Werkzeug==3.1.2 +wheel==0.45.0 +wrapt==1.16.0 From 8bd9eb6dfc2ad2ac8d17768934fce952dd450448 Mon Sep 17 00:00:00 2001 From: Erick Vivas <88099754+erickvivas415@users.noreply.github.com> Date: Sun, 10 Nov 2024 18:23:50 -0800 Subject: [PATCH 4/4] Update requirements.txt --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index a47da43..04b3e6d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -133,7 +133,7 @@ termcolor==2.5.0 terminado==0.18.1 threadpoolctl==3.5.0 tinycss2==1.3.0 -torch==2.4.1+cpu +torch==2.4.1 tornado==6.4.1 traitlets==5.14.3 types-python-dateutil==2.9.0.20240906

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