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._decision_tree_regressor.joblib

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+size 4096

.github/workflows/update_space.yml

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+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/FastingApp.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="3">
+            <item index="0" class="java.lang.String" itemvalue="matplotlib" />
+            <item index="1" class="java.lang.String" itemvalue="numpy" />
+            <item index="2" class="java.lang.String" itemvalue="torch" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11 (FastingApp)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (FastingApp)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/FastingApp.iml" filepath="$PROJECT_DIR$/.idea/FastingApp.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/FastingApp" vcs="Git" />
+  </component>
+</project>

.idea/workspace.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="AutoImportSettings">
+    <option name="autoReloadType" value="SELECTIVE" />
+  </component>
+  <component name="ChangeListManager">
+    <list default="true" id="110c2627-9032-47cf-a1c1-bc62c4ddc737" name="Changes" comment="" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileTemplateManagerImpl">
+    <option name="RECENT_TEMPLATES">
+      <list>
+        <option value="Python Script" />
+      </list>
+    </option>
+  </component>
+  <component name="Git.Settings">
+    <option name="RECENT_GIT_ROOT_PATH" value="$PROJECT_DIR$/FastingApp" />
+  </component>
+  <component name="ProjectColorInfo"><![CDATA[{
+  "associatedIndex": 2
+}]]></component>
+  <component name="ProjectId" id="2Y8jT8CPLJci5KoBpz37K4gLAqf" />
+  <component name="ProjectViewState">
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent"><![CDATA[{
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+    "RunOnceActivity.ShowReadmeOnStart": "true",
+    "last_opened_file_path": "/Volumes/Z Slim 1/FastingApp",
+    "settings.editor.selected.configurable": "com.jetbrains.python.configuration.PyActiveSdkModuleConfigurable"
+  }
+}]]></component>
+  <component name="RecentsManager">
+    <key name="CopyFile.RECENT_KEYS">
+      <recent name="$PROJECT_DIR$" />
+    </key>
+    <key name="MoveFile.RECENT_KEYS">
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+  <component name="TaskManager">
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+      <created>1699914106482</created>
+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
+      <updated>1699914106482</updated>
+    </task>
+    <servers />
+  </component>
+</project>

FastingApp/.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
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FastingApp/README.md

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+---
+title: FastingApp
+emoji: 🐨
+colorFrom: pink
+colorTo: gray
+sdk: gradio
+sdk_version: 4.2.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

README.md

@@ -1,13 +1,6 @@
 ---
 title: FastingApp
-emoji: 🐨
-colorFrom: pink
-colorTo: gray
-sdk: gradio
-sdk_version: 4.2.0
 app_file: app.py
-pinned: false
-license: mit
+sdk: gradio
+sdk_version: 3.50.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import pandas as pd
+import joblib
+import torch
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+from gpt4all import GPT4All
+
+# Load the trained model
+decision_tree_regressor = joblib.load('./decision_tree_regressor.joblib')
+
+# Initialize GPT4All model
+model_name = "mistral-7b-openorca.Q4_0.gguf"  # Replace with your preferred model
+model = GPT4All(model_name)
+
+
+def collect_data(fasting_duration, meal_timing, body_weight, age, gender, height):
+    # Prepare the data for prediction
+    data = {
+        "Fasting Duration (hours)": [fasting_duration],
+        "Meal Timing (hour:minute)": [meal_timing],
+        "Body Weight (kg)": [body_weight],
+        "Age (years)": [age],
+        "Height (cm)": [height]
+    }
+    df = pd.DataFrame(data)
+
+    # Convert 'Meal Timing' from a time string to a continuous variable
+    df['Meal Timing (hour:minute)'] = df['Meal Timing (hour:minute)'].apply(
+        lambda x: int(x.split(':')[0]) + int(x.split(':')[1]) / 60
+    )
+
+    # Add gender columns
+    df['Gender_Male'] = int(gender == 'Male')  # Convert boolean to int directly
+    df['Gender_Other'] = int(gender == 'Other')  # Convert boolean to int directly
+
+    return df
+
+
+def generate_recommendations(health_score, fasting_duration, meal_timing, body_weight, age, gender, height):
+    # Generate recommendations based on the health score
+    message = ""
+    if health_score > 80:
+        message = "You're doing great! Keep up the good work with your fasting and diet."
+    elif health_score > 60:
+        message = "Your health score is good, but there's room for improvement."
+    else:
+        message = "Consider making lifestyle changes to improve your health score."
+
+    prompt = f"{message}\nHealth Score: {health_score}\nFasting Duration: {fasting_duration} hours\nMeal Timing: {meal_timing}\nBody Weight: {body_weight} kg\nAge: {age}\nGender: {gender}\nHeight: {height} cm\n\nWhat lifestyle changes would you recommend for improving metabolic health based on this information? Suggest a weekly exercise routine for the next 7 days, taking into account the user´s parameters. Suggest weekly menus with day and time, considering the mandatory {fasting_duration}, for the next 7 days.\nAdd a shopping list."
+
+    # Use the generator to generate text
+    recommendations = model.generate(prompt, max_tokens=2100, temp=0.7, top_p=0.95,
+                                     repeat_penalty=1.0, repeat_last_n=64, n_batch=16, streaming=False)
+    return recommendations.strip()
+
+
+def predict_metabolic_health(fasting_duration, meal_timing, body_weight, age, gender, height):
+    try:
+        # Check if meal_timing is an empty string or has an invalid format
+        if not meal_timing or ':' not in meal_timing:
+            raise ValueError("Meal timing is required. Please enter a valid time (e.g., '12:30').")
+
+        # Collect the data
+        df = collect_data(fasting_duration, meal_timing, body_weight, age, gender, height)
+
+        # Make the prediction
+        health_score = decision_tree_regressor.predict(df)[0]
+
+        # Generate recommendations using the generate_recommendations function
+        recommendations = generate_recommendations(health_score, fasting_duration, meal_timing, body_weight, age,
+                                                   gender, height)
+
+        # Return the health score and recommendations
+        return health_score, recommendations
+
+    except ValueError as e:
+        # If there is a ValueError, return None for health score and the error message
+        return None, str(e)
+    except IndexError:
+        # If there is an IndexError, likely due to an empty response from the model, handle it
+        return None, "No recommendations could be generated at this time."
+
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=predict_metabolic_health,
+    inputs=[
+        gr.Number(label="Fasting Duration (hours)"),
+        gr.Textbox(label="Meal Timing (HH:MM)", placeholder="Enter time as HH:MM"),
+        gr.Number(label="Body Weight (kg)"),
+        gr.Slider(minimum=18, maximum=100, label="Age (years)"),
+        gr.Radio(choices=["Male", "Female", "Other"], label="Gender"),
+        gr.Number(label="Height (cm)")
+    ],
+    outputs=[
+        gr.Number(label="Predicted Metabolic Health Score"),
+        gr.Textbox(label="Recommendation", max_lines=1600, autoscroll='true')
+    ],
+    live=False,  # Set to False to not make automatic predictions
+    title="Intermittent Fasting Metabolic Health Prediction",
+    description="Enter your fasting duration, meal timings, and physical attributes to predict your metabolic health score and get recommendations."
+)
+
+# Run the interface
+interface.launch()

decision_tree_regressor.joblib

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+size 116737