new model

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+xgboost_model.json filter=lfs diff=lfs merge=lfs -text
+xgboost_model filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,61 @@
+from io import StringIO
+import gradio as gr
+import pandas as pd
+import xgboost as xgb
+  # Add this import
+
+def preprocess_data(df):
+
+
+    # Assuming the model expects the input without the first 50 columns
+    processed_data = df.drop(df.columns[0:50], axis=1)
+
+    # Assuming you want the last column as the target.
+    X = processed_data.drop(processed_data.columns[-1], axis=1).values
+    y = processed_data[processed_data.columns[-1]].values
+
+
+    return (X, y)
+
+
+
+def process_csv_text(temp_file):
+    if isinstance(temp_file, str):
+      df = pd.read_csv(StringIO(temp_file))
+    else:
+      df = pd.read_csv(temp_file.name)
+    print(df)
+    return df
+
+
+def predict_interface(input_csv):
+    print(type(input_csv))
+    loaded_model = xgb.XGBRegressor()
+    loaded_model.load_model('xgboost_model.json')
+
+    # Check if the file is non-empty and has recognizable data
+    try:
+        # Load the csv content into a DataFrame
+        data = process_csv_text(input_csv)
+        if data is None:
+            return "Uploaded file is empty or not recognized as a valid CSV."
+
+        # Continue with the rest of the processing
+        processed_data = preprocess_data(data)
+        predictions = loaded_model.predict(processed_data[0])  # Access the X part
+        data['Predictions'] = predictions
+        data['Actual'] = processed_data[1]  # Access the y part
+        return data.to_html()
+    except Exception as e:
+        return str(e)
+
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=predict_interface,
+    inputs="file",
+    outputs="html",
+    live=True
+)
+
+iface.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -0,0 +1,5 @@
+xgboost==1.7.6
+gradio 
+scikit-learn==1.2.2
+numpy
+

xgboost_model.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d57f4ca019ba072956f422926ebc155ed8af4ce0bb954934d7e04a0f1458df52
+size 15378107