streamlit app

.gitignore

@@ -0,0 +1 @@
+run.bat

Dockerfile

@@ -0,0 +1,18 @@
+FROM continuumio/miniconda3
+
+WORKDIR /home/app
+
+RUN apt-get update
+RUN apt-get install nano unzip
+RUN apt install curl -y
+
+RUN curl -fsSL https://get.deta.dev/cli.sh | sh
+
+COPY requirements.txt /dependencies/requirements.txt
+RUN pip install --no-cache-dir -r /dependencies/requirements.txt
+
+
+COPY . /home/app
+
+# Use shell form of CMD to allow environment variable substitution
+CMD streamlit run app.py --server.port=${PORT} --server.address=0.0.0.0

app.py

@@ -0,0 +1,55 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px 
+import plotly.graph_objects as go
+import numpy as np
+import requests
+
+### Config
+st.set_page_config(
+    page_title="Hate Speech Recognition",
+    page_icon="⚠️",
+    layout="wide"
+)
+
+
+def hate_speech_detection(text):
+    url = "https://llepogam-hate-speech-detection-api.hf.space/predict"
+    headers = {
+        "accept": "application/json",
+        "Content-Type": "application/json"
+    }
+
+    # Define the payload
+    Text_to_predict = {
+        "Text": text
+    }
+
+    # Make the POST request
+    response = requests.post(url, headers=headers, json=Text_to_predict)
+
+    # Process the response
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return f"Failed to get a response. Status code: {response.status_code}, Response: {response.text}"
+
+
+
+
+st.title("Hate Speech Detection")
+user_input = st.text_area("Enter a Tweet:")
+
+if user_input:
+    prediction = hate_speech_detection(user_input)
+    st.write(f"Prediction: {prediction['prediction']}")
+    st.write(f"Probability: {prediction['probability']}")
+ 
+
+
+### Footer 
+empty_space, footer = st.columns([1, 2])
+
+with empty_space:
+    st.write("")
+

requirements.txt

@@ -0,0 +1,10 @@
+ boto3
+ pandas
+ gunicorn
+ streamlit
+ scikit-learn
+ matplotlib
+ seaborn
+ plotly
+ huggingface_hub
+ numpy