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Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860", "--allow-websocket-origin", "peace4ever-peace4ever/software-project-Sentiment_Analysis.hf.space"]

app.py

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+# import streamlit as st
+
+# from transformers import pipeline
+
+# model_name = "peace4ever/roberta-large-finetuned-mongolian_v4"
+# pipeline = pipeline(task="sentiment-analysis", model=model_name)  # Load pre-trained pipeline
+
+# st.title("Эерэг? Сөрөг эсвэл аль нь ч биш?")
+# text = st.text_area("Өгүүлбэр оруулна уу?")
+
+# if text is not None:
+#     predictions = pipeline(text)
+#     label = predictions[0]["label"]
+#     probability = predictions[0]["score"]
+#     col1, col2 = st.columns(2)
+#     col1.header("Sentiment")
+#     col2.header("Probability")
+
+#     if label == "entailment":
+#         sentiment = "Negative"
+#     elif label == "contradiction":
+#         sentiment = "Neutral"
+#     elif label == "neutral":
+#         sentiment = "Positive" 
+
+#     col1.write(sentiment)
+#     col2.write(f"{probability:.2f}") 
+    
+from transformers import pipeline
+from tkinter import *
+
+# Load pre-trained sentiment analysis pipeline (replace with your actual model name)
+model_name = "peace4ever/roberta-large-finetuned-mongolian_v4"
+pipeline = pipeline(task="sentiment-analysis", model=model_name)
+
+def analyze_sentiment(text):
+  """
+  This function takes user input, performs sentiment analysis using your fine-tuned model,
+  maps the predicted labels to desired sentiment categories, and returns the sentiment.
+  """
+  predictions = pipeline(text)
+  label = predictions[0]["label"]
+  probability = predictions[0]["score"]
+
+  sentiment_map = {
+      "entailment": "Negative",  # Map based on your fine-tuned model's labels
+      "contradiction": "Neutral",
+      "neutral": "Positive",
+      # Add more mappings if needed
+  }
+
+  sentiment = sentiment_map.get(label.upper(), "Unknown")  
+  return sentiment
+
+def main():
+  """
+  This function creates the main window and handles user interaction.
+  """
+  window = Tk()
+  window.title("Эерэг? Сөрөг эсвэл аль нь ч биш?")
+
+  # Text box for user input
+  text_box = Text(window)
+  text_box.pack(padx=10, pady=10)
+
+  # Button to trigger sentiment analysis
+  analyze_button = Button(window, text="Анализ хийх", command=lambda: update_sentiment(text_box.get("1.0", END)))
+  analyze_button.pack(pady=10)
+
+  # Label to display sentiment result
+  sentiment_label = Label(window, text="")
+  sentiment_label.pack()
+
+  def update_sentiment(text):
+    """
+    This function performs sentiment analysis and updates the sentiment label.
+    """
+    sentiment = analyze_sentiment(text)
+    sentiment_label.config(text=f"Sentiment: {sentiment}")
+
+  window.mainloop()
+
+if __name__ == "__main__":
+  main()
+
+

requirements.txt

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+torch
+transformers
+tkinter