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README.md

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----
-title: NewVersion
-emoji: 👁
-colorFrom: purple
-colorTo: red
-sdk: gradio
-sdk_version: 6.14.0
-python_version: '3.13'
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+\---
+
+title: Student Support-Seeking Language Demo
+
+emoji: 🎓
+
+colorFrom: blue
+
+colorTo: purple
+
+sdk: gradio
+
+app\_file: app.py
+
+pinned: false
+
+\---
+
+
+
+\# Student Support-Seeking Language Demo
+
+
+
+This Space demonstrates a text-classification workflow deployed on Hugging Face Spaces.
+
+
+
+\## Important
+
+This is an educational demo only. It is not a clinical, disciplinary, or surveillance tool.
+
+It should not be used to diagnose mental health conditions or make high-stakes decisions.
+

app.py

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+import gradio as gr
+from transformers import pipeline
+
+MODEL_NAME = "cardiffnlp/twitter-roberta-base-emotion-multilabel-latest"
+
+classifier = pipeline("text-classification", model=MODEL_NAME, top_k=None)
+
+DISCLAIMER = """
+This demo detects patterns in self-provided text that may indicate support-seeking or distress-related language.
+It is for educational demonstration only and is NOT a diagnostic, disciplinary, or clinical tool.
+If someone may be in immediate danger, contact emergency services or a qualified crisis resource.
+"""
+
+DISTRESS_KEYWORDS = {
+    "sadness", "fear", "anger", "disgust", "negative"
+}
+
+def analyze_text(text):
+    if not text or not text.strip():
+        return "Please enter some text.", {}
+
+    results = classifier(text[:512])[0]
+
+    label_scores = {item["label"]: float(item["score"]) for item in results}
+
+    distress_score = 0.0
+    for label, score in label_scores.items():
+        if label.lower() in DISTRESS_KEYWORDS:
+            distress_score += score
+
+    if distress_score >= 0.60:
+        assessment = "Potential support-seeking / distress-related language detected"
+    elif distress_score >= 0.30:
+        assessment = "Some distress-related language detected"
+    else:
+        assessment = "No strong distress-related language detected"
+
+    return assessment, label_scores
+
+demo = gr.Interface(
+    fn=analyze_text,
+    inputs=gr.Textbox(
+        lines=6,
+        label="Student text input",
+        placeholder="Enter a message, reflection, or post for analysis..."
+    ),
+    outputs=[
+        gr.Textbox(label="Assessment"),
+        gr.Label(label="Model scores")
+    ],
+    title="Student Support-Seeking Language Demo",
+    description=DISCLAIMER,
+    examples=[
+        ["I feel overwhelmed and I do not know who to talk to anymore."],
+        ["I am stressed about finals but I think I can manage."],
+        ["I had a good day and finished my homework."],
+    ],
+    flagging_mode="never"
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+transformers
+torch