Create app.py

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+import requests
+import os
+
+# -------------------------
+# Hugging Face API setup
+# -------------------------
+# Replace with your org/model name
+API_URL = "https://api-inference.huggingface.co/models/DS553-Music-Bot/chord_classifier"
+
+# Expect your HF token as an environment variable (set in HF Space secrets or GitHub Actions)
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+if HF_TOKEN is None:
+    raise ValueError("❌ HF_TOKEN not set. Please add it to your Hugging Face Space or GitHub secrets.")
+
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+# -------------------------
+# Query function
+# -------------------------
+def query_chord(message: str, history: list[tuple[str, str]]):
+    """
+    Send note input to Hugging Face Inference API, return predicted chord.
+    """
+    payload = {"inputs": message}
+    try:
+        response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
+    except Exception as e:
+        return f"❌ Request failed: {str(e)}"
+
+    if response.status_code == 200:
+        try:
+            result = response.json()
+            # Expecting the model repo to return {"label": "Cmaj"} style JSON
+            if isinstance(result, dict) and "label" in result:
+                return f"🎵 Identified chord: **{result['label']}**"
+            else:
+                return f"⚠️ Unexpected API response: {result}"
+        except Exception as e:
+            return f"⚠️ Error parsing API response: {str(e)}"
+    else:
+        return f"❌ Error {response.status_code}: {response.text}"
+
+# -------------------------
+# Gradio ChatInterface
+# -------------------------
+chatbot = gr.ChatInterface(
+    fn=query_chord,
+    title="🎶 Chord Bot (API Version)",
+    description="Enter 2+ notes (e.g., C E G or Db F Ab C). "
+                "This version queries the Hugging Face Inference API "
+                "for chord classification."
+)
+
+if __name__ == "__main__":
+    chatbot.launch()