Create app.py

app.py

@@ -0,0 +1,61 @@
+import gradio as gr
+import requests
+import os
+import pandas as pd
+
+# Hugging Face Inference API endpoint for DeepSeek
+API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-V2"
+headers = {"Authorization": f"Bearer {os.environ['HF_API_TOKEN']}"}
+
+def preprocess_csv(file_path):
+    df = pd.read_csv(file_path)
+    events = []
+    for _, row in df.iterrows():
+        events.append(f"On {row['Date']} at {row['Time']}, state was {row['State']} → {row['Message Text']}")
+    return "\n".join(events)
+
+def analyze_log(file_path, mode):
+    text = preprocess_csv(file_path)
+
+    # Build prompt depending on mode
+    if mode == "Summarize":
+        prompt = "Summarize the following AHU alarm log:\n\n" + text
+    elif mode == "Highlight anomalies":
+        prompt = "Identify unusual or repeated alarms in this AHU log and explain possible causes:\n\n" + text
+    elif mode == "Suggest maintenance":
+        prompt = "Based on this AHU alarm log, suggest maintenance actions:\n\n" + text
+    else:
+        prompt = text
+
+    # Call Hugging Face Inference API
+    response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
+
+    if response.status_code != 200:
+        return f"Error {response.status_code}: {response.text}"
+
+    try:
+        result = response.json()
+    except Exception:
+        return f"Failed to decode JSON. Raw response: {response.text}"
+
+    # Extract generated text
+    if isinstance(result, list) and "generated_text" in result[0]:
+        return result[0]["generated_text"]
+    elif isinstance(result, dict) and "generated_text" in result:
+        return result["generated_text"]
+    else:
+        return str(result)
+
+iface = gr.Interface(
+    fn=analyze_log,
+    inputs=[
+        gr.File(type="filepath", label="Upload Log File"),
+        gr.Dropdown(choices=["Summarize", "Highlight anomalies", "Suggest maintenance"], label="Analysis Mode")
+    ],
+    outputs="text",
+    title="AHU Log Analyzer (DeepSeek API)",
+    description="Upload your log file (CSV) and choose how you want it analyzed using DeepSeek via Hugging Face API."
+)
+
+if __name__ == "__main__":
+    iface.launch()