Create app.py

app.py

@@ -0,0 +1,88 @@
+# app.py
+
+import streamlit as st
+import pandas as pd
+import requests
+from simple_salesforce import Salesforce
+
+# ----------------------
+# CONFIG: Salesforce + Hugging Face
+# ----------------------
+SF_USERNAME = "[email protected]"
+SF_PASSWORD = "Vedavathi@04"
+SF_SECURITY_TOKEN = "jqe4His8AcuFJucZz5NBHfGU"
+SF_DOMAIN = "login"  # or "test" for sandbox
+
+HF_API_URL = "https://api-inference.huggingface.co/models/your-username/your-model"
+HF_API_TOKEN = "hf_your_token"
+
+# ----------------------
+# Connect to Salesforce
+# ----------------------
+@st.cache_resource
+def connect_salesforce():
+    sf = Salesforce(username=SF_USERNAME, password=SF_PASSWORD, security_token=SF_SECURITY_TOKEN, domain=SF_DOMAIN)
+    return sf
+
+# ----------------------
+# Get Pole Data from Salesforce
+# ----------------------
+def fetch_pole_data(sf):
+    query = """
+    SELECT Name, Solar_Gen__c, Wind_Gen__c, Tilt__c, Vibration__c, Camera_Status__c 
+    FROM Smart_Pole__c
+    LIMIT 50
+    """
+    records = sf.query_all(query)['records']
+    df = pd.DataFrame(records).drop(columns=['attributes'])
+    return df
+
+# ----------------------
+# Send Data to Hugging Face Model
+# ----------------------
+def get_hf_predictions(df):
+    headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
+    preds = []
+
+    for _, row in df.iterrows():
+        input_data = {
+            "solar": row["Solar_Gen__c"],
+            "wind": row["Wind_Gen__c"],
+            "tilt": row["Tilt__c"],
+            "vibration": row["Vibration__c"],
+            "camera": row["Camera_Status__c"]
+        }
+        response = requests.post(HF_API_URL, headers=headers, json={"inputs": input_data})
+        if response.status_code == 200:
+            result = response.json()
+            preds.append(result[0]['label'] if isinstance(result, list) else result.get("label", "Unknown"))
+        else:
+            preds.append("Error")
+
+    df["Alert_Prediction"] = preds
+    return df
+
+# ----------------------
+# Streamlit App
+# ----------------------
+def main():
+    st.title("🔌 Salesforce ↔ Hugging Face Smart Pole Integration")
+
+    sf = connect_salesforce()
+    df = fetch_pole_data(sf)
+
+    if not df.empty:
+        st.subheader("📥 Raw Pole Data from Salesforce")
+        st.dataframe(df)
+
+        st.subheader("🤖 Running Hugging Face AI Predictions...")
+        df = get_hf_predictions(df)
+        
+        st.success("✅ Predictions Complete")
+        st.subheader("📊 Results with Predictions")
+        st.dataframe(df)
+    else:
+        st.warning("No data fetched from Salesforce.")
+
+if __name__ == "__main__":
+    main()