Create app.py

app.py

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+import requests
+import pandas as pd
+import streamlit as st
+
+# Sanity project details
+project_id = st.secrets["project_id"]  # You can store secrets in Hugging Face Spaces
+dataset = st.secrets["dataset"]        # Store your dataset name as a secret
+token = st.secrets["api_token"]        # Store your API token as a secret
+
+# Sanity API URL for querying tasks
+url = f'https://{project_id}.api.sanity.io/v1/data/query/{dataset}'
+
+# GROQ query to get tasks
+groq_query = """
+*[_type == "task"]{
+  _id,
+  title,
+  description,
+  status,
+  dueDate
+}
+"""
+
+# Prepare headers with authorization token
+headers = {
+    'Authorization': f'Bearer {token}'
+}
+
+# Streamlit UI elements
+st.title('Sanity Task Dashboard')
+st.write('This is a task dashboard fetching data from Sanity CMS.')
+
+# Fetch data using the GROQ query
+response = requests.get(url, headers=headers, params={'query': groq_query})
+
+# Check if request was successful
+if response.status_code == 200:
+    tasks = response.json()['result']  # Get tasks from the response
+    tasks_df = pd.DataFrame(tasks)  # Create a DataFrame from the tasks
+    tasks_df['dueDate'] = pd.to_datetime(tasks_df['dueDate'])  # Convert 'dueDate' to datetime
+    
+    st.dataframe(tasks_df)  # Display the tasks in a table
+else:
+    st.error(f"Error fetching tasks: {response.status_code} - {response.text}")