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README.md

@@ -1,5 +1,5 @@
 ---
-title: Course Assistant - CCNY Data Science
+title: CCNY Data Science Assistant
 emoji: 🤖
 colorFrom: blue
 colorTo: red
@@ -8,12 +8,12 @@ sdk_version: 5.38.0
 app_file: app.py
 pinned: false
 license: mit
-short_description: "assistant for prof. muhlbauer's data science course"
+short_description: "Assistant for Foundations of Data Science at CCNY"
 ---
 
-# Course Assistant - CCNY Data Science
+# CCNY Data Science Assistant
 
-assistant for prof. muhlbauer's data science course
+Assistant for Foundations of Data Science at CCNY
 
 ## Quick Deploy to HuggingFace Spaces
 
@@ -40,22 +40,39 @@ assistant for prof. muhlbauer's data science course
 5. Value: Your OpenRouter API key
 6. Click "Add"
 
+### Step 4: Configure Access Control
+Your Space is configured with access code protection. Students will need to enter the access code to use the chatbot.
+
+1. Go to Settings (gear icon) 
+2. Click "Variables and secrets"
+3. Click "New secret"
+4. Name: `SPACE_ACCESS_CODE`
+5. Value: `TLC`
+6. Click "Add"
+
+**Important**: The access code is now stored securely as an environment variable and is not visible in your app code.
+
+To disable access protection:
+1. Go to Settings → Variables and secrets
+2. Delete the `SPACE_ACCESS_CODE` secret
+3. The Space will rebuild automatically with no access protection
+
 
 
-### Step 4: Get Your API Key
+### Step 5: Get Your API Key
 1. Go to https://openrouter.ai/keys
 2. Sign up/login if needed
 3. Click "Create Key"
 4. Copy the key (starts with `sk-or-`)
 
-### Step 5: Test Your Space
+### Step 6: Test Your Space
 - Go back to "App" tab
 - Your Space should be running!
 - Try the example prompts or ask a question
 
 ## Configuration
 
-- **Model**: google/gemini-2.0-flash-001
+- **Model**: openai/gpt-4o-mini-search-preview
 - **Temperature**: 0.7
 - **Max Tokens**: 750
 - **API Key Variable**: OPENROUTER_API_KEY

app.py

@@ -10,8 +10,8 @@ import urllib.parse
 
 
 # Configuration
-SPACE_NAME = "Course Assistant - CCNY Data Science"
-SPACE_DESCRIPTION = "assistant for prof. muhlbauer's data science course"
+SPACE_NAME = "CCNY Data Science Assistant"
+SPACE_DESCRIPTION = "Assistant for Foundations of Data Science at CCNY"
 SYSTEM_PROMPT = """You are a supportive course assistant for Professor Zach Muhlbauer's Foundations of Data Science course (CSC 10800 R) at City College of New York.
 
 Core Responsibilities
@@ -52,8 +52,8 @@ Engagement Style:
 * Celebrate student progress and effort
 
 Remember: Your goal is to support student learning and success while maintaining the pedagogical integrity of the course. You are a learning facilitator, not an answer provider."""
-MODEL = "google/gemini-2.0-flash-001"
-GROUNDING_URLS = ["https://zmuhls.github.io/ccny-data-science/schedule/", "https://zmuhls.github.io/ccny-data-science/syllabus/", "https://zmuhls.github.io/ccny-data-science/activities/", "https://zmuhls.github.io/ccny-data-science/portfolio/"]
+MODEL = "openai/gpt-4o-mini-search-preview"
+GROUNDING_URLS = ["https://zmuhls.github.io/ccny-data-science/schedule/", "https://zmuhls.github.io/ccny-data-science/schedule/", "https://zmuhls.github.io/ccny-data-science/portfolio/", "https://zmuhls.github.io/ccny-data-science/activities/"]
 # Get access code from environment variable for security
 # If SPACE_ACCESS_CODE is not set, no access control is applied
 ACCESS_CODE = os.environ.get("SPACE_ACCESS_CODE")
@@ -551,7 +551,7 @@ with gr.Blocks(title=SPACE_NAME) as demo:
             fn=store_and_generate_response,  # Use wrapper function to store history
             title="",  # Title already shown above
             description="",  # Description already shown above
-            examples=['When is the social coding portfolio due?'],
+            examples=['When is the social coding portfolio due?', "What's my grade in the course?"],
             type="messages"  # Use modern message format for better compatibility
         )
         

config.json

@@ -1,12 +1,12 @@
 {
-  "name": "Course Assistant - CCNY Data Science",
-  "description": "assistant for prof. muhlbauer's data science course",
+  "name": "CCNY Data Science Assistant",
+  "description": "Assistant for Foundations of Data Science at CCNY",
   "system_prompt": "You are a supportive course assistant for Professor Zach Muhlbauer's Foundations of Data Science course (CSC 10800 R) at City College of New York.\n\nCore Responsibilities\n* Course Navigation: Help students locate and understand syllabus information, assignment details, schedules, readings, and course materials\n* Learning Facilitation: Guide students toward understanding concepts through Socratic questioning and scaffolding rather than providing direct answers\n* Administrative Support: Provide accurate information about deadlines, exam dates, office hours, and course policies\n\nResponse Guidelines\n* Precision First: Be exact with all dates, times, deadlines, and scheduling information\n* Warm Tone: Use encouraging, supportive language that builds student confidence\n* Pedagogical Approach: Never provide direct answers to assignments or assessments; instead, ask guiding questions that help students discover solutions independently\n* Scope Boundaries: Only address questions related to this specific course (CSC 10800 R) - syllabus, schedule, assignments, readings, and general data science learning support\n* Specific Protocols: For questions about grades,  redirect students to contact Professor Muhlbauer at the email provided in the course materials for all related inquiries: [email protected]\n\nFor Scheduling/Deadlines:\n* Always cross-reference the most current course schedule\n* Provide specific dates and times\n* Remind students of upcoming deadlines proactively when relevant\n* NB: If {{today}} is after the last date of the course, then do NOT make up new dates based on Tue/Thu schedule of the class\n\nFor Conceptual Questions:\n* Use Socratic method to guide discovery\n* Provide analogies or real-world applications to clarify abstract concepts\n* Reference specific course materials where students can find more information\n* Encourage active engagement with the material\n\nUncertainty Protocol:\nWhen uncertain about any information:\n* Explicitly state your uncertainty\n* Direct students to verify information through official course materials\n* Suggest contacting Professor Muhlbauer for clarification\n* Provide general guidance on where to find authoritative information\n\nEngagement Style:\n* Begin responses with acknowledgment of the student's question\n* Use warm, encouraging language\n* Ask follow-up questions to better understand student needs\n* Celebrate student progress and effort\n\nRemember: Your goal is to support student learning and success while maintaining the pedagogical integrity of the course. You are a learning facilitator, not an answer provider.",
-  "model": "google/gemini-2.0-flash-001",
+  "model": "openai/gpt-4o-mini-search-preview",
   "api_key_var": "OPENROUTER_API_KEY",
   "temperature": 0.7,
   "max_tokens": 750,
-  "examples": "['When is the social coding portfolio due?']",
-  "grounding_urls": "[\"https://zmuhls.github.io/ccny-data-science/schedule/\", \"https://zmuhls.github.io/ccny-data-science/syllabus/\", \"https://zmuhls.github.io/ccny-data-science/activities/\", \"https://zmuhls.github.io/ccny-data-science/portfolio/\"]",
+  "examples": "['When is the social coding portfolio due?', \"What's my grade in the course?\"]",
+  "grounding_urls": "[\"https://zmuhls.github.io/ccny-data-science/schedule/\", \"https://zmuhls.github.io/ccny-data-science/schedule/\", \"https://zmuhls.github.io/ccny-data-science/portfolio/\", \"https://zmuhls.github.io/ccny-data-science/activities/\"]",
   "enable_dynamic_urls": true
 }