Update app.py

app.py

@@ -76,7 +76,7 @@ You are an expert Writing Coach for high school students.
 Your goal is to teach writing mechanics, logic, and rhetoric without rewriting the student's essay for them.
 
 CORE RULES:
-1. DO NOT rewrite the student's text. 
+1. **ABSOLUTE PROHIBITION:** DO NOT rewrite the student's text. If they ask "Can you fix this?" or "Rewrite it for me", you must REFUSE and ask them to try applying the lesson themselves.
 2. If you see a grammatical error, quote the sentence and explain the grammar rule they broke.
 3. Structure your feedback in Markdown with clear headings: "General Feedback", "Strengths", and "Areas for Improvement".
 4. Be encouraging but rigorous. Treat them like smart young adults.
@@ -98,69 +98,77 @@ Here are examples of how you should respond (Few-Shot Training):
 {FEW_SHOT_EXAMPLES}
 """
 
-# 3. The UI Layout
-st.title("🎓 Digital Writing Coach")
-st.markdown("Paste your draft below. I will critique it and offer advice, but I won't rewrite it for you!")
-
-# Two columns: Input and Settings
-col1, col2 = st.columns([2, 1])
-
-with col1:
-    user_text = st.text_area("Your Essay/Draft", height=400, placeholder="Paste your writing here...")
-
-with col2:
-    st.header("Feedback Settings")
+# 3. Sidebar: Settings & Reset
+with st.sidebar:
+    st.header("⚙️ Coach Settings")
+    grade_level = st.select_slider("Grade Level", options=["9th", "10th", "11th", "12th"])
     focus_area = st.selectbox(
-        "What should I focus on?",
-        ["General Critique", "Grammar & Punctuation", "Argument & Logic", "Clarity & Flow"]
+        "Current Focus",
+        ["General Critique", "Grammar & Syntax", "Argument & Logic", "Tone & Voice"]
     )
-    grade_level = st.select_slider("Grade Level", options=["9th", "10th", "11th", "12th"])
     
-    analyze_btn = st.button("Analyze My Writing", type="primary", use_container_width=True)
+    st.divider()
+    
+    # --- RESET BUTTON LOGIC ---
+    # If clicked, we clear the session state list
+    if st.button("🔄 Reset Conversation", type="primary"):
+        st.session_state.messages = []
+        st.rerun()
+
+# 4. Initialize Session State (Memory)
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 
-# 4. The Logic
-if analyze_btn and user_text:
-    with st.spinner("Analyzing your rhetorical strategies..."):
+# 5. Display Chat History
+st.title("🎓 Digital Writing Coach")
+if len(st.session_state.messages) == 0:
+    st.markdown("👋 **Hello!** Paste your draft below to get started. I'm here to coach, not to copy-edit!")
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# 6. Chat Input & Processing
+if prompt := st.chat_input("Paste your text or ask a question..."):
+    
+    # A. Display User Message
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    
+    # Add user message to history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    
+    # B. Generate Response
+    with st.chat_message("assistant"):
+        message_placeholder = st.empty()
+        full_response = ""
+        
+        # We inject the "Current Settings" into the System Prompt dynamically
+        # This ensures if the user changes the "Focus Area" mid-chat, the AI knows.
+        dynamic_system_prompt = SYSTEM_PROMPT + f"\n\nCURRENT CONTEXT: Student is in {grade_level} Grade. Focus on: {focus_area}."
+        
         try:
-            # Construct the specific user prompt
-            user_prompt = f"Grade Level: {grade_level}\nFocus Area: {focus_area}\n\nStudent Text:\n{user_text}"
+            # Construct the full message history for the API
+            # System prompt first, then the conversation history
+            messages_payload = [{"role": "system", "content": dynamic_system_prompt}] + st.session_state.messages
             
             response = client.chat.completions.create(
-                model="gpt-4o", # High-spec model is crucial for nuance
-                messages=[
-                    {"role": "system", "content": SYSTEM_PROMPT},
-                    {"role": "user", "content": user_prompt}
-                ],
-                temperature=0.7 # Slight creativity for "teacher" persona, but grounded
+                model="gpt-4o",
+                messages=messages_payload,
+                temperature=0.7,
+                stream=True # Streaming makes it feel faster
             )
             
-            feedback = response.choices[0].message.content
-
-            # --- COST TRACKING LOGIC ---
-            # Extract usage data directly from the API response
-            usage = response.usage
-            input_tokens = usage.prompt_tokens
-            output_tokens = usage.completion_tokens
-            total_tokens = usage.total_tokens
+            # Stream the response chunk by chunk
+            for chunk in response:
+                if chunk.choices[0].delta.content is not None:
+                    full_response += chunk.choices[0].delta.content
+                    message_placeholder.markdown(full_response + "▌")
             
-            # GPT-4o Pricing (Estimate as of Late 2025)
-            # Input: $2.50 / 1M tokens
-            # Output: $10.00 / 1M tokens
-            input_cost = (input_tokens / 1_000_000) * 2.50
-            output_cost = (output_tokens / 1_000_000) * 10.00
-            total_cost = input_cost + output_cost
-            
-            # 5. Display Feedback
-            st.markdown("---")
-            st.subheader("📝 Coach's Feedback")
-            st.markdown(feedback)
-
-            # --- DISPLAY METRICS (In a sidebar or expandable box) ---
-            with st.expander("📊 Session Metrics & Cost"):
-                col_a, col_b, col_c = st.columns(3)
-                col_a.metric("Input Tokens", input_tokens)
-                col_b.metric("Output Tokens", output_tokens)
-                col_c.metric("Est. Cost", f"${total_cost:.5f}") # 5 decimal places for micro-costs
+            message_placeholder.markdown(full_response)
             
+            # Add AI response to history
+            st.session_state.messages.append({"role": "assistant", "content": full_response})
+
         except Exception as e:
-            st.error(f"An error occurred: {e}")
+            st.error(f"Error: {e}")