Update README and Sidebar UI

README.md

@@ -1,45 +1,19 @@
----
-title: FocusFlow
-emoji: 🎯
-colorFrom: purple
-colorTo: indigo
-sdk: docker
-app_file: app.py
-pinned: false
----
-
-#  FocusFlow - AI Study Companion
+# FocusFlow - AI Study Companion
 
 An intelligent study assistant powered by AI that transforms your learning materials into personalized, adaptive study experiences.
 
-##  Features
+[Try FocusFlow on Hugging Face Spaces](https://huggingface.co/spaces/noodledom/focusflow)
 
-- ** Multi-Subject Study Planning**: Upload PDFs and get automated multi-day study plans
-- ** RAG-Powered Q&A**: Ask questions and get answers with source citations
-- ** Adaptive Quizzes**: Context-based quizzes that adapt to your performance
-- ** Progress Tracking**: Track mastery levels and quiz history
-- ** Smart Day Progression**: Automatically unlocks new topics as you complete them
-- ** Source Citations**: Every answer cites the exact source and page number
-- ** Cloud Persistence**: Study plans and progress persist across sessions (cloud demo only)
-- ** Multi-User Support**: Each browser session maintains isolated data
+## Features
 
-##  Live Demo
+- **Multi-Subject Study Planning**: Upload PDFs and get automated multi-day study plans.
+- **RAG-Powered Q&A**: Ask questions and get answers with source citations.
+- **Adaptive Quizzes**: Context-based quizzes that adapt to your performance.
+- **Progress Tracking**: Track mastery levels and quiz history.
+- **Cloud Persistence**: Study plans and progress persist across sessions.
+- **Multi-User Support**: Firebase Authentication enables secure, isolated data per user.
 
-**[Try FocusFlow on Hugging Face Spaces](https://huggingface.co/spaces/SivaRohith69/focusflow)**
-
-> **Note**: The cloud demo uses ephemeral containers. Your data persists in Supabase but each browser tab is treated as a separate user. For true persistent local storage, use the local deployment below.
-
-##  Models Used
-
-### Cloud Demo (HF Spaces)
-- **LLM**: Meta-Llama-3-8B-Instruct (via Hugging Face Inference API)
-- **Embeddings**: sentence-transformers/all-MiniLM-L6-v2
-
-### Local Deployment
-- **LLM**: llama3.2:1b (via Ollama - offline)
-- **Embeddings**: nomic-embed-text (offline)
-
-##  Local Installation
+## Local Installation
 
 ### Prerequisites
 - Python 3.10+
@@ -50,12 +24,12 @@ An intelligent study assistant powered by AI that transforms your learning mater
 
 ```bash
 # Clone the repository
-git clone https://github.com/thesivarohith/hack.git
-cd hack
+git clone https://github.com/suwethadevakiruba3012-wq/Free.git
+cd Free
 
 # Create virtual environment
 python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
+source venv/bin/activate  # On Windows: venv\\Scripts\\activate
 
 # Install dependencies
 pip install -r requirements.txt
@@ -71,100 +45,12 @@ uvicorn backend.main:app --reload &
 streamlit run app.py
 ```
 
-Visit `http://localhost:8501` to use the app!
-
-##  How to Use
-
-1. **Upload PDFs**: Add your study materials in the Sources panel
-2. **Generate Plan**: Ask the Calendar to create a study plan (e.g., "Make a 5-day plan")
-3. **Study**: Click on topics to view lessons and ask questions
-4. **Take Quizzes**: Test your knowledge and unlock new topics
-5. **Track Progress**: View analytics and mastery levels
-
-##  Architecture
+Visit `http://localhost:8501` to use the app.
 
-```
-┌─────────────────────────────────────────┐
-│         Streamlit Frontend              │
-│  (Material Design UI + Calendar)        │
-└──────────────┬──────────────────────────┘
-               │
-       ┌───────▼────────┐
-       │  FastAPI       │
-       │  Backend       │
-       └───────┬────────┘
-               │
-    ┌──────────┼──────────┐
-    │          │          │
-┌───▼────┐ ┌──▼────┐ ┌──▼─────────┐
-│ ChromaDB│ │  LLM  │ │ Supabase  │
-│ (RAG)   │ │       │ │ (Cloud DB)│
-└─────────┘ └───────┘ └───────────┘
-```
-
-##  Tech Stack
+## Tech Stack
 
 - **Frontend**: Streamlit + Material Design
 - **Backend**: FastAPI + LangChain
 - **Vector DB**: ChromaDB
 - **LLM**: Ollama (local) / HuggingFace (cloud)
 - **Database**: Supabase PostgreSQL (cloud) / JSON files (local)
-
-##  Cloud vs Local
-
-| Feature | Local | Cloud (HF Spaces) |
-|---------|-------|-------------------|
-| **Privacy** |  Fully offline |  Data in cloud |
-| **Cost** |  Free |  Free |
-| **Speed** |  Depends on hardware |  Fast |
-| **Persistence** |  Local files |  Supabase DB |
-| **Setup** |  Requires Ollama |  Just click |
-| **Multi-user** |  Single user |  Multi-user |
-
-##  Configuration
-
-### Environment Variables
-
-For cloud deployment, set these in Hugging Face Spaces Settings:
-
-```bash
-# Required for cloud mode
-HUGGINGFACE_API_TOKEN=your_hf_token
-SUPABASE_URL=your_supabase_url
-SUPABASE_KEY=your_supabase_key
-USE_SUPABASE=true
-LLM_PROVIDER=huggingface
-```
-
-For local deployment, no configuration needed!
-
-##  Privacy
-
-- **Local Mode**: All data stays on your machine. No internet required.
-- **Cloud Mode**: Study plans stored in Supabase. PDFs processed in-memory, not stored.
-
-##  License
-
-MIT License - See [LICENSE](LICENSE) for details.
-
-##  Contributing
-
-Contributions welcome! Please feel free to submit a Pull Request.
-
-##  Contact
-
-For questions or feedback, open an issue on [GitHub](https://github.com/thesivarohith/hack/issues).
-
----
-
-**Built with  for better learning experiences**
-
- **Links:**
-- [Live Demo](https://huggingface.co/spaces/SivaRohith69/focusflow)
-
-## 🚀 Latest Updates
-- ✅ Firebase Authentication (Google, GitHub, Email/Password)
-- ✅ OCR support for scanned PDFs
-- ✅ Paste Text feature for cloud mode
-- ✅ Student data stored in Supabase per user
-- ✅ Deployed on HuggingFace Spaces

app.py

@@ -541,39 +541,25 @@ if not st.session_state.get("logged_in") and not st.session_state.get("local_byp
     show_login_page()
     st.stop()
 
-# Show sign out button in sidebar
+# Show profile and sign out in sidebar
 with st.sidebar:
     name = st.session_state.get("user_name", "Student")
     email = st.session_state.get("user_email", "")
     avatar = st.session_state.get("user_avatar", "")
-    if avatar:
-        st.image(avatar, width=50)
-    st.markdown(f"**{name}**")
-    st.caption(email)
-    if st.button("🚪 Sign Out", use_container_width=True):
-        for k in ["uid", "user_email", "user_name", "user_avatar", 
-                  "logged_in", "firebase_token", "local_bypass", 
-                  "user_info", "profile_loaded", "study_plan", 
-                  "topic_scores", "mastery_data", "chat_history"]:
-            st.session_state.pop(k, None)
-        st.rerun()
-    st.divider()
-
-    # ADMIN DATA RESET BUTTON (TEMPORARY FIX)
-    if st.button("⚠️ Admin: Reset All Data", help="Wipes all existing backend data to fix shared state issues", type="primary"):
-        with st.spinner("Wiping all existing data..."):
-            try:
-                res = requests.delete(f"{API_URL}/admin/clear_all_data?secret=focusflow_clear", timeout=10)
-                if res.status_code == 200:
-                    st.success("✅ All legacy data wiped successfully! Please refresh.")
-                    time.sleep(2)
-                    for k in list(st.session_state.keys()):
-                        del st.session_state[k]
-                    st.rerun()
-                else:
-                    st.error(f"Failed: {res.text}")
-            except Exception as e:
-                st.error(f"Error resetting data: {e}")
+    
+    with st.popover("👤 Profile"):
+        if avatar:
+            st.image(avatar, width=50)
+        st.markdown(f"**{name}**")
+        st.caption(email)
+        if st.button("🚪 Sign Out", use_container_width=True):
+            for k in ["uid", "user_email", "user_name", "user_avatar", 
+                      "logged_in", "firebase_token", "local_bypass", 
+                      "user_info", "profile_loaded", "study_plan", 
+                      "topic_scores", "mastery_data", "chat_history"]:
+                st.session_state.pop(k, None)
+            st.rerun()
+    
     st.divider()
 
 # Session State

test_frontend.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+set -e
+export HF_HUB_OFFLINE=0
+export TRANSFORMERS_OFFLINE=1
+export USE_SUPABASE=true
+export LLM_PROVIDER=huggingface
+
+echo "Starting frontend..."
+streamlit run app.py --server.port 7860 --server.address 0.0.0.0 --server.headless true > frontend.log 2>&1 &
+FRONTEND_PID=$!
+sleep 5
+
+if ps -p $FRONTEND_PID > /dev/null; then
+  echo "Frontend is running fine."
+  kill $FRONTEND_PID
+else
+  echo "Frontend CRASHED! Logs:"
+  cat frontend.log
+fi

test_hf_startup.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+set -e
+export HF_HUB_OFFLINE=0
+export TRANSFORMERS_OFFLINE=1
+export USE_SUPABASE=true
+export LLM_PROVIDER=huggingface
+
+echo "Starting backend..."
+python3 -m uvicorn backend.main:app --host 0.0.0.0 --port 8000 > backend.log 2>&1 &
+BACKEND_PID=$!
+sleep 5
+
+if ps -p $BACKEND_PID > /dev/null; then
+  echo "Backend is running fine."
+  kill $BACKEND_PID
+else
+  echo "Backend CRASHED! Logs:"
+  cat backend.log
+fi