version 6 | DB

src/architecture.md

@@ -14,10 +14,12 @@ Daease is an AI-powered medical consultation application that enables users to d
 ├── utils.py                # Utility functions for text processing
 ├── chat_display.py         # Chat UI components and rendering
 ├── session_state.py        # Session state management
+├── database.py             # Database integration with Supabase
 ├── styles.py               # Custom CSS styling
 ├── sendgrid_service.py     # Email service for sending reports
 ├── __init__.py             # Package initialization
-└── requirements.txt        # Project dependencies
+├── requirements.txt        # Project dependencies
+└── README_DB_SETUP.md      # Database setup instructions
 ```
 
 ## Core Components
@@ -30,15 +32,19 @@ The entry point for the Streamlit web application.
 - Streamlit UI setup with dark theme
 - Chat interface for medical consultations
 - Toggle for enabling/disabling medical database search (RAG)
-- Report generation functionality
+- Report generation functionality with priority management
+- Conversation lock mechanism to ensure uninterrupted user experience
 - Session state management
+- "End Conversation" functionality
 
 **Flow:**
 1. Initializes session state and applies styling
 2. Sets up the sidebar with features toggle and report generation button
 3. Displays chat history and handles new user inputs
-4. Processes user queries through the orchestrator model
-5. Updates the UI with AI responses
+4. Prioritizes conversation processing over report generation
+5. Processes user queries through the orchestrator model
+6. Updates the UI with AI responses
+7. Only processes report generation when no conversation is active
 
 ### 2. AI Model Integration (`model.py`)
 
@@ -65,11 +71,13 @@ Handles the creation of medical reports based on consultation history.
 - PDF report generation with ReportLab
 - File download functionality
 - Email integration for report sharing
+- Error handling for patient information validation
+- Conversation-aware processing to prevent disruptions
 
 **Key Functions:**
 - `extract_medical_json()`: Extracts structured medical data from conversations
 - `build_medical_report()`: Creates a formatted PDF report
-- `generate_and_download_report()`: Manages the report generation workflow
+- `generate_and_download_report()`: Manages the report generation workflow with conversation awareness
 - `show_email_form()`: Handles the email input and sending interface
 
 ### 4. Utility Functions (`utils.py`)
@@ -87,29 +95,48 @@ Provides helper functions for text processing and formatting.
 Manages the chat interface components and rendering.
 
 **Key Functions:**
-- `display_chat_history()`: Renders the chat messages
+- `display_chat_history()`: Renders the chat messages from database
 - `show_typing_indicator()`: Shows a typing animation while processing
 - `display_legal_disclaimer()`: Shows medical disclaimer
 - `get_avatars()`: Handles avatar images for the chat
 
 ### 6. Session State Management (`session_state.py`)
 
-Manages the application's state across interactions.
+Manages the application's state across interactions and integrates with database.
 
-**Key Function:**
+**Key Functions:**
 - `initialize_session_state()`: Sets up all required session variables
+- `add_message_to_history()`: Adds messages to both local cache and database
+- `get_full_history()`: Retrieves complete conversation history from database
+- `end_conversation()`: Deletes conversation data from database
 
 **State Variables:**
-- `history`: Chat message history
+- `history`: Local cache of chat message history
 - `consultation_id`: Unique ID for each consultation
 - `use_rag`: Toggle for retrieval-augmented generation
 - `processing`: Flag for response generation status
+- `conversation_lock`: Flag to prioritize conversations over report generation
 - `show_report_form`: Report generation form visibility
 - `patient_info`: Patient details for reports
 - `pdf_data`: Generated PDF report data
 - `show_email_form`: Email form visibility
 
-### 7. Styling (`styles.py`)
+### 7. Database Integration (`database.py`)
+
+Handles persistence of conversation data in Supabase.
+
+**Key Features:**
+- Supabase integration for conversation history storage
+- Error handling and fallback mechanisms
+- Conversation and message management
+
+**Key Functions:**
+- `create_conversation()`: Creates a new conversation record 
+- `save_message()`: Saves individual messages to the database
+- `get_conversation_history()`: Retrieves complete history for a consultation
+- `delete_conversation()`: Removes conversation data when no longer needed
+
+### 8. Styling (`styles.py`)
 
 Provides custom CSS styling for the application.
 
@@ -122,7 +149,7 @@ Provides custom CSS styling for the application.
 **Key Function:**
 - `apply_styling()`: Applies the custom CSS to the Streamlit app
 
-### 8. Email Service (`sendgrid_service.py`)
+### 9. Email Service (`sendgrid_service.py`)
 
 Handles email functionality for sending reports.
 
@@ -140,11 +167,12 @@ Handles email functionality for sending reports.
 
 1. **Initialization:**
    - Load environment variables
-   - Initialize session state
+   - Initialize session state and database connection
    - Apply custom styling
 
 2. **User Interaction:**
    - User inputs symptoms or medical queries
+   - Conversation lock is activated to prioritize conversation processing
    - The application displays a typing indicator while processing
 
 3. **Query Processing:**
@@ -156,10 +184,14 @@ Handles email functionality for sending reports.
    - Main response is shown in the chat
    - Detailed reasoning is available in an expandable section
    - Sources are linked to their original content
+   - All data is persisted to the database
+   - Conversation lock is released after response is processed
 
 5. **Report Generation:**
    - User clicks "Generate Report" button
-   - Application extracts structured medical data from the conversation
+   - System checks that no conversation is being processed
+   - Application retrieves full conversation history from database
+   - Input validation ensures all form fields have valid values
    - PDF report is generated with patient information and consultation details
    - User can download the report or send it via email
 
@@ -168,14 +200,20 @@ Handles email functionality for sending reports.
    - System validates email format
    - Report is sent using the SendGrid service
 
+7. **End Conversation:**
+   - User can end the conversation which deletes the data from the database
+   - A new conversation ID is generated for future interactions
+
 ## Dependencies
 
 - **Core:** openai, requests, beautifulsoup4, markdown, python-dotenv
 - **Report Generation:** jinja2, python-docx, pydantic, reportlab
 - **Web App:** streamlit
+- **Database:** supabase, postgrest
 
 ## Security and Compliance
 
 - Medical disclaimer is prominently displayed
 - Email functionality includes appropriate medical disclaimers
-- Patient data is not persisted between sessions 
+- Database storage is secured with row-level security
+- Conversations can be deleted to ensure data privacy