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michael 908053def2 Fix data filtering race condition and allow all assistants to display 
This fixes the critical bug where all conversations and messages were being filtered out (0 results) despite successfully fetching data from the API.

Root causes fixed:
1. Race condition: window.validAssistantIds was undefined when filtering logic ran
2. Overly restrictive filtering: Only assistants with friendly names were shown
3. Assistant ID mismatch: Hardcoded IDs didn't match actual data

Changes in Dashboard.jsx:
- Replaced window global variables with React state (validAssistantIds, assistantDisplayToIdMap, etc.)
- Added guard to prevent filtering until validAssistantIds is initialized
- Removed filter that required friendly names - now all assistants display
- Use raw Assistant_ID as fallback if no friendly name exists
- Fixed useEffect dependencies to properly track state changes

Changes in assistantMapping.js:
- Added mapping for asst_eECsc64ZG3t6HHuvqR9FvoPt (Copy Assistant)
- Kept existing mappings for backwards compatibility

Result: All 469 conversations and 2471 messages now display correctly in the dashboard.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 14:32:12 -06:00
backend extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
frontend Fix data filtering race condition and allow all assistants to display 2025-11-18 14:32:12 -06:00
.env.example Configure MSAL redirect URI explicitly via environment variables 2025-11-18 09:27:13 -06:00
.gitignore extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
CLAUDE.md extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
deploy.sh Fix Vite environment variable loading during production build 2025-11-18 09:30:44 -06:00
email_analysis.py extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
README.md extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
run.sh extracted all domains, URLS, secrets, etc. to .env and wrote a deploy script to deploy on server 2025-11-12 16:27:59 -06:00
test_user_mapping.js initial commit 2025-11-12 15:55:59 -06:00
USER_FILTERING_NOTES.md initial commit 2025-11-12 15:55:59 -06:00

README.md

Oliver Agency Reporting Module

A web-based reporting module to display usage analytics for conversations and messages with various filtering options and CSV export functionality.

Project Structure

  • /backend: Python Flask backend API
  • /frontend: React + Vite frontend application

Environment Setup

Before running the application, you need to configure environment variables:

  1. Copy the example environment file:

    cp .env.example .env

  2. Edit .env with your configuration:

    • DOMAIN: Your deployment domain (e.g., yourdomain.com)
    • BASE_PATH: Application base path (default: /dashboard/)
    • AZURE_TENANT_ID: Azure AD tenant identifier
    • AZURE_CLIENT_ID: Azure AD application (client) identifier
    • BACKEND_PORT: Backend server port (default: 5001)
    • MAKE_WEBHOOK_URL: Make.com webhook endpoint
    • VITE_* variables: Duplicate the above values with VITE_ prefix for frontend

  3. Azure AD Setup:

    • Create an app registration in Azure Portal
    • Add redirect URIs for your deployment domain
    • Copy the Tenant ID and Client ID to your .env file

Getting Started

Quick Start (Recommended)

Run both backend and frontend together:

./run.sh

This script automatically loads environment variables from .env and starts both servers.

Backend

  1. Navigate to the backend directory:

    cd backend

  2. Activate the virtual environment:

    source venv/bin/activate

  3. Install dependencies:

    pip install -r requirements.txt

  4. Load environment variables and start the development server:

    # Load environment variables
set -a && source ../.env && set +a
# Start server
python app.py

The API will be available at http://localhost:{BACKEND_PORT} (default: 5001).

Frontend

  1. Navigate to the frontend directory:

    cd frontend

  2. Install dependencies:

    npm install

  3. Start the development server:

    npm run dev

The application will be available at http://localhost:5173.

Features

  • Dashboard displaying conversation and message volume over time
  • Filter data by user, assistant, brand/TOV, and date range
  • Export filtered data to CSV
  • Interactive graph with assistant-specific coloring

API Endpoints

  • GET /api/data: Returns all conversations and messages data