This application helps you generate professional client communication reports by analyzing your email communications with clients. It combines Next.js, TypeScript, the Vercel AI SDK, Microsoft Graph API, and PostgreSQL to create a powerful AI tool for client communication management.
- Create and manage clients with their domains and email addresses
- Filter emails by client domains and addresses
- Organize communications by client for better relationship management
- Generate detailed client communication reports using OpenAI GPT-4o
- Customizable report formats with placeholders
- Save and reuse report templates
- AI synthesizes emails into structured reports with key topics, action items, and more
- Two-tier processing approach for efficient and detailed analysis
- Create fully customizable report templates
- Use dynamic placeholders like
{summary}
,{key_topics}
,{action_items}
- Add your own custom placeholders (e.g.,
{key_technologies}
,{project_status}
,{stakeholders}
) - The AI intelligently generates content for any placeholder you define
- Templates can be linked to specific clients
- Craft detailed client activity reports using AI
- Sync with Microsoft 365 email accounts
- Find related emails through semantic search
- Works on desktop, tablet, and mobile devices
- PostgreSQL with pgvector extension for vector search
- Microsoft 365 account login
- Clone this repository
- Create a
.env
file based on.env.example
with your:OPENAI_API_KEY
- Get from OpenAI PlatformWEBHOOK_SECRET
- Random string for webhook security- Microsoft Graph API credentials for authentication
- Install dependencies:
npm install
- Start the development server:
npm run dev
- Initialize the database:
npm run db:migrate
- For webhook testing, use
npm run dev:webhook
with smee.io
- Frontend: Next.js, React, TailwindCSS, shadcn/ui
- Backend: Next.js API Routes
- Database: PostgreSQL with pgvector extension
- AI: OpenAI GPT-4o via Vercel AI SDK
- Authentication: Microsoft OAuth via MSAL
- Email Integration: Microsoft Graph API
Emails are fetched from two sources:
- Microsoft Graph API - directly fetches emails from your Microsoft account
- Webhook endpoint - can be connected to other email services like Gmail using external scripts
The system validates, processes, and stores these emails with AI-generated summaries and labels using a dynamic approach for efficiency.
The application uses smart, model-aware limits to process emails optimally:
- Model-based Dynamic Sizing: Automatically adjusts processing based on the AI model's context window
- Adaptive Content Analysis: Allocates more tokens to important/recent emails and less to older ones
- Token Budget Optimization: Calculates exact limits based on current model's capabilities
-
Model Selection: Control which AI models to use for different tasks:
OPENAI_SUMMARY_MODEL
: Model for email summarization (default: gpt-3.5-turbo)OPENAI_REPORT_MODEL
: Model for generating reports (default: gpt-4o-2024-08-06)OPENAI_EMBEDDING_MODEL
: Model for vector embeddings (default: text-embedding-3-small)
-
Dynamic Limits: Enable/disable dynamic calculation:
USE_DYNAMIC_MODEL_LIMITS
: Set to "true" to use model-aware limits (default: true)
-
Configurable Fallback Limits: Override defaults when needed:
EMAIL_FETCH_LIMIT
: Maximum emails to fetch (default: 1000)EMAIL_PROCESSING_BATCH_SIZE
: Emails to process in background tasks (default: 200)EMAIL_EMBEDDING_BATCH_SIZE
: Emails to create embeddings for (default: 200)EMBEDDING_BATCH_SIZE
: Batch size for embedding processing (default: 20)
The application analyzes emails related to specific clients and generates comprehensive reports that summarize communications, highlight key topics, identify action items, and more. Reports are fully customizable with templates that support any placeholder fields you define. The processing happens in two stages:
- Initial summarization of individual emails
- Comprehensive analysis across the full email thread context
When creating a report, you can:
- Select a client to filter relevant emails
- Choose a date range for the report
- Use an existing template or create your own format
- Add custom placeholders for specialized content
- Link templates to specific clients for quick report generation
To access the admin dashboard for reviewing user feedback and telemetry, follow these steps:
-
First, you need to sign in with your Microsoft account. The system is configured to only allow users with specific email domains (as configured in the environment settings).
-
Navigate to the main application and use the "Sign in with Microsoft" button if you're not already authenticated.
-
Once authenticated, navigate to the admin feedback dashboard by going to:
/admin/feedback
-
This dashboard provides comprehensive analytics on user feedback and telemetry, including:
- Total reports generated
- Average user ratings
- Vector search usage percentage
- Average report generation time
- Clipboard copy rate
- Feedback submission rate
- Most common user actions
The feedback dashboard displays:
- Summary Statistics: Key metrics in card format at the top of the page
- Recent Feedback: A detailed table showing:
- Date of feedback
- Client information
- User ratings (1-5 stars)
- Vector search usage
- Email count
- Actions taken by users
- Feedback text/comments
- Access is restricted to users with authorized email domains (as configured in the application)
- The data is fetched from the
/api/admin/feedback
endpoint - You can return to the main reports page using the "Back to Reports" link in the dashboard
If you're having trouble accessing the admin dashboard, ensure:
- You're properly authenticated with a Microsoft account
- Your email domain is authorized in the system
- You have the necessary permissions to access admin features
The AI will intelligently fill in all placeholders based on your email content, producing a comprehensive client communication report.
The reporting system supports unlimited custom placeholders. Some examples:
{client_name}
- Client's name{date_range}
- Period covered by the report{summary}
- Overall communication summary{key_topics}
- Main topics discussed{action_items}
- Tasks to be completed{next_steps}
- Upcoming actions{key_technologies}
- Technologies mentioned in emails{project_status}
- Overview of project status{stakeholders}
- Key people mentioned{open_questions}
- Questions that need answers{decision_summary}
- Summary of decisions made
You can add any placeholder that makes sense for your reporting needs, and the AI will generate appropriate content by analyzing your email communications.
MIT
The application uses environment variables to manage secrets and configuration. To set up your environment:
-
Copy
.env.example
to.env
in your local development environmentcp .env.example .env
-
Fill in your own API keys and credentials in the
.env
file- Never commit the
.env
file to version control - Never share your API keys or tokens
- Never commit the
-
The following safeguards are in place to prevent accidental credential exposure:
.env
files are excluded via.gitignore
- A pre-commit hook checks for potential secrets
- GitHub Actions workflow scans for leaked credentials
- All API routes are protected by authentication middleware
- Authentication is handled via Microsoft OAuth
- User data (emails) are only accessible to authenticated users
- Database files are excluded from version control
- User sessions are properly secured
- Always use the
env
helper fromsrc/lib/env.ts
instead of accessingprocess.env
directly - Mark variables that need to be available client-side with the
NEXT_PUBLIC_
prefix - Add new environment variables to both
.env.example
and the schema insrc/lib/env.ts
- Local database files are stored in the
/data
directory - The directory is excluded from git via
.gitignore
- Backups of production data should be properly secured
- Never commit database files to version control
The application associates clients with specific users through the user_id
field. For backward compatibility and database maintenance, several utility scripts are provided:
-
Update Client User IDs: Ensure all clients have a user ID assigned
npm run db:ensure-client-ids
-
Verify Client User IDs: Check the status of client user ID assignments
npm run db:verify-clients
-
Custom User ID: You can specify a custom default user ID
DEFAULT_USER_ID=custom@example.com npm run db:ensure-client-ids
These scripts help maintain data integrity when migrating from older versions of the application or when setting up a new environment. See the scripts/README.md
file for more detailed information about these database maintenance tools.
The application uses PostgreSQL for data storage with the pgvector extension for AI vector search capabilities. The database is automatically initialized when the application starts, ensuring the correct schema is in place.
- The database is automatically initialized when the application starts
- The initialization script checks for the existence of required tables and columns
- If the database or tables don't exist, they are created with the correct schema
- If tables exist but are missing required columns (like
user_id
), they are added automatically
The application connects to PostgreSQL using the connection string specified in the DATABASE_URL
environment variable. In development mode, the database is automatically created and initialized if it doesn't exist.
You can configure the database connection using the following environment variables:
DATABASE_URL=postgres://postgres:postgres@localhost:5432/email_agent
POSTGRES_USER=postgres
POSTGRES_PASSWORD=your_password
POSTGRES_DB=email_agent
Run the database initialization tests to verify the schema is correctly set up:
npm test tests/database-init.test.js
You can specify a custom database path using the DB_PATH
environment variable:
DB_PATH=/path/to/custom/database.db npm start