### USER I want to build an LLM agent that leverages tool usage and reasoning in order to act as an Email Triage Agent. I imagine having a list of categories (or tags i guess since I’m on gmail?) that the LLM agent can then sort the emails into their respective folders by using the tools available to them, but I want to make sure that the agent has all the tools it could need in order to get all the information and context about the inbox and its emails, and how to allow it to organize the data in a way that is safe to my data. What tools should I include with the agent ### ASSISTANT
Thinking… > > We are building an Email Triage Agent for Gmail. The agent will categorize emails into folders (labels in Gmail) based on a predefined list of categories. > > Key components: > 1. **Tools for Information Gathering**: The agent needs to access the email data to make decisions. > 2. **Tools for Action**: The agent needs to move emails to the correct folders (labels). > > Since we are using Gmail, we can leverage the Gmail API. However, note that the agent must be run in a secure environment to protect user data. > > Tools to include: > > 1. **Gmail API Access**: > - `list_emails`: Retrieve a list of emails from the inbox (with optional filters like unread, date range, etc.). > - `get_email_details`: Fetch the full content (subject, sender, date, body) of a specific email by its ID. > - `search_emails`: Search emails based on criteria (query string, date range, etc.). > - `update_email_labels`: Add or remove labels (folders) from an email. > > 2. **Categorization Logic**: > - The agent should be able to parse the email content (subject, body, sender) and decide which category it belongs to. > - We can provide a list of categories (tags) that the agent can choose from. > > 3. **Safety and Data Protection**: > - The agent should only have access to the user's Gmail account via OAuth 2.0 tokens (with minimal scopes: read, send, and modify). > - We must ensure that the agent does not leak data. Therefore, we should run the agent in a secure environment (e.g., on the user's device or in a secure cloud environment with restricted access). > - We can implement logging and monitoring to track the agent's actions. > > 4. **User Interface (Optional)**: > - A way to define the categories and their corresponding labels (folder names) in Gmail. > - A dashboard to review the agent's actions and adjust settings. > > Implementation Steps: > > 1. **Set up Gmail API**: > - Register a project in the Google Cloud Console. > - Enable the Gmail API. > - Create OAuth 2.0 credentials (client ID and secret). > - Request the user to grant permissions (scopes: `https://www.googleapis.com/auth/gmail.modify`). > > 2. **Agent Architecture**: > - **Inbox Processor**: Fetches emails (using `list_emails` or `search_emails`). > - **Email Parser**: Extracts key information (sender, subject, body) and uses the LLM to classify the email into one of the predefined categories. > - **Action Executor**: Moves the email to the correct label using `update_email_labels`. > > 3. **Agent Workflow**: > - Step 1: Get the list of emails (e.g., unread emails). > - Step 2: For each email, get the full details (if needed for classification). > - Step 3: Use the LLM to assign a category (from the predefined list). > - Step 4: Update the email's labels (add the assigned category label and remove any previous non-relevant labels). > > 4. **Security Measures**: > - Store OAuth tokens securely (e.g., encrypted storage). > - Run the agent in a sandboxed environment (e.g., Docker container) to prevent unauthorized access to the host system. > - Only allow the agent to access the Gmail account with the minimal required permissions. > > 5. **Error Handling**: > - Handle API rate limits and errors gracefully. > - Log errors and notify the user of any issues. > > Example Code Snippet (Python with Gmail API): > > ```python > from google