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GitHub - Reactance0083/pydantic-ai-email-linear-auto-tria...
reactance008 · 2026-06-16 · via Show HN

Automatically convert incoming emails into prioritized Linear issues using AI-powered triage. Extract customer information, priority levels, and issue types from raw email content, then instantly create structured tickets in your Linear workspace with Slack notifications for urgent items.

Overview

This template provides a production-ready FastAPI webhook service that:

  • Accepts emails via SMTP forwarding or Gmail API integration
  • Extracts priority, customer, and issue classification using Claude AI
  • Creates Linear issues with rich metadata and proper linking
  • Sends Slack alerts for high-priority tickets
  • Stores triage decisions for audit and refinement

Why use this?

  • Cost savings: Eliminates $20-40/mo Zapier fees + manual triage overhead
  • Speed: 30-second email-to-ticket pipeline vs. 5-minute manual routing
  • Consistency: AI-driven classification reduces human error in priority assignment
  • Extensibility: Built on Pydantic AI for easy customization of triage logic

What It Does

Email Ingestion

  • Accepts raw email POST payloads (SMTP webhook format or parsed JSON)
  • Extracts sender, subject, body, and attachment metadata
  • Supports both plain text and HTML email bodies

AI-Powered Triage

Uses Claude to extract from email content:

  • Priority level (urgent/high/normal/low)
  • Customer identifier (email domain, name, account ID)
  • Issue type (bug/feature-request/support/billing)
  • Summary (auto-generated from subject + body context)
  • Suggested assignee (based on issue type patterns, optional)

Linear Integration

  • Creates issues in your Linear workspace
  • Attaches original email as issue comment
  • Sets priority and status based on triage output
  • Links to customer/team projects (configurable)
  • Supports custom fields for email metadata

Slack Notifications

  • Posts urgent/high-priority tickets to designated channel
  • Includes customer info, issue link, and priority badge
  • Optional thread replies for follow-up updates

Audit & History

  • Stores all triage decisions in SQLite (or configured DB)
  • Enables performance monitoring and model refinement
  • Supports manual override and feedback loops

Prerequisites

Optional

  • Docker + Docker Compose (for containerized deployment)
  • PostgreSQL (for production database, defaults to SQLite)

Setup

1. Clone and Install Dependencies

git clone https://github.com/yourusername/email-linear-triage.git
cd email-linear-triage
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

2. Create Environment File

Create .env in the project root:

# API Keys
ANTHROPIC_API_KEY=sk-ant-...
LINEAR_API_KEY=lin_api_...
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL  # Optional

# Linear Configuration
LINEAR_TEAM_ID=acme  # Your Linear team slug (e.g., 'acme' from linear.app/acme)
LINEAR_PROJECT_ID=INB  # Project key for incoming emails (default: 'INB')
LINEAR_DEFAULT_STATUS=backlog  # Initial status for new issues

# Email Configuration
SMTP_SECRET_TOKEN=your-secret-token-here  # For webhook authentication
EMAIL_DOMAIN=yourdomain.com

# Database (optional)
DATABASE_URL=sqlite:///./triage.db  # Or: postgresql://user:pass@localhost/triage

# Feature Flags
ENABLE_SLACK_NOTIFICATIONS=true
ENABLE_AUTO_ASSIGN=false
TRIAGE_MODEL=claude-3-5-sonnet-20241022  # Claude model to use

3. Initialize Database

python -m alembic upgrade head

Or for SQLite (auto-created):

python -c "from app.db import init_db; init_db()"

4. Run the Server

uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

Server runs on http://localhost:8000

5. Configure Email Routing

Option A: SMTP Forwarding (Recommended)

  • In your email provider, set up a forward rule:
    • From: tickets@yourdomain.com
    • To: {your-server}/webhook/email with authentication

Option B: Gmail API

  • Enable Gmail API in Google Cloud Console
  • Download credentials JSON to ./credentials.json
  • App auto-fetches labeled emails periodically

Option C: Manual Testing

curl -X POST http://localhost:8000/webhook/email \
  -H "X-Webhook-Token: your-secret-token-here" \
  -H "Content-Type: application/json" \
  -d '{
    "from": "customer@example.com",
    "subject": "Payment processing is broken",
    "body": "Hi, our recurring invoices havent charged for 2 days. This is urgent!",
    "timestamp": "2024-01-15T14:30:00Z"
  }'

6. Set Linear Webhook (Optional, for future integration)

In Linear Settings > Integrations > Webhooks, add:

  • URL: {your-server}/webhook/linear-event
  • Events: Issue created, issue updated
  • Useful for closing issues via email replies

Usage

Basic Email-to-Issue Flow

  1. Email arrives at tickets@yourdomain.com (forwarded via SMTP)
  2. Webhook handler receives POST, validates token
  3. Claude triage classifies email (2-5 seconds)
  4. Linear issue created with extracted metadata
  5. Slack notification posted (if urgent/high)
  6. Response returned with issue URL

Example: Send an Email

curl -X POST http://localhost:8000/webhook/email \
  -H "X-Webhook-Token: your-secret-token-here" \
  -H "Content-Type: application/json" \
  -d '{
    "from": "sarah@acmecorp.com",
    "subject": "[BUG] Dashboard crashes on mobile",
    "body": "When I open the dashboard on iPhone, it instantly crashes. Happens every time. Our team cant work.",
    "timestamp": "2024-01-15T09:30:00Z"
  }'

Response (201 Created):

{
  "status": "success",
  "linear_issue_id": "INB-234",
  "linear_issue_url": "https://linear.app/acme/issue/INB-234",
  "triage_result": {
    "priority": "urgent",
    "issue_type": "bug",
    "customer_domain": "acmecorp.com",
    "summary": "Dashboard mobile app crashes on iOS",
    "suggested_assignee": "eng-mobile"
  },
  "slack_notification_sent": true,
  "processing_time_ms": 3200
}

API Endpoints

POST /webhook/email

Ingest raw email and create Linear issue

Headers:

X-Webhook-Token: {SMTP_SECRET_TOKEN}
Content-Type: application/json

Request Body:

{
  "from": "customer@example.com",
  "subject": "Issue title",
  "body": "Email body text",
  "html_body": "<p>HTML version (optional)</p>",
  "timestamp": "2024-01-15T10:00:00Z",
  "attachments": [
    {
      "filename": "screenshot.png",
      "content_base64": "iVBORw0KGgoAAAANS...",
      "mime_type": "image/png"
    }
  ]
}

Response (201 Created):

{
  "status": "success|error",
  "linear_issue_id": "INB-123",
  "linear_issue_url": "string",
  "triage_result": {
    "priority": "urgent|high|normal|low",
    "issue_type": "bug|feature|support|billing",
    "customer_domain": "string",
    "customer_name": "string (optional)",
    "summary": "string",
    "suggested_assignee": "string (optional)"
  },
  "slack_notification_sent": boolean,
  "error": "string (if status='error')"
}

POST /api/triage/override/{issue_id}

Manually override AI triage decision

Headers:

X-API-Key: {LINEAR_API_KEY}
Content-Type: application/json

Request Body:

{
  "priority": "high",
  "issue_type": "bug",
  "notes": "Manually corrected from 'low' due to context"
}

Response (200 OK):

{
  "status": "updated",
  "triage_record_id": "uuid",
  "changes": {
    "priority": {"old": "normal", "new": "high"}
  }
}

GET /api/triage/history

Retrieve triage history and metrics

Query Parameters:

  • limit=50 (default)
  • offset=0
  • priority_filter=urgent|high|normal|low (optional)
  • date_from=2024-01-01 (optional)
  • date_to=2024-01-31 (optional)

Response (200 OK):

{
  "total_processed": 342,
  "results": [
    {
      "id": "uuid",
      "email_from": "customer@example.com",
      "linear_issue_id": "INB-234",
      "priority": "high",
      "issue_type": "bug",
      "created_at": "2024-01-15T09:30:00Z",
      "processing_time_ms": 3200,
      "model_confidence": 0.94
    }
  ],
  "statistics": {
    "avg_processing_time_ms": 2800,
    "priority_distribution": {
      "urgent": 15,
      "high": 87,
      "normal": 198,
      "low": 42
    },
    "issue_type_distribution": {
      "bug": 124,
      "feature": 56,
      "support": 142,
      "billing": 20
    }
  }
}

GET /health

Service health check

Response (200 OK):

{
  "status": "healthy",
  "timestamp": "2024-01-15T10:00:00Z",
  "dependencies": {
    "anthropic": "ok",
    "linear": "ok",
    "slack": "ok",
    "database": "ok"
  }
}

Configuration

Environment Variables

Variable Required Default Description
ANTHROPIC_API_KEY Claude API key from Anthropic Console
LINEAR_API_KEY Linear API token from Settings > API
LINEAR_TEAM_ID Linear team slug (e.g., 'acme')
LINEAR_PROJECT_ID INB Linear project key for new issues
LINEAR_DEFAULT_STATUS backlog Initial issue status (backlog/todo/in_progress)
SMTP_SECRET_TOKEN Secret token for webhook authentication
SLACK_WEBHOOK_URL Slack webhook URL (leave empty to disable)
ENABLE_SLACK_NOTIFICATIONS true Post notifications for urgent/high
ENABLE_AUTO_ASSIGN false Automatically assign based on issue type
TRIAGE_MODEL claude-3-5-sonnet-20241022 Claude model (3-opus-20250219 for best accuracy)
DATABASE_URL sqlite:///./triage.db PostgreSQL or SQLite connection string
GMAIL_CREDENTIALS_PATH ./credentials.json Path to Gmail API credentials (if using Gmail)
EMAIL_DOMAIN Your email domain (for reply-to headers)
LOG_LEVEL INFO Logging level (DEBUG/INFO/WARNING/ERROR)

Pydantic AI Configuration

Edit app/config.py to customize:

# Claude model settings
TRIAGE_MODEL = "claude-3-5-sonnet-20241022"  # Change to claude-3-opus-20250219 for higher accuracy

# Triage classification thresholds
PRIORITY_KEYWORDS = {
    "urgent": ["critical", "down", "broken", "asap", "emergency"],
    "high": ["bug", "broken", "failing", "urgent"],
    "normal": ["feature", "improve"],
    "low": ["typo", "minor", "nice-to-have"]
}

# Linear field mappings
LINEAR_PRIORITY_MAP = {
    "urgent": 4,    # Urgent in Linear
    "high": 3,
    "normal": 2,
    "low": 1
}

Customization

Change Triage Prompt

Edit app/agents/triage_agent.py:

TRIAGE_SYSTEM_PROMPT = """You are an expert customer support triage system...
Analyze the email and extract:
1. Priority (urgent/high/normal/low) - consider customer tone, service impact, frequency
2. Issue type (bug/feature/support/billing) - classify by nature
3. Customer identifier - extract domain or company name
4. Concise summary - max 10 words
5. Suggested team - based on issue type
"""

Add Custom Issue Fields

In app/models/triage.py, extend TriageResult:

class TriageResult(BaseModel):
    priority: str
    issue_type: str
    customer_domain: str
    summary: str
    custom_field_1: str | None = None  # Add your field

Then update the Claude prompt to extract it, and Linear creation logic in app/integrations/linear.py:

custom_field_id = "LIN_CUSTOM_1"
issue_data["fieldValues"].append({
    "fieldId": custom_field_id,
    "value": triage_result.custom_field_1
})

Route Issues to Different Projects

In app/integrations/linear.py, modify project selection:

def get_target_project(triage_result: TriageResult) -> str:
    if triage_result.issue_type == "billing":
        return "BIL"  # Billing project
    elif triage_result.customer_domain == "enterprise.com":
        return "ENT"  # Enterprise project
    return settings.LINEAR_PROJECT_ID

Customize Slack Messages

In app/integrations/slack.py, edit the Slack payload:

blocks = [
    {
        "type": "section",
        "text": {
            "type": "mrkdwn",
            "text": f"🔴 *URGENT: {triage_result.summary}*\nCustomer: {triage_result.customer_domain}\n<{issue_url}|View in Linear>"
        }
    }
]

Use Different Claude Models

For higher accuracy (slower + more expensive):

TRIAGE_MODEL=claude-3-opus-20250219 python -m uvicorn app.main:app

For lower cost (faster):

TRIAGE_MODEL=claude-3-5-haiku-20241022 python -m uvicorn app.main:app

Add Database Persistence

Switch from SQLite to PostgreSQL:

pip install psycopg2-binary
export DATABASE_URL=postgresql://user:password@localhost:5432/triage
python -m alembic upgrade head

Testing

Run Unit Tests

Test Triage Agent Locally

python -m app.agents.triage_agent --email-from "customer@example.com" --subject "Payment failed" --body "We can't process payments today"

Mock Email Webhook

python scripts/test_email_webhook.py

Deployment

Docker Compose

See docker-compose.yml for production config (PostgreSQL, environment variables).

Heroku

git push heroku main
heroku config:set ANTHROPIC_API_KEY=sk-ant-...
heroku config:set LINEAR_API_KEY=lin_api_...

AWS Lambda

pip install aws-wsgi
# See Dockerfile.lambda for container image setup

Troubleshooting

"Invalid Linear API Key"

"Claude rate limit exceeded"

  • Upgrade Anthropic plan or implement request queueing
  • Batch emails in peak hours

"Slack notification not sent"

  • Verify SLACK_WEBHOOK_URL is set and valid
  • Check Slack workspace webhook permissions
  • Set ENABLE_SLACK_NOTIFICATIONS=false to skip errors

"Database connection error"

  • For SQLite: ensure triage.db directory is writable
  • For PostgreSQL: verify host/port/credentials
  • Run python -c "from app.db import init_db; init_db()" to reinitialize

Performance Metrics

Typical performance on Sonnet 3.5:

  • Email parsing: 50ms
  • Claude triage: 2-4s (network + inference)
  • Linear issue creation: 300-800ms
  • Slack notification: 200-500ms
  • Total end-to-end: 2.5-6s

License

MIT License — see LICENSE file for details.

Built with Pydantic AI, FastAPI, and Linear API.