wehub-resource-sync
93 lines
6.0 KiB
Plaintext
93 lines
6.0 KiB
Plaintext
---
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title: "Mastra agents with memory sharing + Trigger.dev task orchestration"
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sidebarTitle: "Mastra agents with memory"
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description: "Multi-agent workflow with persistent memory sharing using Mastra and Trigger.dev for clothing recommendations based on weather data."
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---
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## Overview
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Enter a city and an activity, and get a clothing recommendation generated for you based on today's weather.
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By combining Mastra's persistent memory system and agent orchestration with Trigger.dev's durable task execution, retries and observability, you get production-ready AI workflows that survive failures, scale automatically, and maintain context across long-running operations.
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## Tech stack
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- **[Node.js](https://nodejs.org)** runtime environment
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- **[Mastra](https://mastra.ai)** for AI agent orchestration and memory management (Mastra is a Typescript framework for building AI agents, and uses Vercel's AI Agent SDK under the hood.)
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- **[PostgreSQL](https://postgresql.org)** for persistent storage and memory sharing
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- **[Trigger.dev](https://trigger.dev)** for task orchestration, batching, and observability
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- **[OpenAI GPT-4](https://openai.com)** for natural language processing
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- **[Open-Meteo API](https://open-meteo.com)** for weather data (no API key required)
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- **[Zod](https://zod.dev)** for schema validation and type safety
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## GitHub repo
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<Card
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title="View the Mastra agents with memory repo"
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icon="GitHub"
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href="https://github.com/triggerdotdev/examples/tree/main/mastra-agents"
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>
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Click here to view the full code for this project in our examples repository on GitHub. You can
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fork it and use it as a starting point for your own project.
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</Card>
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## Featured patterns
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- **[Agent Memory Sharing](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/trigger/weather-task.ts)**: Efficient data sharing between agents using Mastra's working memory system
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- **[Task Orchestration](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/trigger/weather-task.ts)**: Multi-step workflows with `triggerAndWait` for sequential agent execution
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- **[Centralized Storage](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/index.ts)**: Single PostgreSQL storage instance shared across all agents to prevent connection duplication
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- **[Custom Tools](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/tools/weather-tool.ts)**: External API integration with structured output validation
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- **[Agent Specialization](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/agents/)**: Purpose-built agents with specific roles and instructions
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- **[Schema Optimization](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/schemas/weather-data.ts)**: Lightweight data structures for performance
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## Project Structure
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```
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src/
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├── mastra/
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│ ├── agents/
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│ │ ├── weather-analyst.ts # Weather data collection
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│ │ ├── clothing-advisor.ts # Clothing recommendations
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│ ├── tools/
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│ │ └── weather-tool.ts # Enhanced weather API tool
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│ ├── schemas/
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│ │ └── weather-data.ts # Weather schema
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│ └── index.ts # Mastra configuration
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├── trigger/
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│ └── weather-task.ts # Trigger.dev tasks
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```
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## Relevant code
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- **[Multi-step task orchestration](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/trigger/weather-task.ts)**: Multi-step task orchestration with `triggerAndWait` for sequential agent execution and shared memory context
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- **[Weather analyst agent](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/agents/weather-analyst.ts)**: Specialized agent for weather data collection with external API integration and memory storage
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- **[Clothing advisor agent](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/agents/clothing-advisor.ts)**: Purpose-built agent that reads from working memory and generates natural language responses
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- **[Weather tool](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/tools/weather-tool.ts)**: Custom Mastra tool with Zod validation for external API calls and error handling
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- **[Weather data schema](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/schemas/weather-data.ts)**: Optimized Zod schema for efficient memory storage and type safety
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- **[Mastra configuration](https://github.com/triggerdotdev/examples/blob/main/mastra-agents/src/mastra/index.ts)**: Mastra configuration with PostgreSQL storage and agent registration
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## Storage Architecture
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This project uses a **centralized PostgreSQL storage** approach where a single database connection is shared across all Mastra agents. This prevents duplicate database connections and ensures efficient memory sharing between the weather analyst and clothing advisor agents.
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### Storage Configuration
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The storage is configured once in the main Mastra instance (`src/mastra/index.ts`) and automatically inherited by all agent Memory instances. This eliminates the "duplicate database object" warning that can occur with multiple PostgreSQL connections.
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The PostgreSQL storage works seamlessly in both local development and serverless environments with any PostgreSQL provider, such as:
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- [Local PostgreSQL instance](https://postgresql.org)
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- [Supabase](https://supabase.com) - Serverless PostgreSQL
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- [Neon](https://neon.tech) - Serverless PostgreSQL
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- [Railway](https://railway.app) - Simple PostgreSQL hosting
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- [AWS RDS](https://aws.amazon.com/rds/postgresql/) - Managed PostgreSQL
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## Learn More
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To learn more about the technologies used in this project, check out the following resources:
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- [Mastra docs](https://mastra.ai/en/docs) - learn about AI agent orchestration and memory management
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- [Mastra working memory](https://mastra.ai/en/docs/memory/overview) - learn about efficient data sharing between agents
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