translation/source/documents/course/03-agent-memory/25-combining-memory-feature...

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# Building a Complete Memory-Enhanced Agent
In this final step, we'll bring together all the memory features we've explored to create a complete memory-enhanced agent. We'll also create a practical example that demonstrates how these features work together.
## Combining All Memory Features
Let's create a comprehensive agent that utilizes conversation history, semantic recall, and working memory:
```typescript
// src/mastra/agents/memory-agent.ts
import { Agent } from "@mastra/core/agent";
import { Memory } from "@mastra/memory";
import { openai } from "@ai-sdk/openai";
import { LibSQLStore, LibSQLVector } from "@mastra/libsql";
// Create a comprehensive memory configuration
const memory = new Memory({
storage: new LibSQLStore({
id: "learning-memory-storage",
url: "file:../../memory.db", // relative path from the `.mastra/output` directory
}),
vector: new LibSQLVector({
connectionUrl: "file:../../vector.db", // relative path from the `.mastra/output` directory
}),
embedder: openai.embedding("text-embedding-3-small"),
options: {
// Conversation history configuration
lastMessages: 20, // Include the last 20 messages in the context
// Semantic recall configuration
semanticRecall: {
topK: 3, // Retrieve 3 most similar messages
messageRange: {
before: 2, // Include 2 messages before each match
after: 1, // Include 1 message after each match
},
},
// Working memory configuration
workingMemory: {
enabled: true,
template: `
# User Profile
## Personal Info
- Name:
- Location:
- Timezone:
- Occupation:
## Preferences
- Communication Style:
- Topics of Interest:
- Learning Goals:
## Project Information
- Current Projects:
- [Project 1]:
- Deadline:
- Status:
- [Project 2]:
- Deadline:
- Status:
## Session State
- Current Topic:
- Open Questions:
- Action Items:
`,
},
},
});
```
This comprehensive memory configuration combines all three memory features we've explored:
1. **Conversation history** with the `lastMessages` option
2. **Semantic recall** with the `semanticRecall` option
3. **Working memory** with the `workingMemory` option
Each feature serves a different purpose in enhancing your agent's memory capabilities, and together they create a powerful memory system that can maintain context across conversations and provide personalized responses.