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Merge pull request #180 from mongodb-developer/voice-memory-wip
Voice memory wip
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apps/voice-memory-demo/README.md

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A Next.js demo showcasing persistent memory for voice AI agents using **Gemini Live** and **MongoDB**.
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Based on the article: [Building Persistent Memory for Voice AI Agents with MongoDB](../article.md)
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Based on the article: [Building Persistent Memory for Voice AI Agents with MongoDB](https://dev.to/mongodb/building-persistent-memory-for-voice-ai-agents-with-mongodb-1obe)
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## Features
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GOOGLE_API_KEY=your_gemini_api_key
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MONGODB_URI=mongodb+srv://...
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MONGODB_DB=voice_memory_demo
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VOYAGE_AI_API_KEY=your_voyage_ai_key # Optional, for semantic search
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VOYAGE_AI_API_KEY=your_voyage_ai_key
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```
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### 3. Run the Development Server
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### 4. Create MongoDB Indexes
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For hybrid search (vector + text) with `$rankFusion`, you need to create two Atlas Search indexes on the `memories` collection:
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For hybrid search (vector + text) with `$rankFusion` (require latest Atlas version cluster), the code creates on startup two Atlas Search indexes on the `memories` collection:
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#### Vector Search Index
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**Index Name:** `memory_vector_index`
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In Atlas UI: **Search Indexes****Create Search Index****Atlas Vector Search**
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Optional: In Atlas UI: **Search Indexes****Create Search Index****Atlas Vector Search**
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```json
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{
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**Index Name:** `memory_text_index`
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In Atlas UI: **Search Indexes****Create Search Index****Atlas Search**
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Optional: In Atlas UI: **Search Indexes****Create Search Index****Atlas Search**
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```json
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{

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