80 lines
2.1 KiB
Markdown
80 lines
2.1 KiB
Markdown
# Google Gemini File Search Templates
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This directory contains working example projects demonstrating different deployment patterns for Gemini File Search.
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## Templates
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### 🚧 basic-node-rag/ (TO BE IMPLEMENTED)
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Minimal Node.js/TypeScript example for learning and prototyping.
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**Features:**
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- Simple TypeScript setup
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- Create store → Upload documents → Query → Display citations
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- Single-file example (~200 lines)
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- Perfect for understanding core concepts
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**Use When:**
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- Learning File Search API
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- Quick prototyping
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- Building CLI tools
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### 🚧 cloudflare-worker-rag/ (TO BE IMPLEMENTED)
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Edge deployment with Cloudflare Workers + R2 integration.
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**Features:**
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- Cloudflare Workers with @cloudflare/vite-plugin
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- R2 integration for document storage
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- Edge API endpoints (upload, query)
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- Hybrid architecture (Gemini File Search + Cloudflare edge)
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- Wrangler configuration
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**Use When:**
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- Building global edge applications
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- Integrating with Cloudflare stack (D1, R2, KV)
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- Need low-latency worldwide
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### 🚧 nextjs-docs-search/ (TO BE IMPLEMENTED)
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Full-stack Next.js application with UI.
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**Features:**
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- Next.js 14+ App Router
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- Document upload UI with drag-and-drop
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- Real-time search interface
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- Citation rendering with source links
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- Metadata filtering UI
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- Tailwind CSS + shadcn/ui
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- TypeScript throughout
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**Use When:**
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- Building production documentation sites
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- Creating knowledge base UIs
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- Need full-stack app with frontend
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## Structure
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Each template includes:
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- `README.md` - Setup and deployment instructions
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- `package.json` - Dependencies and scripts
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- `tsconfig.json` - TypeScript configuration
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- `.env.example` - Environment variables template
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- `src/` - Source code
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- Working example with sample data
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## Development Status
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**Completed:** 0/3 templates (0%)
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**Priority:**
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1. basic-node-rag (foundational example)
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2. nextjs-docs-search (most practical for users)
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3. cloudflare-worker-rag (advanced integration)
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## Notes
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All templates demonstrate:
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- Proper error handling from SKILL.md
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- Recommended chunking configurations
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- Metadata schema best practices
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- Operation polling patterns
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- Cost-aware implementations
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