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assets/css/index.css

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build/components/example.py

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'java-sync': '@Test',
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'java-async': '@Test',
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'java-reactive': '@Test',
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'c#': r'\[Fact]|\[SkipIfRedis\(.*\)]'
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'c#': r'\[Fact]|\[SkipIfRedis\(.*\)]',
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'c#-sync': r'\[Fact]|\[SkipIfRedis\(.*\)]',
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'c#-async': r'\[Fact]|\[SkipIfRedis\(.*\)]',
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'rust': r'#\[test]|#\[cfg\(test\)]|#\[tokio::test]'
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}
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PREFIXES = {
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'python': '#',
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'java-reactive': '//',
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'go': '//',
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'c#': '//',
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'c#-sync': '//',
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'c#-async': '//',
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'redisvl': '#',
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'php': '//',
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'rust': '//',

build/local_examples.py

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'python': 'Python',
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'node.js': 'Node.js',
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'go': 'Go',
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'c#': 'C#',
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'c#': 'C#-Sync',
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'java': 'Java-Sync', # Default to sync, could be overridden
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'php': 'PHP',
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'redisvl': 'RedisVL',
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return 'Rust-Async'
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if 'rust-sync' in path:
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return 'Rust-Sync'
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if language == 'c#':
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if 'async' in path:
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return 'C#-Async'
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if 'sync' in path:
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return 'C#-Sync'
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# Default behavior for all languages (and Java fallback)
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return get_client_name_from_language(language)
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config.toml

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gitHubRepo = "https://github.com/redis/docs"
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# Display and sort order for client examples
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clientsExamples = ["Python", "Node.js", "Java-Sync", "Java-Async", "Java-Reactive", "Go", "C#", "RedisVL", "PHP", "Rust-Sync", "Rust-Async"]
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clientsExamples = ["Python", "Node.js", "Java-Sync", "Java-Async", "Java-Reactive", "Go", "C#-Sync", "C#-Async", "RedisVL", "PHP", "Rust-Sync", "Rust-Async"]
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searchService = "/convai/api/search-service"
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ratingsService = "/docusight/api/rate"
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ratingsService = "/docusight/api/rate/docs"
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# RDI params
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rdi_rlec_min_version = "6.2.18"
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"Java-async"={quickstartSlug="lettuce"}
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"Java-reactive"={quickstartSlug="lettuce"}
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"Go"={quickstartSlug="go"}
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"C#"={quickstartSlug="dotnet"}
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"C#-Sync"={quickstartSlug="dotnet"}
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"C#-Async"={quickstartSlug="dotnet"}
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"RedisVL"={quickstartSlug="redis-vl"}
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"PHP"={quickstartSlug="php"}
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"Rust-sync"={quickstartSlug="rust"}

content/commands/hdel.md

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## Examples
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{{< clients-example set="cmds_hash" step="hdel" >}}
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HSET myhash field1 "foo"
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(integer) 1
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HDEL myhash field1
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(integer) 1
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HDEL myhash field2
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(integer) 0
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{{< /clients-example >}}
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Give these commands a try in the interactive console:
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{{% redis-cli %}}
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HSET myhash field1 "foo"
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HDEL myhash field1
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---
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Title: Redis AI Agent Builder
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alwaysopen: false
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categories:
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- docs
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- develop
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- ai
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description: Build custom AI agents powered by Redis with our interactive code generator
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linkTitle: Agent Builder
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hideListLinks: true
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weight: 50
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---
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Agents use Redis for data storage, vector search, and conversation memory. The interactive builder generates production-ready code in your preferred programming language.
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## Get started
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Use the interactive builder below to generate your custom AI agent code:
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{{< agent-builder >}}
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## What are AI agents?
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AI agents are intelligent systems that can plan, remember, and take actions to help users accomplish goals. Unlike simple chatbots, agents can remember conversations, plan multi-step tasks, use external tools, and learn from interactions.
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Redis powers these capabilities with fast, reliable data storage and retrieval that keeps your agents responsive and intelligent.
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**Learn more**: [How agents work](agent-concepts/)
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## What you can build
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Choose from two types of intelligent agents:
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- **Recommendation engines**: Personalized product and content recommendations
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- **Conversational assistants**: Chatbots with memory and context awareness
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The agent builder will generate complete, working code examples for your chosen agent type.
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## Features
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- **Multiple programming languages**: Generate code in Python, with JavaScript (Node.js), Java, and C# coming soon
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- **LLM integration**: Support for OpenAI, Anthropic Claude, and Llama 2
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- **Redis optimized**: Uses Redis data structures for optimal performance
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## After you generate your code
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Use the **Copy** or **Download** buttons and follow the steps below to test it locally:
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1. **Set up your environment**: Install Redis and the required dependencies
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2. **Configure your API keys**: Add your LLM provider credentials to environment variables
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3. **Test locally**: Start with simple conversations to verify everything works
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4. **Deploy and scale**: Use Redis Cloud for production deployments
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The generated code includes detailed setup instructions and best practices to get you started quickly. If you want to generate another agent, select the **Start again** button.
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## Learn more
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### AI agent resources
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- [How agents work](agent-concepts/) - Learn how agents work and why Redis is perfect for them
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### Redis AI documentation
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- [Redis Vector Search](/develop/interact/search-and-query/vector-search/) - Semantic search capabilities
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- [Redis Streams](/develop/data-types/streams/) - Real-time data and conversation history
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- [AI Notebooks Collection](/develop/ai/notebook-collection/) - Interactive tutorials and examples
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- [Ecosystem Integrations](/develop/ai/ecosystem-integrations/) - Redis with AI frameworks
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### Community and support
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- Join the [Redis Discord](https://discord.gg/redis) for community support
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- Explore [Redis AI Resources on GitHub](https://github.com/redis-developer/redis-ai-resources)
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- Watch [AI Video Collection](/develop/ai/ai-videos/) for tutorials and demonstrations

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