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add real-world example overview page (#8442)
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# Real-World Examples
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This section demonstrates practical applications of DSPy across different domains and use cases. Each tutorial shows how to build production-ready AI systems using DSPy's modular programming approach.
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## Featured Examples
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### 📄 [Generating llms.txt](../llms_txt_generation/index.md)
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Learn how to create AI-powered documentation generators that analyze codebases and produce structured, LLM-friendly documentation following the llms.txt standard.
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**Key Concepts:** Repository analysis, meta-programming, documentation generation
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### 📧 [Email Information Extraction](../email_extraction/index.md)
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Build intelligent email processing systems that classify messages, extract entities, and identify action items using DSPy's structured prediction capabilities.
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**Key Concepts:** Information extraction, classification, text processing
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### 🧠 [Memory-Enabled ReAct Agents with Mem0](../mem0_react_agent/index.md)
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Create conversational agents with persistent memory using DSPy ReAct and Mem0 integration for context-aware interactions across sessions.
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**Key Concepts:** Memory systems, conversational AI, agent persistence
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### 💰 [Financial Analysis with Yahoo Finance](../yahoo_finance_react/index.md)
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Develop financial analysis agents that fetch real-time market data, analyze news sentiment, and provide investment insights using LangChain tool integration.
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**Key Concepts:** Tool integration, financial data, real-time analysis

docs/mkdocs.yml

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- Streaming: tutorials/streaming/index.md
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- Async: tutorials/async/index.md
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- Real-World Examples:
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- Overview: tutorials/real_world_examples/index.md
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- Generating llms.txt: tutorials/llms_txt_generation/index.md
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- Memory-Enabled ReAct Agents: tutorials/mem0_react_agent/index.md
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- Financial Analysis with Yahoo Finance: tutorials/yahoo_finance_react/index.md

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