Introducing modular blocks architecture and reorganize study agents

[wilhelm-tiger]

This PR introduces the packages/study directory, establishing a multi-language learning path for building AI agents from scratch. It adopts an industrial, modular architecture inspired by LlamaIndex, providing both minimal baselines and pluggable components (Blocks) for TypeScript, Python, Go, and Rust.

• New Study Path: Created a comprehensive curriculum for learning agent development across four languages.

• Minimal Baselines: Established agent-*-minimal packages in each language to serve as pure, bare-bones entry points for Milestone 1

• Modular Blocks: Introduced packages/study/agent-*-blocks to house reusable components:

  • AgentEngine: A core orchestrator with lifecycle hooks.
  • ChatMemoryBuffer: A pluggable memory component (Milestone 2).

• Architectural Manifest: Added packages/study/AGENTS.md to enforce design consistency and LlamaIndex-inspired patterns.

• Documentation:

  • Added a new Build from scratch section to the documentation.
  • Completed tutorials for Milestone 1 (Chat Loop) and Milestone 2 (Memory and Context).

[github-actions]

📊 PR Size: size/XL

• Lines changed: 1666
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• Deletions: -7
• Files changed: 45

[github-actions]

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