gemini-code-assist[bot] commented on PR #168:
URL: https://github.com/apache/tvm-ffi/pull/168#issuecomment-3417552761

   ## Summary of Changes
   
   Hello @tqchen, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull 
request and will post my feedback shortly. In the meantime, here's a summary to 
help you and other reviewers quickly get up to speed!
   
   This pull request significantly refines and expands the quickstart 
documentation for TVM-FFI. The changes aim to enhance clarity, provide more 
accurate and comprehensive code examples for C++ and Rust, and ensure correct 
CMake integration. The overall goal is to make it easier for users to 
understand and implement TVM-FFI across various languages and frameworks, 
improving the onboarding experience.
   
   ### Highlights
   
   * **Documentation Clarity**: Improved explanations for TVM-FFI's core 
concepts, including ABI stability, `TensorView` usage, and stream handling, 
making the quickstart guide more accessible.
   * **CMake Configuration Updates**: Updated CMake examples within the 
documentation and the `CMakeLists.txt` file to correctly use `tvm_ffi.config` 
for locating TVM-FFI targets, ensuring smoother build processes.
   * **Enhanced C++ Bundle Examples**: Introduced a new C++ example 
demonstrating how to directly bundle exported modules into a binary using 
`FromExternC` or `InvokeExternC`, offering more flexibility for integration.
   * **Refined Rust API Example**: The Rust quickstart example has been 
enhanced to better illustrate function loading and invocation, and a new hint 
was added about using Rust to implement FFI functions.
   * **Expanded Language Agnosticism**: Refined descriptions of `libmain.so`'s 
language and framework agnosticism, explicitly including support for multiple 
Python ABI versions.
   
   
   
   
   
   
   
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