docs(devlog): DevLog @ 2025.07.18 #289
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Summary of Changes
Hello @LemonNekoGH, I'm Gemini Code Assist1! 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 introduces a new development log entry that reflects on the current state of the airi-factorio project, incorporates learnings from external research, and outlines a strategic shift in its underlying architecture. The main README.md is also updated to ensure discoverability and consistency of documentation links.
Highlights
- New DevLog Publication: A new development log entry for July 18, 2025, has been published, detailing a significant architectural re-evaluation for the
airi-factorioproject. - README Update: The
README.mdfile has been updated to include a link to the latest DevLog and to standardize the URL format for previous DevLog entries. - Project Retrospective and Analysis: The new DevLog provides a detailed review of the initial
airi-factorioimplementation, highlighting challenges encountered, and analyzes insights gained from the 'Factorio Learning Environment' research paper. - Proposed Architectural Shift: A new architectural direction for
airi-factoriois proposed, moving away from direct LLM Lua code generation towards a Golang-based MCP server approach for improved robustness and maintainability.
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Code Review
This pull request adds a new devlog for July 18, 2025, in both English and Chinese. It also updates the links to previous devlogs in the main README.md for consistency. The changes are well-structured. My review focuses on improving the clarity, consistency, and technical accuracy of the documentation.
… English Co-authored-by: Neko <neko@ayaka.moe>
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| They evaluated mainstream LLMs like Claude 3.5 Sonnet, GPT-4o, Deepseek-v3, Gemini-2, etc., but in Lab-play, even the strongest Claude 3.5 at the time only completed 7 levels. | ||
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| Reading this, I became curious. Their evaluation was so complex, so they must have also ensured maintainability technically. How did they achieve this? Continuing to read, I found that their implementation method was very similar to `airi-factorio`, but had many advantages compared to `airi-factorio`: |
There was a problem hiding this comment.
| Reading this, I became curious. Their evaluation was so complex, so they must have also ensured maintainability technically. How did they achieve this? Continuing to read, I found that their implementation method was very similar to `airi-factorio`, but had many advantages compared to `airi-factorio`: | |
| Reading this, I became curious. Their evaluation was so complex, they must have also ensured maintainability technically. How did they achieve this? Continue reading, I found that their implementation method was very similar to `airi-factorio`, but had many advantages compared to `airi-factorio`: |
Try not to say so so many times. (Sorry I said here too)
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Neko <neko@ayaka.moe>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Neko <neko@ayaka.moe>
Co-authored-by: Neko <neko@ayaka.moe>
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