REPOGEO REPORT · LITE
huang1332/finetune_dataset_maker
Default branch main · commit 4b6e2075 · scanned 5/30/2026, 3:37:11 PM
GitHub: 604 stars · 73 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface huang1332/finetune_dataset_maker, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition the README's opening to clarify specific focus
Why:
CURRENT# finetune_dataset_maker 注:新版的openai包改了api接口的用法,要使用现有代码请安装旧版,pip install openai==0.28.0 介绍视频在https://www.bilibili.com/video/BV1mg4y1g718/
COPY-PASTE FIX# finetune_dataset_maker 一个专为ChatGLM设计的微调数据集生成工具,通过GPT API或手动输入,将问题和回答快速整理成ChatGLM所需的JSON格式。 注:新版的openai包改了api接口的用法,要使用现有代码请安装旧版,pip install openai==0.28.0 介绍视频在https://www.bilibili.com/video/BV1mg4y1g718/
- hightopics#2Add relevant topics to improve discoverability
Why:
COPY-PASTE FIXChatGLM, finetuning, LLM, dataset-generation, GPT, streamlit, AI-tools
- mediumhomepage#3Add the introductory video link as the repository homepage
Why:
COPY-PASTE FIXhttps://www.bilibili.com/video/BV1mg4y1g718/
The category visibility step did not produce results for this scan (the LLM may have been unreachable). Re-run the diagnosis to get the full GEO picture.
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of huang1332/finetune_dataset_maker?passAI did not name huang1332/finetune_dataset_maker — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts huang1332/finetune_dataset_maker in production, what risks or prerequisites should they evaluate first?passAI named huang1332/finetune_dataset_maker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo huang1332/finetune_dataset_maker solve, and who is the primary audience?passAI named huang1332/finetune_dataset_maker explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of huang1332/finetune_dataset_maker. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/huang1332/finetune_dataset_maker)<a href="https://repogeo.com/en/r/huang1332/finetune_dataset_maker"><img src="https://repogeo.com/badge/huang1332/finetune_dataset_maker.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
huang1332/finetune_dataset_maker — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite