# SMNETSTUDIO/WeChat-AI SLOC report

> As of 2026-09-16 (commit afcc6511c128), SMNETSTUDIO/WeChat-AI contains 47,042 total lines: 39,647 code, 4,027 comments, 3,368 blank, across 171 files in 11 languages (top: TypeScript 85.1%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

SMNETSTUDIO/WeChat-AI has 39,647 source lines of code out of 47,042 total lines across 171 files, counted from the afcc6511c1280516dbfa9251eecb76e87f1d8038 ref at commit afcc6511c128 by the OctoCounts tokei engine on 2026-09-16. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving SMNETSTUDIO/WeChat-AI to commit afcc6511c128, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

## Repository size insights

This is a medium-sized codebase by counted code lines. Code represents 84.3% of all lines, comments represent 8.6%, and the repository averages 232 code lines per file. TypeScript accounts for 85.1% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| TypeScript | 124 | 39,974 | 33,737 | 3,462 | 2,775 |
| HTML | 5 | 2,490 | 2,367 | 49 | 74 |
| JavaScript | 6 | 1,569 | 1,344 | 102 | 123 |
| YAML | 3 | 1,473 | 1,327 | 26 | 120 |
| Python | 11 | 606 | 487 | 6 | 113 |
| JSON | 13 | 238 | 238 | 0 | 0 |
| SVG | 1 | 76 | 76 | 0 | 0 |
| Dockerfile | 2 | 121 | 58 | 38 | 25 |
| TOML | 1 | 30 | 13 | 15 | 2 |
| Markdown | 4 | 456 | 0 | 320 | 136 |
| Plain Text | 1 | 9 | 0 | 9 | 0 |

Top language (TypeScript 85.1%). Generated at 2026-09-16T04:49:33.361665164+00:00. Canonical report: https://octocounts.com/github/SMNETSTUDIO/WeChat-AI

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/SMNETSTUDIO/WeChat-AI/commit/afcc6511c1280516dbfa9251eecb76e87f1d8038?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does SMNETSTUDIO/WeChat-AI have?

SMNETSTUDIO/WeChat-AI has 47,042 total lines, including 39,647 code lines, 4,027 comment lines, and 3,368 blank lines.

### How was the SMNETSTUDIO/WeChat-AI line count measured?

OctoCounts resolved the public GitHub repository to commit afcc6511c128, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for SMNETSTUDIO/WeChat-AI?

This OctoCounts report was generated from afcc6511c1280516dbfa9251eecb76e87f1d8038 at commit afcc6511c128 on 2026-09-16T04:49:33.361665164+00:00.

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