# Gavailer/Ai-talk SLOC report

> As of 2026-09-23 (commit 7474b2c14971), Gavailer/Ai-talk contains 27,723 total lines: 24,336 code, 1,024 comments, 2,363 blank, across 118 files in 13 languages (top: YAML 54.0%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

Gavailer/Ai-talk has 24,336 source lines of code out of 27,723 total lines across 118 files, counted from the main ref at commit 7474b2c14971 by the OctoCounts tokei engine on 2026-09-23. 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 Gavailer/Ai-talk to commit 7474b2c14971, 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 87.8% of all lines, comments represent 3.7%, and the repository averages 206 code lines per file. YAML accounts for 54.0% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| YAML | 5 | 14,551 | 13,152 | 13 | 1,386 |
| JSON | 6 | 7,214 | 7,214 | 0 | 0 |
| TypeScript | 61 | 2,582 | 2,284 | 11 | 287 |
| LESS | 4 | 1,461 | 1,236 | 1 | 224 |
| Vue | 26 | 377 | 350 | 0 | 27 |
| Dockerfile | 1 | 56 | 27 | 3 | 26 |
| JavaScript | 2 | 28 | 27 | 1 | 0 |
| HTML | 1 | 28 | 26 | 0 | 2 |
| Shell | 1 | 11 | 8 | 0 | 3 |
| Batch | 1 | 9 | 7 | 0 | 2 |
| CSS | 1 | 3 | 3 | 0 | 0 |
| SVG | 2 | 2 | 2 | 0 | 0 |

Top language (YAML 54.0%). Generated at 2026-09-23T08:35:42.134698234+00:00. Canonical report: https://octocounts.com/github/Gavailer/Ai-talk

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/Gavailer/Ai-talk/commit/7474b2c14971d2d9584c4b129396f9332ed87b7b?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&reportId=279f5005b076f95dfbb4ed567a3d689ad0076106e540f34370abf6faff8fb12c).

## Report FAQ

### How many lines of code does Gavailer/Ai-talk have?

Gavailer/Ai-talk has 27,723 total lines, including 24,336 code lines, 1,024 comment lines, and 2,363 blank lines.

### How was the Gavailer/Ai-talk line count measured?

OctoCounts resolved the public GitHub repository to commit 7474b2c14971, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for Gavailer/Ai-talk?

This OctoCounts report was generated from main at commit 7474b2c14971 on 2026-09-23T08:35:42.134698234+00:00.

## Similar repository reports

- [discourse/discourse-chat-integration](https://octocounts.com/github/discourse/discourse-chat-integration) — YAML, 24,018 code lines
- [cncf/sbom](https://octocounts.com/github/cncf/sbom) — YAML, 23,143 code lines
- [wechatferry/wechatferry](https://octocounts.com/github/wechatferry/wechatferry) — YAML, 25,897 code lines
- [vuejs/pinia](https://octocounts.com/github/vuejs/pinia) — YAML, 20,922 code lines
- [haloydev/examples](https://octocounts.com/github/haloydev/examples) — YAML, 20,496 code lines
- [CopilotKit/OpenIntelligentUI](https://octocounts.com/github/CopilotKit/OpenIntelligentUI) — YAML, 20,119 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)
