GitHub
Open-source vernacular text normalization for AI pipelines
What it does
Normalize Indian code-mixed text before LLM, RAG, and routing workflows. Includes API endpoints, Docker deploy path, language-pack design, and practical integration examples.
Does the same job
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- IBI built an AI that turns GitHub codebases into easy tutorials2025 · github.com · ▲923
https://the-pocket.github.io/Tutorial-Codebase-Knowledge/

- RHReplace "hub" by "ingest" in GitHub URLs for a prompt-friendly extract2024 · gitingest.com · ▲185
Gitingest is a open-source micro dev-tool that I made over the last week. It turns any public Github repository into a text extract that you can give to your favourite LLM easily. Today I added this url trick to make it even easier to use! How I use it myself: - Quickly generate a README.md boilerplate for a project - Ask LLMs questions about an undocumented codebase It is still very much work in progress and I plan to add many more options (file size limits, exclude patterns..) and a public API I hope this tool can help you Your feedback is very valuable to help me prioritize And…

- GAGitHub-assistant – Natural language questions from your GitHub data2024 · github.com · ▲49
Simon(sfarshid) and I spend a lot of time on GitHub. As data nerds we put together a quick tool to explore your repository’s data. How it works: - Data Loading: We use dlt to pull data (issues, PRs, commits, stars) from GitHub - Semantic Layer: Relta wraps the underlying dataset into a semantic layer so the LLM doesn’t hallucinate. - Text-to-SQL: A text-to-SQL agent transforms your plain-English question into a query using the semantic layer - Generative Charts: assistant-ui dynamically generates a chart based on the SQL query - Refinements: If the semantic layer can’t handle your question,…
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