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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
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Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM
| Date | Stars |
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| 2026-07-31 | 466 |
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# Marsha AI Language [](https://discord.gg/p5BTaWAdjm) [](https://github.com/alantech/marsha) <p align="center"><b>Describe Logic ⴲ Provide Examples ⴲ Run Reliably</b><br /><br /><img src="./examples/images/duckduckgo-terminal.gif" /></p> Marsha is an LLM-based programming language. Describe what you want done with a simple syntax, provide examples of usage, and the Marsha compiler will guide an LLM to produce tested Python software. ## Usage The Marsha compiler can be used to compile the syntax using a `uv`-installed package via a terminal or Jupyter Notebook: ```bash uv pip install git+https://github.com/alantech/marsha python -m marsha data_mangling.mrsh ``` From a source checkout you can instead install a `marsha` command directly: ```bash make install # Linux / macOS install.bat # Windows ``` This builds a virtualenv with Marsha in it and drops a small launcher script at `~/.local/bin/marsha` (`~/.local/bin/marsha.bat` on Windows; override the location with `make install PREFIX=/usr/local` or `install.bat C:\tools`) that simply runs `python -m marsha` from that virtualenv, passing your arguments through. The venv location can be overridden per-invocation with the `MARSHA_VENV` environment variable, and `make uninstall` / `uninstall.bat` remove the launcher. ## Syntax The Marsha syntax looks a lot like markdown and is a mixture of English and mathematical notation. It has its own file format `.mrsh` that houses function definition(s). The syntax is subject to change as Marsha is currently in an alpha state. If you have a legitimate use case for Marsha, please let us know. ### Data Types Data types provide function type safety which helps improve the accuracy of the code generation. The data type format is almost identical to the CSV format. ```md # type EmployeeSkills name, skill Bob, math Jake, spreadsheets Lisa, coding Sue, spreadsheets ``` It is also possible for Marsha to infer the data type from CSV file ```md # type EmployeesByDepartment employees_by_department.csv ``` ### Functions Functions are the bread and butter of Marsha and can easily define transformations between different data types. There are three sections to a Marsha function: the declaration, the description, and the examples. The declaration is a Markdown heading section prefixed with `func`, then followed by a name, parenthesis containing the input type(s), and finally a colon followed by the output type. The name must be a single word, but the types don't need to be classic software types, or even the explicit data types defined above. They can themselves be simple descriptions of what the type is meant to be. Eg, ```md # func get_employee_skills(list of EmployeesByDepartment, list of DepartmentSkills): list of EmployeeSkills ``` The next section is the description of the function. Here you explain what the function should do. Being more explicit here will reduce variability in the generated output and improve reliability in behavior, but it's up to you just how explicit you will be and how much you leave to the LLM to figure out. This is similar to declarative languages like SQL and HTML where there are defaults for things you do not specify, like the sort order of `select` statements or the default styling of a `<div>`. Eg, ```md This function receives a list of EmployeesByDepartment and a list of DepartmentSkills. The function should be able to create a response of EmployeeSkills merging the 2 list by department. Use the pandas library. ``` The final section is the example section. Here you provide examples of calling the function and what its output should be. Marsha uses this to provide more information to the LLM to generate the logic you want, but also uses it to generate a test suite to validate that what it has generated actually does what you want it
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matched fp:3ec2d94d930d2c32, llm:Repository description: 'Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM'
matched fp:3ec2d94d930d2c32, llm:Repository description: 'Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM'
matched fp:3ec2d94d930d2c32, llm:Repository description: 'Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM'