posts/dsci_llm


# Title You can create any workflow or pipeline you want with DSCI and LLM # Description How to create any sort of pipelines using DSCI and LLM # Tags devops, ai, ci, LLM --- [DSCI](https://deadsimpleci.sparrowhub.io) - is a self hosted git server with embedded CI runner. The cool thing about it that advances it position among other tools: - You can use many popular programming languages to create CI scenarios, no need entangled YAML - You can generate CI pipeline by talking to AI agent using public [DSCI sandbox](http://dsci.sparrowhub.io:8080/) --- Here the thing. Just ask LLM what do you need and you'll get your answer in seconds: ``` Create DSCI pipeline to build golang project with unit tests and go vet and publishing resulted container image based on Alpine to external container registry. Please use Bash or Python as preferable language for CI pipeline ``` If you don't believe me those are examples I've created for myself, by just playing with DSCI and LLM: --- * [Python / selenium tests ci pipeline](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/1c9fb55.1789580532/answer) * [Execute chef cookbook on remote host](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/007aefe.1789618706/answer) * [Execute Ansible playbook on remote host](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/007aefe.1789617896/answer) * [C++ with cmake](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/007aefe.1789628812/answer) * [Node.js with npm project](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/007aefe.1789654909/answer) * [Create DSCI pipeline to deploy AI agent on localhost , use some popular Agent framework and LLM](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/007aefe.1789718838/answer) * [Python+pytest+coverage](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/1c9fb55.1789570454/answer) * [Golang+unit tests+ coverage + docker image push](http:/doc//dsci.sparrowhub.io:8080/file_view/dsci/1c9fb55.1789570619/answer) * [Perl/Mariadb service/doc/Sqlite/Curl](http://dsci.sparrowhub.io:8080/file_view/dsci/1c9fb55.1789573431/answer) Now, what amazing about all those examples: * They are pretty accurate in a sense of correctness of code they generated ( believe me I am - DSCI author ) * They are built in seconds * I use my free GROQ tokens to build them ( now this is part of DSCI sandbox service ) - that means - not a lot of tokens is required to build such a code --- How to use it ? Use this link - [http://dsci.sparrowhub.io:8080/repo/pipeline-generator.git](http://dsci.sparrowhub.io:8080/repo/pipeline-generator.git) To build pipeline for your requirements, just say something: > Build DSCI pipeline for typical Python project with pytest unit tests and code coverage more then X Then just for a few seconds, go to the builds/ page and pick up the latest `dsci@*` build, click on artifacts links and get your answer.md You can do more than that. AI agent is smart enough to nail it down for you. ---