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Automated Terminal Session Dockerfiles
The demo shows how a pipeline of fine‑tuned LLMs converts a recorded terminal session into structured events and automatically produces a Dockerfile for reproducibility.
A lack of documentation is a common pain point for any developer recently onboarded to a team. This absence frequently leads to difficulties in the comprehension of a piece of software, often leading to errors as a result. Under the guidance of Julia Longtin of the Human Feedback Foundation, the program that will be demoed will be our solution to fill this gap in knowledge: a program that will automate the generation of either documentation or a dockerfile, wherein the latter will hence can be run to replicate commands of the user. Our program achieves this automation through dividing tasks amongst three fine-tuned variants of DeepSeek R1 (and one model responsible for markdown outputs, which had been developed by a previous team utilizing a version of Gemma).
We will be presenting the user flow of an individual inputting their terminal recording session, and receiving a dockerfile that can be used to replicate the commands used during the recording session. To output a dockerfile, we will present a session that will first be inputted to a model that will be responsible for dividing the session into relevant “events”, and these events will be both annotated (i.e., summarized) and assigned a hierarchical structure (i.e., an event being a subevent of exiting a previous event’s hierarchy) by a subsequent model. Finally, the annotated session will be inputted to a model responsible for the generation of a dockerfile, which will be ran to replicate the user’s commands during the recorded session. Further, the motivation behind this approach over other solutions will also be discussed in detail.
LoRA fine-tuned Deepseek models automate Asciinema conversion into structured documentation and Dockerfiles.
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