# SyGra is a low-code/no-code framework for creating and transforming LLM and SLM datasets

DevFeed: [SyGra is a low-code/no-code framework for creating and transforming LLM and SLM datasets](<https://devfeed.tech/articles/sygra-the-one-stop-framework-for-building-data-for-llms-and-slms-7051.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/ServiceNow-AI/sygra-data-gen-framework>)

Author: Bidyapati Pradhan; Vipul Mittal; Amit Kumar Saha; Surajit Dasgupta

Published: 2025-09-22T06:45:05Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [datasets](<https://devfeed.tech/topics/datasets.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Low code](<https://devfeed.tech/topics/low-code.md>), [dpo](<https://devfeed.tech/topics/dpo.md>), [Python](<https://devfeed.tech/topics/python.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [dpo](<https://devfeed.tech/tags/dpo.md>), [llms](<https://devfeed.tech/tags/llms.md>), [low-code](<https://devfeed.tech/tags/low-code.md>), [ollama](<https://devfeed.tech/tags/ollama.md>), [python](<https://devfeed.tech/tags/python.md>), [rag](<https://devfeed.tech/tags/rag.md>), [tgi](<https://devfeed.tech/tags/tgi.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

## AI overview

SyGra is presented as a low-code/no-code Python framework for creating, transforming, and aligning datasets for large and small language models. It supports use cases including Q&A generation, preference-pair creation, reasoning data, multilingual adaptation, quality filtering, and RAG-oriented datasets.

## Source excerpt

You start with a simple dataset, but the model fails on advanced reasoning tasks. How do you generate more complex datasets to strengthen performance? You already have a knowledge base, but it's not in Q&A format. How can you transform it into a usable question-answering dataset? You've prepared a supervised fine-tuning (SFT) dataset. But now you want to align your model using Direct Preference Optimization (DPO). How can you generate preference pairs?