Developer-first hub for open-source AI workflows with reusable blueprints for OCR, training, agents, and more.
Blueprints is a developer-first hub for open-source AI workflows, offering a collection of reusable, customizable blueprints for tasks like OCR, synthetic data detection, model training, evaluation, embedding, local AI, federated AI, finetuning, text-to-text, text-to-speech, speech-to-text, image segmentation, object detection, automatic speech recognition, and agents. Each blueprint includes open-source models, a README, demo app, config file, and CLI support, enabling developers to quickly build and deploy AI solutions.
Key Features
check_circleReusable AI blueprints
check_circleOpen-source models and tools
check_circleCLI support
check_circleDemo app (Streamlit/Gradio) or Jupyter notebook
check_circleConfig file for customization
check_circleREADME and organized folder structure
check_circleCPU compatibility for local setups
check_circleGoogle Colab notebook option
check_circlePyPI package availability
check_circleDockerfile for demo app
check_circleDiagram in README
check_circleSetup and guidance docs using mkdocs
check_circleGitHub template repo
Use Cases
lightbulbDevelopers building an OCR pipeline can use the LLM Document Parser blueprint to extract structured data from scanned documents, reducing development time from weeks to days.
lightbulbMachine learning engineers training a synthetic audio detection model can follow the blueprint to train and deploy a detector, achieving high accuracy without starting from scratch.
lightbulbData scientists finetuning an LLM with federated learning can leverage the Federated AI blueprint to collaborate on private datasets, ensuring data privacy while improving model performance.
lightbulbAI researchers comparing agent frameworks can use the surf spot finding blueprint to evaluate different agents on a real-world task, selecting the best framework for their needs.
lightbulbDevelopers building a speech-to-text application can use the Whisper transcription blueprint to transcribe audio files with open-source models, integrating a self-hosted API in hours.
lightbulbContent creators converting documents to Markdown can use the Docling CLI blueprint to automate the conversion, saving hours of manual formatting per week.
lightbulbDevelopers creating personalized timeline algorithms can use the Build Your Own Timeline Algorithm blueprint to customize content ranking, delivering relevant feeds to users.
