Sparrow: A Comprehensive Project Introduction
Overview
Sparrow is an advanced, open-source project designed to make data extraction and processing from documents and images both efficient and straightforward. Whether dealing with forms, invoices, receipts, or other unstructured data, Sparrow is built to handle it all with ease. What makes Sparrow stand out is its modular architecture, allowing for independent services and agents, each optimized for high performance.
One of the key features of Sparrow is its pluggable architecture. This means users can easily integrate various data extraction tools and run their own pipelines. For instance, Sparrow Parse supports vision-language model integration, while Instructor works well with unstructured data formats. Additionally, Sparrow offers solutions for local LLM (Large Language Model) data extraction, utilizing a range of backends such as vLLM, Ollama, PyTorch, or Apple MLX. The flexibility provided by Sparrow allows for either on-premise operations or cloud-based inference.
Sparrow also comes with an API, turning your data into structured outputs that seamlessly integrate with custom workflows. Furthermore, users can develop independent LLM agents within the Sparrow ecosystem and utilize an API to invoke these agents as needed.
Sparrow Components
- sparrow-ml-llm: This is Sparrow’s engine, responsible for executing various agents.
- sparrow-data-parse: This library enables data parsing with the Sparrow Parse agent, utilizing vision-language models to output structured JSON responses.
- sparrow-data-ocr: Provides optical character recognition services to extract text from images or scanned documents.
- sparrow-ui: A user interface dashboard for managing and interacting with Sparrow.
Sparrow UI
Sparrow offers a demo application that allows users to see its capabilities in action. The interface provides a visual approach to managing data processing tasks and showcases Sparrow’s architecture and functionalities.
Practical Examples
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Bank Statement Processing: Sparrow can extract detailed information from bank statements. The output includes everything from bank names and account details to transaction histories and account summaries, all presented in a neat structured JSON format.
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Document Inference: Using Sparrow, one can extract detailed information from documents such as invoices or receipts, via inference calls using agents that support JSON response creation and data enrichment processes.
Quickstart Guide
Starting with Sparrow is straightforward:
- Begin by installing
pyenv, then set up Python in your environment. - Create a virtual environment for the specific Sparrow agent you plan to run.
- Install the necessary requirements.
- Run Sparrow from either the command line interface or via API by starting an API endpoint.
- Use JSON schemas to query and extract data from documents.
Installation and Usage
Running Sparrow can be done via CLI or API. To run locally, use the provided script from the relevant virtual environment. The sparrow-parse agent, for example, runs vision-language models and does not use Ollama.
Inference and API Integration
Sparrow supports LLM function calls and can perform complex data processing tasks directly through its CLI. Additionally, it offers a FastAPI endpoint to deploy and interact with Sparrow services locally. Users can specify plugins for inference, ensuring flexibility and efficiency in processing tasks.
Licensing and Commercial Use
Sparrow is released under the GPL 3.0 license, allowing broad freedom for use, modification, and distribution while ensuring any changes remain open source. It is free for commercial use by small to medium enterprises with less than $5 million in gross revenue over the past year. Beyond this, Sparrow offers dual licensing options, enabling its use under separate proprietary licenses suitable for businesses requiring more confidentiality or specific usage terms.
Contact and Support
For more information about proprietary licensing, custom workflows, or dedicated support, users can contact the team via email. Katana ML, led by Andrej Baranovskij, is committed to providing support and fostering the growth and sustainability of Sparrow in the open-source community.
Sparrow is a testament to the power of modular, open-source solutions, and stands ready to transform how users process and extract data across a wide array of applications.