Andrejus Baranovski
Oracle DB 23ai Free Connection Pool in Python
I describe how to connect to Oracle DB from Python. I explain why DB connection pool is important for better performance. Connection is done through thin oracledb mode, without installing Oracle Client.
Temporary Files Cleaner for Gradio Web App
Learn how to implement an automatic temporary file cleanup solution for Gradio web applications. This tutorial shows you how to prevent disk space issues by periodically removing old upload files and folders that Gradio leaves behind. Perfect for developers who deploy Gradio apps in production environments or run memory-intensive applications.
Building AI Agent for Local Structured JSON Output
I explain key steps of building AI agent to process document and extract structured JSON data locally. I'm running it with Sparrow and using Qwen VL model for vision processing backend and OCR. The steps are explained with Sparrow code walkthrough.
Querying Non Existing Fields with Qwen2.5 Vision LLM
I describe how Sparrow helps to query non existing fields with Qwen2.5 Vision LLM. Running it locally with MLX and MLX-VLM.
Structured Data Extraction with Sparrow Agent: Vision LLM & Prefect in Action
Discover how to streamline your data extraction process with Sparrow Agent! In this tutorial, I showcase how Sparrow Agent leverages Vision LLM to intelligently handle complex data tasks, while Prefect ensures every step is logged and monitored for maximum transparency and efficiency. Join me as I break down the process and share tips for optimizing your automated workflows.
Building Web UI Apps with Python Gradio – A Java Developer’s Perspective
I explain building Web UI apps with Python Gradio framework. I used to work with Java in the past and was building enterprise Web UI apps with JSF. Based on this experience I can tell, Gradio is awesome framework for server side generated UI - it is easy to define UI components and control UI flow with event triggers.
Improving Qwen-VL Structured Output with Image Cropping
Explaining how I'm improving structured output results from Qwen-VL with image cropping in Sparrow.
Apple MLX Vision LLM Server with Ngrok, FastAPI and Sparrow
I show how I run Apple MLX backend on my local Mac Mini M4 Pro 64GB and access it from the Web through Ngrok, with automatically provisioned HTTPS certificate.
Vision LLM Structured Output with Sparrow
I show how Sparrow UI Shell works with both image and PDF docs to process and extract structured data with Vision LLM (Qwen2) in the MLX backend.
Stateless MLX Inference with FastAPI in Sparrow
I show how to run inference with MLX in stateless mode, when loaded model is released after inference completes. This is useful when inference requests are less frequent and it helps to reclaim resources reserved by MLX.
Streamlined Table Data Extraction with Sparrow | Table Transformer, Qwen2 VL, MLX, & Mac Mini M4 Pro
Learn how to streamline table data extraction with Sparrow, Table Transformer, Qwen2 VL, and MLX on the Mac Mini M4 Pro. Simplify your workflow and get accurate results!
Structured Output from Multipage PDF with Sparrow (Qwen2 Vision LLM and MLX)
I explain how multipage PDFs are handled in Sparrow to extract structured data in a single call.
Sparrow Apple MLX Backend on Mac Mini M4 (Qwen2 72B 4bit)
I show how I’m running the Qwen2 72B 4bit model locally on a Mac Mini M4 for Sparrow’s backend. MLX (and MLX-VLM) is the main platform I’m using for local data extraction in Sparrow.
Batch Inference with Qwen2 Vision LLM (Sparrow)
I'm explaining several hints how to optimize Qwen2 Visual LLM performance for batch processing.
Visual LLM Structured Output Validation with Sparrow
I explain how Sparrow validates the structured output of visual LLMs to ensure it complies with the JSON schema provided in the query. This process helps prevent errors and hallucinations generated by the LLM.
Extracting Financial Market Stock Data from Images with Vision LLM
In this video, I demonstrate how to extract financial market stock data from images using the powerful Vision LLM Qwen2, all within a Gradio interface. This setup allows quick and easy extraction of key stock stats from screenshots and other image-based data sources—perfect for analysts, traders, and finance enthusiasts looking to streamline data processing. Watch to see how this AI tool can simplify your workflow and make stock data analysis faster and more efficient!
Structured Output Example with Sparrow UI Shell
Structured output is all you need. I deployed a Sparrow demo UI with Gradio to demonstrate the output Sparrow can produce by running a JSON schema query. You can see examples for the Bonds table, Lab results, and Bank statement.
Qwen2-VL Performance Boost
I share performance-boosting tips based on my experience using Qwen2-VL in production.
Sparrow Parse Vision LLM FastAPI Endpoint
Sparrow provides an API for accessing the Sparrow Parse agent, allowing you to run document extraction workflows directly from your existing systems. It helps simplify how data is pulled from documents and integrated into your workflows.
Sparrow Parse Invoice Query with Vision LLM
New Sparrow Agent - Sparrow Parse, works with Qwen2 Vision LLM.
What it does:
1. Accepts query with JSON schema, this helps to solve few things at once - provides JSON structure for LLM to generate response, and hints LLM what types to use for each response element
2. Runs inference on your GPU of choice, either cloud or local GPU
3. Validates JSON response, based on query schema