LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
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Updated
Jun 2, 2026 - Python
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
Turn Chaos Into Structure. A Type-Safe AI Agent that extracts valid JSON from unstructured data using PydanticAI, FastHTML, and Gemini 2.5.
Universal prompt library for structured outputs & ready-to-use content. Teachers get lesson plans, developers get reliable JSON/CSV. Works across GPT-4, Claude, Gemini.
Fine-tune Qwen3-0.6B for resume parsing using LoRA
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Structured JSON extraction from LLMs with validation, repair, and streaming.
Fine-tuned Qwen2.5-7B on Fireworks AI for structured JSON extraction from job postings. LoRA SFT + DPO | FastAPI | +47% over baseline.
Turn handwritten forms, notes, and scanned paperwork into automation-ready JSON
Production-style fine-tuning project for schema-constrained JSON extraction using QLoRA + DPO, with reproducible evals, training curves, and vLLM benchmarks.
A Json Analysis Tool
Professional-grade AI logistics pipeline built with Java 17 and Spring Boot 3. Converts unstructured documents into validated JSON via non-blocking WebClient adapters (Groq/Llama 3.1). Features real-time dashboard, Slack/Email notifications, and secure error handling."
Document ingestion and chunking agent that extracts and validates typed JSON against a strict schema.
Fine-tuning Qwen2-VL on Apple Silicon (MLX) for structured JSON document extraction.
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