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Convert Any Document to LLM Knowledge with Docling and Ollama - 100% Local PDF to Markdown Pipeline

Venelin Valkov via YouTube

Overview

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Learn to build a local document ingestion pipeline that converts PDFs into structured Markdown while preserving tables and generating image descriptions using Docling and Ollama. Discover how to overcome common RAG pipeline failures caused by poor PDF processing that destroys document structure and ignores visual elements. Build a complete solution that transforms complex financial reports into semantic Markdown format, maintaining table structures and leveraging Vision Language Models to describe charts and images. Explore the pipeline architecture from PDF input to Markdown output, understand why Docling excels at document conversion, and implement a VLM pipeline using Ollama for local processing. Set up the document converter, configure the vision language model pipeline, and run the complete extraction process to see how tables and chart descriptions are preserved in the final output. Test the results by chatting with the processed data to verify the quality of the conversion and the effectiveness of the local RAG pipeline implementation.

Syllabus

The "Garbage In" problem
Pipeline architecture PDF to Markdown
Why Docling?
Building the document converter
Setting up the VLM pipeline Ollama
Running the extraction
Results - tables & chart descriptions
Chatting with the data
Conclusion

Taught by

Venelin Valkov

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