>"A practical comparison between rule-based PDF extraction using pytesseract and an LLM-based approach with Ollama and LLaMA 3, based on a realistic B2B order scenario."
- Regex approach excels with stable, standardized layouts.
- Regex offers speed, low cost, and deterministic results but requires high maintenance as document variety increases.
- LLM approach (using LLaMA 3 via Ollama) leverages semantic context to handle diverse field names and formats automatically.
- LLM approach reduces manual rule updates.
- Trade-offs: LLMs provide superior flexibility for complex layouts but incur higher latency, greater infrastructure costs, and probabilistic uncertainty compared to traditional methods.
- Selection depends on document stability, required throughput, and need for explainability.
- Regex approach excels with stable, standardized layouts.
- Regex offers speed, low cost, and deterministic results but requires high maintenance as document variety increases.
- LLM approach (using LLaMA 3 via Ollama) leverages semantic context to handle diverse field names and formats automatically.
- LLM approach reduces manual rule updates.
- Trade-offs: LLMs provide superior flexibility for complex layouts but incur higher latency, greater infrastructure costs, and probabilistic uncertainty compared to traditional methods.
- Selection depends on document stability, required throughput, and need for explainability.
