Local LLM pipeline parses bank SMS for privacy-conscious users

A developer has created a local LLM pipeline to parse bank notifications, prioritizing data privacy by keeping sensitive financial information on their personal device. The system utilizes Ollama with a small, locally run model (like Qwen2.5-3B) for efficient processing of short Vietnamese bank SMS messages. This approach combines JSON Schema structured output from the LLM with Pydantic validation and a regex fallback for robust and reliable data extraction, suitable for managing personal finances without third-party cloud services. AI

IMPACT Enables privacy-focused personal finance management by leveraging small, local LLMs for data extraction.

RANK_REASON Developer shares a practical guide for using local LLMs with specific tools for a common task.

Read on dev.to — LLM tag →

• gemma3:4b
• Llama3.2 3B
• llama.cpp
• MacBook M1
• Ollama
• OpenAI
• pydantic
• Qwen2.5-3B
• SQLite
• Techcombank
• Vietcombank

• product
• infra

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