Building Multimodal Workflows with a Local LLM

A step-by-step build of a multimodal LLM workflow using Gemma 4 (E4B variant) running locally via Ollama, combined with Pydantic for structured output. The workflow analyzes travel photos, extracting structured records (scene summary, mood, objects, uncertainty notes) from images plus metadata, then synthesizes those records into a trip-level narrative summary. It also covers a practical compatibility fix: on Windows with Ollama 0.32.5, gemma4:e4b failed to process image inputs correctly, requiring a workaround using Unsloth's split GGUF files (quantized model plus multimodal projector) imported via a custom Modelfile. The workflow is extended into a small travel-memory app with photo timelines, maps, and search, with full code shared in a GitHub repo.

Source: https://towardsdatascience.com/building-multimodal-workflows-with-a-local-llm. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.