17 lines
1.1 KiB
Markdown
17 lines
1.1 KiB
Markdown
# Product Context: PyNamer
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**Problem:** Manually naming large numbers of image files is tedious and time-consuming. Generic filenames (e.g., `IMG_1234.JPG`) lack descriptive value, making it hard to find specific images later.
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**Solution:** `pynamer` automates the process of generating descriptive filenames for images by leveraging the image understanding capabilities of multimodal LLMs.
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**User Experience:**
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- The user provides one or more image paths via the command line.
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- The tool processes each image, interacts with an LLM (configured via `config.yaml`), and renames the file with a descriptive, clean filename.
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- A dry-run option allows users to preview the changes without modifying files.
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- **Efficiency Enhancement:** By resizing large images before sending them to the LLM, the tool aims to:
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- Reduce the amount of data transferred.
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- Potentially lower API costs (as some models charge based on input size/tokens).
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- Speed up the processing time.
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**Target User:** Individuals or teams dealing with many images who need a better way to organize and retrieve them based on content (e.g., photographers, researchers, content creators).
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