clip-interrogator
Generate a prompt from an image
Decision gist · record as of 2026-08-14
Yes, if you need to generate prompts from images and can tolerate dormant maintenance. The package is stable with no known vulnerabilities, but expect no updates or bug fixes. Install only if you're comfortable pinning versions and managing torch dependencies yourself, and if the last release from 2023-03-20 meets your needs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires torch with GPU support (or CPU fallback); on low-VRAM systems, call config.apply_low_vram_defaults() to reduce memory use.
- Low friction to install, but requires torch and torchvision as runtime dependencies, which are large downloads.
- Maintenance is dormant—last release was 2023-03-20 and no commits since 2024-05-15, so expect no active support or updates.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use this package freely in commercial and private projects with minimal restrictions.
last release 2023-03-20 (1243 days) · last repo commit 2024-05-15 · 2,979 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 289,175 downloads/mo, #8,004 on PyPI
Alternatives
Verify before relying
pip install clip-interrogator
from clip_interrogator import Config, Interrogator
ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
print(ci.interrogate(image))- Whether the package works with recent torch versions or if version pinning is needed
- Current state of precomputed embeddings cache and whether downloads still work
- Performance and accuracy changes between version 0.5.5 (in docs) and current 0.6.0
- Exact VRAM requirements and whether 6.3GB and 2.7GB figures remain accurate
What it is and what it does
CLIP Interrogator is a prompt engineering tool that analyzes an image and generates a natural-language text prompt describing it, optimized to work with text-to-image models. It combines CLIP and BLIP to understand image content and produce prompts that, when fed back into a generative model, would recreate similar images.
The package is designed primarily as a library for Python scripts. It requires torch, torchvision, transformers, accelerate, open-clip-torch, and several other dependencies. Configuration options let you trade speed and quality for memory usage, and you can rank custom term lists against images. However, the project is dormant—no releases since 2023-03-20 and no recent commits—so it receives no active maintenance or updates.
Use it for
- Generate prompts from reference images to create similar artwork without manual prompt writing.
- Analyze existing images to understand what visual features a model should prioritize.
- Build custom image-to-prompt pipelines by ranking domain-specific term lists against images.
- Reverse-engineer prompts from generated images to understand model behavior or reproduce styles.
- Batch process image collections to extract descriptive prompts for metadata or tagging.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to generate prompts from images and can tolerate dormant maintenance.
The package is stable with no known vulnerabilities, but expect no updates or bug fixes. Install only if you're comfortable pinning versions and managing torch dependencies yourself, and if the last release from 2023-03-20 meets your needs.
Install
clip-interrogator on PyPI
Before you install
Low friction to install, but requires torch and torchvision as runtime dependencies, which are large downloads. Maintenance is dormant—last release was 2023-03-20 and no commits since 2024-05-15, so expect no active support or updates.
Requires torch with GPU support (or CPU fallback); on low-VRAM systems, call config.apply_low_vram_defaults() to reduce memory use.
License in practice
MIT license is permissive; you can use this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install clip-interrogator
from clip_interrogator import Config, Interrogator
ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
print(ci.interrogate(image))Verify before relying
- Whether the package works with recent torch versions or if version pinning is needed
- Current state of precomputed embeddings cache and whether downloads still work
- Performance and accuracy changes between version 0.5.5 (in docs) and current 0.6.0
- Exact VRAM requirements and whether 6.3GB and 2.7GB figures remain accurate
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagestorchtorchvisionPillowrequestssafetensorstqdmopen-clip-torchacceleratetransformers |
| Maintenance | Dormant 1,243 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 289,175 / month, #8,004 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseTopic :: EducationTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: clip_interrogator-0.6.0-py3-none-any.whl
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See also dynamicprompts · open-clip-torch · diffusers · clip-benchmark · compel · clip-anytorch · transparent-background · chatterbox-tts · click-prompt