clip-interrogator
Generate a prompt from an image
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
Generates natural-language prompts from images by combining CLIP and BLIP models to reverse-engineer what text would recreate a given image.
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
pip
pip install clip-interrogatoruv
uv add clip-interrogatorpoetry
poetry add clip-interrogatorInstalling clip-interrogator
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.
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))
Requires torch with GPU support (or CPU fallback); on low-VRAM systems, call config.apply_low_vram_defaults() to reduce memory use.
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 — torch, torchvision, Pillow, requests, safetensors, tqdm, open-clip-torch, accelerate, transformers |
| 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) |
Evidence: clip_interrogator-0.6.0-py3-none-any.whl
Keywords: blip, clip, prompt-engineering, stable-diffusion, text-to-image
Tags
More Scientific/Engineering packages
NumPy provides an N-dimensional array object…
permissive · top 100 on PyPI
pandaspandas provides fast, flexible data structures…
permissive · top 100 on PyPI
scipyscipy provides numerical algorithms for…
permissive · top 100 on PyPI
scikit-learnscikit-learn provides a comprehensive Python…
permissive · top 1,000 on PyPI
dilldill extends Python's pickle module to…
permissive · top 1,000 on PyPI
multiprocessMultiprocess is an enhanced fork of Python's…
permissive · top 1,000 on PyPI
dynamicpromptsGenerates varied text prompts for image…
permissive · top 15,000 on PyPI
open-clip-torchOpenCLIP provides open-source implementations…
permissive · top 5,000 on PyPI
diffusersDiffusers provides pretrained diffusion models…
permissive · top 5,000 on PyPI
clip-benchmarkEvaluates CLIP-like vision-language models on…
permissive · top 15,000 on PyPI
compelCompel lets you re-weight different parts of…
permissive · top 15,000 on PyPI
clip-anytorchLoads and runs OpenAI's CLIP model to encode…
unclear · top 15,000 on PyPI
transparent-backgroundRemoves backgrounds from images and videos…
permissive · top 15,000 on PyPI
chatterbox-ttsChatterbox TTS converts text to speech using…
permissive · top 15,000 on PyPI
click-promptclick-prompt adds interactive prompts to Click…
permissive · top 15,000 on PyPI