Model: o4-mini
import fitz
doc = fitz.open("input.pdf")
for page in doc:
pix = page.get_pixmap(matrix=fitz.Matrix(300/72, 300/72))
jpeg_bytes = pix.tobytes(output="jpg", jpg_quality=30)c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4
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2445053ba6363fde66c9f27f4403aca25624f59051825bec34bed8ff7419463b
import os
import tempfile
import subprocess
import glob
from urllib.parse import urlparse, parse_qs
import llm
@llm.hookimpl
def register_fragment_loaders(register):
register("video-frames", video_frames_loader)
def video_frames_loader(argument: str):
"""
Fragment loader "video-frames:<path>?fps=N×tamps=1"
- extracts frames at `fps` per second (default 1)
- if `timestamps=1`, overlays "filename hh:mm:ss" at bottom-right
"""
# parse out path and query params
parts = urlparse(argument)
video_path = parts.path
params = parse_qs(parts.query)
fps = int(params.get("fps", ["1"])[0])
timestamps = params.get("timestamps", ["0"])[0] in ("1", "true", "True")
if not os.path.exists(video_path):
raise ValueError(f"Video file not found: {video_path}")
# prepare temp dir
out_dir = tempfile.mkdtemp(prefix="llm_video_frames_")
# base filename for overlay
base_name = os.path.basename(video_path)
# build ffmpeg filter
vf_parts = [f"fps={fps}"]
if timestamps:
# overlay filename and timestamp (hh:mm:ss) at bottom-right
timestamp_expr = r"%{pts\:hms}" # → %{pts\:hms}
text = f"{base_name} {timestamp_expr}" # → "items.mov %{pts\:hms}"
draw = (
"drawtext=fontcolor=white:fontsize=24:box=1:boxcolor=black@0.5"
f":text='{text}':x=w-tw-10:y=h-th-10"
)
vf_parts.append(draw)
vf = ",".join(vf_parts)
# output pattern
pattern = os.path.join(out_dir, "frame_%05d.jpg")
# run ffmpeg
cmd = ["ffmpeg", "-v", "error", "-i", video_path, "-vf", vf, "-q:v", "2", pattern]
try:
subprocess.run(cmd, check=True)
except subprocess.CalledProcessError as e:
raise RuntimeError(f"ffmpeg failed: {e}")
# collect frames
files = sorted(glob.glob(os.path.join(out_dir, "frame_*.jpg")))
attachments = [llm.Attachment(path=f) for f in files]
return attachments
2c6a2392e92d5240e2b8720f2ff681f9c925840590b610663cffc4ef5b24820f
[project]
name = "llm-video-frames"
version = "0.1"
description = "LLM plugin to turn a video into individual frames"
readme = "README.md"
authors = [{name = "Simon Willison"}]
license = "Apache-2.0"
classifiers = []
requires-python = ">=3.9"
dependencies = [
"llm>=0.25"
]
[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"
[project.urls]
Homepage = "https://github.com/simonw/llm-video-frames"
Changelog = "https://github.com/simonw/llm-video-frames/releases"
Issues = "https://github.com/simonw/llm-video-frames/issues"
CI = "https://github.com/simonw/llm-video-frames/actions"
[project.entry-points.llm]
video_frames = "llm_video_frames"
[project.optional-dependencies]
test = ["pytest"]
46b22c9ab6a17b50c3acda54238bbe7308515fceece990642165592d6ba1adb5
# llm-video-frames
[](https://pypi.org/project/llm-video-frames/)
[](https://github.com/simonw/llm-video-frames/releases)
[](https://github.com/simonw/llm-video-frames/actions/workflows/test.yml)
[](https://github.com/simonw/llm-video-frames/blob/main/LICENSE)
LLM plugin to turn a video into individual frames
## Installation
Install this plugin in the same environment as [LLM](https://llm.datasette.io/).
```bash
llm install llm-video-frames
```
Requires `ffmpeg` installed and available on the system `PATH`. On macOS, you can install it using Homebrew:
```bash
brew install ffmpeg
```
## Usage
The `llm-video-frames` plugin provides a [fragment loader](https://llm.datasette.io/en/stable/fragments.html#using-fragments-from-plugins) that extracts individual frames from a video file using `ffmpeg`.
You can use the `video-frames:` fragment prefix to turn a video into a series of image attachments.
### Fragment syntax
```
video-frames:<path>?fps=N×tamps=1
```
- `<path>`: Path to the video file accessible to the environment where LLM runs.
- `fps=N`: (optional) Number of frames per second to extract. Defaults to `1` if omitted.
- `timestamps=1`: (optional) If set to `1`, overlays the filename and timestamp on each extracted frame in the bottom-right corner.
### Examples
Extract 1 frame per second (default) from `video.mp4`:
```bash
llm -f video-frames:video.mp4 'describe the key scenes in this video'
```
Extract 5 frames per second:
```bash
llm -f 'video-frames:video.mp4?fps=5' 'summarize the video'
```
Extract 2 frames per second with filename and timestamps overlayed on frames:
```bash
llm -f 'video-frames:video.mp4?fps=2×tamps=1' 'list notable events with timestamps'
```
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
```bash
cd llm-video-frames
python -m venv venv
source venv/bin/activate
```
Now install the dependencies and test dependencies:
```bash
python -m pip install -e '.[test]'
```
To run the tests:
```bash
python -m pytest
```
98769434d2c6001edd8f9cd236d0a137c37732d0796873c1c759927addfdf7fd
.venv
__pycache__/
*.py[cod]
*$py.class
venv
.eggs
.pytest_cache
*.egg-info
.DS_Store
.vscode
dist
build
ac2cf940d4287308a1e426b8ae175d5a342b633596585b97c7533d4229769f92
import os
import shutil
import pytest
# adjust this import path to wherever your loader code actually lives
from llm_video_frames import video_frames_loader
# skip entire module if ffmpeg is not installed
ffmpeg_path = shutil.which("ffmpeg")
if not ffmpeg_path:
pytest.skip(
"ffmpeg not found on PATH, skipping video frame extraction tests",
allow_module_level=True,
)
@pytest.fixture
def video_file_path(tmp_path):
"""
Ensure there's a test.mp4 available. We expect a small 2-second mp4
sitting next to this test file at tests/test.mp4; if not found, we skip.
"""
here = os.path.dirname(__file__)
candidate = os.path.join(here, "test.mp4")
if not os.path.exists(candidate):
pytest.skip("test.mp4 not found in tests directory, skipping")
return candidate
def cleanup_attachments(attachments):
"""
Remove generated files and their parent temp directory.
"""
if not attachments:
return
# attachments are llm.Attachment objects with .path
out_dir = os.path.dirname(attachments[0].path)
shutil.rmtree(out_dir)
def test_missing_file_raises_value_error():
fake = "/path/does/not/exist.mp4"
with pytest.raises(ValueError) as exc:
video_frames_loader(fake)
assert "Video file not found" in str(exc.value)
def test_default_fps_produces_two_frames(video_file_path):
"""
Default is fps=1 on a 2-second video -> 2 frames
"""
arg = f"video-frames:{video_file_path}"
attachments = video_frames_loader(arg)
try:
paths = [a.path for a in attachments]
assert len(paths) == 2, f"expected 2 frames, got {len(paths)}"
for p in paths:
assert os.path.exists(p), f"frame file missing: {p}"
assert p.lower().endswith(".jpg")
finally:
cleanup_attachments(attachments)
@pytest.mark.parametrize(
"fps, expected_count",
[
(1, 2),
(2, 5),
],
)
def test_fps_parameter_changes_frame_count(video_file_path, fps, expected_count):
arg = f"video-frames:{video_file_path}?fps={fps}"
attachments = video_frames_loader(arg)
try:
paths = [a.path for a in attachments]
assert (
len(paths) == expected_count
), f"fps={fps} expected {expected_count} frames, got {len(paths)}"
finally:
cleanup_attachments(attachments)
def test_timestamps_overlay_does_not_change_count(video_file_path):
"""
Turning on timestamps should not change the number of frames, just overlay text.
"""
arg = f"video-frames:{video_file_path}?timestamps=1"
attachments = video_frames_loader(arg)
try:
paths = [a.path for a in attachments]
# still 2 frames at default fps=1
assert len(paths) == 2
# basic sanity: files exist and are non‐empty
for p in paths:
assert os.path.getsize(p) > 0
finally:
cleanup_attachments(attachments)
0a79b6614e205017c1e53a92ede4e2b6081e1065a14ef53670704274f114a3d2
name: Publish Python Package
on:
release:
types: [created]
permissions:
contents: read
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
- name: Install ffmpeg
run: |
sudo apt-get update
sudo apt-get install -y ffmpeg
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: Install dependencies
run: |
pip install -e '.[test]'
- name: Run tests
run: |
python -m pytest
deploy:
runs-on: ubuntu-latest
needs: [test]
environment: release
permissions:
id-token: write
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.13"
cache: pip
cache-dependency-path: pyproject.toml
- name: Install dependencies
run: |
pip install setuptools wheel build
- name: Build
run: |
python -m build
- name: Publish
uses: pypa/gh-action-pypi-publish@release/v1
2025683070b8ee66812d6584497b258fa3eb828087a2e22ee5ad5a8a15a658ce
name: Test
on: [push, pull_request]
permissions:
contents: read
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
- name: Install ffmpeg
run: |
sudo apt-get update
sudo apt-get install -y ffmpeg
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: Install dependencies
run: |
pip install -e '.[test]'
- name: Run tests
run: |
python -m pytest -vv
output llm_pdf_to_images.py which adds a pdf-to-images: fragment loader that converts a PDF to frames using fitz like in the example
# llm_pdf_to_images.py
import os
import tempfile
import fitz
import glob
from urllib.parse import urlparse, parse_qs
import llm
@llm.hookimpl
def register_fragment_loaders(register):
"""
Register the "pdf-to-images" fragment loader.
Usage: pdf-to-images:/path/to/file.pdf?dpi=300&format=jpg&quality=80
"""
register("pdf-to-images", pdf_to_images_loader)
def pdf_to_images_loader(argument: str):
"""
Fragment loader "pdf-to-images:<path>?dpi=N&format=jpg|png&quality=Q"
- dpi: render resolution (dots per inch), default 300
- format: "jpg" (default) or "png"
- quality: JPEG quality 1–100, default 80
"""
parts = urlparse(argument)
pdf_path = parts.path
params = parse_qs(parts.query)
# parse parameters
dpi = int(params.get("dpi", ["300"])[0])
img_format = params.get("format", ["jpg"])[0].lower()
quality = int(params.get("quality", ["80"])[0])
if not os.path.exists(pdf_path):
raise ValueError(f"PDF file not found: {pdf_path}")
# open PDF
doc = fitz.open(pdf_path)
# compute scale matrix
scale = dpi / 72.0
matrix = fitz.Matrix(scale, scale)
# prepare output directory
out_dir = tempfile.mkdtemp(prefix="llm_pdf_to_images_")
attachments = []
for page_number, page in enumerate(doc, start=1):
pix = page.get_pixmap(matrix=matrix)
if img_format in ("jpg", "jpeg"):
image_bytes = pix.tobytes(output="jpg", jpg_quality=quality)
ext = "jpg"
elif img_format == "png":
image_bytes = pix.tobytes(output="png")
ext = "png"
else:
raise ValueError(f"Unsupported image format: {img_format}")
out_name = f"page_{page_number:03d}.{ext}"
out_path = os.path.join(out_dir, out_name)
with open(out_path, "wb") as img_file:
img_file.write(image_bytes)
attachments.append(llm.Attachment(path=out_path))
return attachments5,056 input, 1,368 output, {"completion_tokens_details": {"reasoning_tokens": 832}}