Model: openai/o4-mini
-- none --
c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4
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76b5b21267fdc0d6ee512ab67bc99b323574c71bcd3a1eb55a3fed9d16d48c54
import llm
import html
import httpx
import json
import re
from typing import Dict, List, Any
@llm.hookimpl
def register_fragment_loaders(register):
register("hn", hacker_news_loader)
def hacker_news_loader(argument: str) -> llm.Fragment:
try:
response = httpx.get(f"https://hn.algolia.com/api/v1/items/{argument}")
response.raise_for_status()
data = response.json()
except Exception as ex:
raise ValueError(f"Could not load Hacker News {argument}: {str(ex)}")
return llm.Fragment(
process_hn_comments(data),
source=f"https://news.ycombinator.com/item?id={argument}",
)
def convert_hn_to_thread_path(
json_data: Dict[str, Any], path: str = "", result: List[str] = None
) -> List[str]:
"""
Convert Hacker News JSON hierarchy to thread path notation.
Args:
json_data: The JSON data from HN API
path: Current thread path (used in recursion)
result: Accumulator for formatted comments
Returns:
List of formatted comments in thread path notation
"""
if result is None:
result = []
# Handle root node
if not path:
# Root node needs special handling as it might not be in the standard format
if "text" in json_data: # It's a comment
comment_text = clean_html_content(json_data.get("text", ""))
result.append(f"[1] {json_data.get('author', 'Anonymous')}: {comment_text}")
current_path = "1"
else: # It's a story or top-level item
title = json_data.get("title", "")
result.append(f"[1] {json_data.get('author', 'Anonymous')}: {title}")
current_path = "1"
else:
current_path = path
# Process children recursively
if "children" in json_data and json_data["children"]:
for i, child in enumerate(json_data["children"], 1):
child_path = f"{current_path}.{i}" if current_path else f"{i}"
# Handle the comment text, unescape HTML entities and clean HTML
comment_text = clean_html_content(child.get("text", ""))
result.append(
f"[{child_path}] {child.get('author', 'Anonymous')}: {comment_text}"
)
# Process this child's children
convert_hn_to_thread_path(child, child_path, result)
return result
def clean_html_content(text: str) -> str:
"""
Clean HTML content by unescaping entities and removing HTML tags.
Args:
text: HTML text to clean
Returns:
Cleaned text
"""
if not text:
return ""
# First unescape HTML entities
text = html.unescape(text)
# Replace paragraph tags with newlines
text = text.replace("<p>", "\n").replace("</p>", "")
# Remove link tags but keep the link text
text = re.sub(r"<a\s+href=[^>]*>(.*?)</a>", r"\1", text)
# Remove all other HTML tags
text = re.sub(r"<[^>]*>", "", text)
return text
def process_hn_comments(json_str: str) -> str:
"""
Process the JSON string from HN API and return thread path notation.
Args:
json_str: JSON string from HN API
Returns:
Formatted string with thread path notation
"""
try:
json_data = json.loads(json_str) if isinstance(json_str, str) else json_str
formatted_comments = convert_hn_to_thread_path(json_data)
return "\n\n".join(formatted_comments)
except Exception as e:
return f"Error processing JSON: {str(e)}"
cb0b0b1aae76cbe7f7ba5644f3f54f62bd4322b233cab628c95adf4c01481fbe
[project]
name = "llm-hacker-news"
version = "0.1"
description = "LLM plugin for pulling content from Hacker News"
readme = "README.md"
authors = [{name = "Simon Willison"}]
license = "Apache-2.0"
classifiers = []
requires-python = ">=3.9"
dependencies = [
"llm>=0.24"
]
[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"
[project.urls]
Homepage = "https://github.com/simonw/llm-hacker-news"
Changelog = "https://github.com/simonw/llm-hacker-news/releases"
Issues = "https://github.com/simonw/llm-hacker-news/issues"
CI = "https://github.com/simonw/llm-hacker-news/actions"
[project.entry-points.llm]
hacker_news = "llm_hacker_news"
[project.optional-dependencies]
test = ["pytest", "pytest-httpx"]
49255a891b377ccaba61a01026c98680de5f83d38795593d3658ffa91bc1280f
# llm-hacker-news
LLM plugin for pulling content from Hacker News
For background on how this works:
- Long context support in LLM 0.24 using fragments and template plugins
- Blog post announcing llm-hacker-news
Install this plugin in the same environment as LLM.
llm install llm-hacker-newsYou can feed a full conversation thread from Hacker News into LLM using the hn: fragment with the ID of the conversation. For example:
llm -f hn:43615912 'summary with illustrative direct quotes'Item IDs can be found in the URL of the conversation thread.
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-hacker-news
python -m venv venv
source venv/bin/activateNow install the dependencies and test dependencies:
pip install -e '.[test]'To run the tests:
python -m pytest98769434d2c6001edd8f9cd236d0a137c37732d0796873c1c759927addfdf7fd
.venv
__pycache__/
*.py[cod]
*$py.class
venv
.eggs
.pytest_cache
*.egg-info
.DS_Store
.vscode
dist
build
fd9ae3faccb5bb2227ef436c186a560df2b04809bfa1273ed1278920560a130b
import llm
from llm_hacker_news import hacker_news_loader
def test_hacker_news_loader(httpx_mock):
httpx_mock.add_response(json=EXAMPLE)
fragment = hacker_news_loader("123456")
assert isinstance(fragment, llm.Fragment)
assert fragment.source == "https://news.ycombinator.com/item?id=123456"
assert str(fragment) == (
'[1] BeakMaster: Fish Spotting Techniques\n\n'
'[1.1] CoastalFlyer: The dive technique works best when hunting in shallow waters.\n\n'
'[1.1.1] PouchBill: Agreed. Have you tried the hover method near the pier?\n\n'
'[1.1.2] WingSpan22: My bill gets too wet with that approach.\n\n'
'[1.1.2.1] CoastalFlyer: Try tilting at a 40° angle like our Australian cousins.\n\n'
'[1.2] BrownFeathers: Anyone spotted those "silver fish" near the rocks?\n\n'
'[1.2.1] GulfGlider: Yes! They\'re best caught at dawn.\nJust remember: swoop > grab > lift'
)
EXAMPLE = {
"author": "BeakMaster",
"title": "Fish Spotting Techniques",
"children": [
{
"author": "CoastalFlyer",
"text": "The dive technique works best when hunting in shallow waters.",
"children": [
{
"author": "PouchBill",
"text": "Agreed. Have you tried the hover method near the pier?",
"children": [],
},
{
"author": "WingSpan22",
"text": "My bill gets too wet with that approach.",
"children": [
{
"author": "CoastalFlyer",
"text": "Try tilting at a 40° angle like our Australian cousins.",
"children": [],
}
],
},
],
},
{
"author": "BrownFeathers",
"text": "Anyone spotted those "silver fish" near the rocks?",
"children": [
{
"author": "GulfGlider",
"text": "Yes! They're best caught at dawn.<p>Just remember: <code>swoop > grab > lift</code>",
"children": [],
}
],
},
],
}
fd7da2a5c82824ad71ed3e70e6f72082e37c860bdafec56be8a95c39142c108f
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: 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
1a564a200569424b8ef1276a16daa3d1697dc5d615adc85a9f51a18cd453020c
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: 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
write a new plugin called llm_video_frames.py which takes video:path-to-video.mp4 and creates a temporary directory which it then populates with one frame per second of that video using ffmpeg - then it returns a list of [llm.Attachment(path="path-to-frame1.jpg"), ...] - it should also support passing video:video.mp4?fps=2 to increase to two frames per second, and if you pass ?timestamps=1 or ×tamps=1 then it should add a text timestamp to the bottom right conner of each image with the mm:ss timestamp of that frame (or hh:mm:ss if more than one hour in) and the filename of the video without the path as well.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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", video_frame_loader)
def video_frame_loader(argument: str):
"""
Fragment loader "video:<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
# %% escapes to a single % in ffmpeg expression
text = f"{base_name} %%{{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 attachmentsExplanation:
• We register a fragment loader under the prefix “video”.
• The loader parses the argument as a URL to extract the path, fps (default 1), and a boolean timestamps flag.
• We create a temporary output directory with tempfile.mkdtemp().
• We build an ffmpeg “-vf” filter string: first fps=N, then, if requested, a DrawText filter that overlays filename hh:mm:ss in the bottom-right corner.
• We invoke ffmpeg to output JPEG frames (-q:v 2 for good quality) named frame_00001.jpg, etc.
• Finally we glob the output directory, wrap each frame in llm.Attachment, and return the list.
5,018 input, 2,208 output, {"output_tokens_details": {"reasoning_tokens": 1408}}
llm -m openai/o4-mini -f github:simonw/llm-hacker-news -s 'write a new plugin called llm_video_frames.py which takes video:path-to-video.mp4 and creates a temporary directory which it then populates with one frame per second of that video using ffmpeg - then it returns a list of [llm.Attachment(path="path-to-frame1.jpg"), ...] - it should also support passing video:video.mp4?fps=2 to increase to two frames per second, and if you pass ?timestamps=1 or ×tamps=1 then it should add a text timestamp to the bottom right conner of each image with the mm:ss timestamp of that frame (or hh:mm:ss if more than one hour in) and the filename of the video without the path as well.' -o reasoning_effort high