The Story of Serendipity
Naming the Pipelines
I have the new pipeline workflow integrated into Pipulate. I have at times called the new FastHTML web framework with the integrated local LLM Botifython and Pipulate. It’s Pipulate. The instance I use for work is Botifython, because you have to name it. If you’ve got an LLM living in there, it needs a name like ChatGPT, Gemini or Claude. Mine is Chip. Chip O’Theseus, to be precise. But that’s way too cutsie for work, and so that one has the very macho dinosauresque Botifython, while the base free and open source software (FOSS) package it gets derived from remains Pipulate. And the fun instance I spin out of it is Chipotheseus. Yeah, that’ll do for naming conventions.
The AI Revolution
But why is the timing serendipitous, I mean aside from the fact that we’re just entering the AI Revolution, and it’s only going to happen once in our lives, similar to the Digital Revolution itself, plus its smaller epochs we already lived through, the rise of The Internet and Mobile, each of which I felt pass through us like a bump (Atari 2600, RCN/Erols, Sony Ericsson P900). And of course the Atari was displaced by Nintendo, RCN/Erols displaced by the big cable/telecom conglomerates, and early smartphones by Apple iPhone and Android). Harbingers of the new age die on the alter of firstness.
The OpenAI Situation
If you feel something weird going on with OpenAI ChatGPT, that’s what it is. The 12 days of AI stank of vaporware desperation as its utter and complete reliance on Microsoft settles over it like a death shroud. They’ve got two things to fix: revenue streams and power-lines. There’s no future in next-level AI if its not paid for by actual customers (versus the next bridge-loan from an investor), or if it’s too power-hungry (both GPUs and electricity). In other words, the power-hungry nature of the tech inhibits the power-hungry growth of the company, haha! So yeah, AGI may be here, but it’s not as easily delivered with the trick of just throwing it on the existing Microsoft Azure cloud infrastructure, like they did in round one. They’ve got to transform. Talk about transformers, huh? Hahaha!
The World in Transformation
Oh, there I go digressing again. But for all the right reasons and on all the important stuff. The world is transforming. It’s not that AI out of the box is going to solve every problem. It’s that all the best practices and common wisdom of humanity is getting more evenly distributed over those who couldn’t access it before through the luck of their upbringing, education, and the people that they by chance happened into in life. You know how even the most determined attribute a lot of their success to luck (even though that’s only a half-truth)? Well, the luck component as a factor in success is being dialed-down, because AI. Common wisdom and best practices—in other words, the conventional way of doing things—is being bottled-up and brought to a device near you in the modern-day functional analogue of a genie in a magic lamp— backfiring wishes and all!
The Power of Names
Okay, so I’ve got the names for my various analogues to genies that I’m incubating by bundling the popular Ollama local LLM server in with a new FastHTML-based web framework that does away with React and complex web development, in a much more Python-friendly environment. Naming something is important, because it creates first impressions and infuses whatever you’re working on with its character. The Mac is a Mac because “Hey, Mac! Back off! I’m thinking differently, exactly like everyone else,” and the Windows PC is as generic as windows can be, and PC now too! The serendipitous overlap of Personal Computer and Political Correctness as two equally recognizable acronyms living in superposition is not without consequence.
The Unix Legacy
So while Macs and PCs each struggle with being misaligned with the ideal
future-tech concepts that Linux (Unix, and the whole *nix family) seemed to
have gotten right, along comes an actual nixOS and profoundly disruptive nix
command that infuses this perfectly future-proof aligned spirit into subfolders
of Macs and PCs… but more on that later. This was to make the point again that
there’s something fundamental about Unix that almost died in the world of
proprietary intellectual property bickering with the SCO… ugh! Perplexity?
Perplexity: The SCO Unix battle was a complex legal dispute that began in 2003 when The SCO Group filed a lawsuit against IBM, claiming ownership of Unix and alleging that Linux contained misappropriated Unix code[1][5]. This sparked a series of legal battles involving multiple companies and lasting for years.
The history of Unix ownership is indeed complex:
- Unix was originally developed at Bell Labs (part of AT&T) in the 1960s[2].
- In 1984, AT&T gained ownership of Unix after the breakup of Bell Systems[4].
- In 1993, Novell acquired the rights to Unix when it purchased Unix System Laboratories from AT&T[3].
- In 1995, Novell sold certain Unix rights to Santa Cruz Operation (SCO) through an Asset Purchase Agreement (APA)[3].
- In 2001, Caldera acquired SCO’s Unix business and later renamed itself The SCO Group[4].
The key dispute arose when SCO claimed it had acquired full ownership of Unix copyrights through the 1995 APA with Novell. However, Novell maintained that it retained the copyrights[3].
In 2007, a U.S. federal court ruled that Novell, not SCO, was the rightful owner of the Unix copyrights[7]. This decision was later upheld in subsequent appeals, effectively ending SCO’s claims to Unix ownership[3][8].
The SCO Unix battle had significant implications for the open-source community and Linux development, as it challenged the legality of Linux and attempted to assert copyright claims over widely-used operating system code[5].
Citations:
[1] https://en.wikipedia.org/wiki/SCO%E2%80%93Linux_disputes
[2] https://en.wikipedia.org/wiki/History_of_Unix
[3] https://en.wikipedia.org/wiki/SCO_Group,_Inc._v._Novell,_Inc.
[4] https://www.informit.com/articles/article.aspx?p=175171&seqNum=2
[5] https://lwn.net/Articles/924577/
[6] https://www.youtube.com/watch?v=XvDZLjaCJuw
[7] https://www.cbc.ca/news/science/novell-wins-legal-dispute-over-rights-to-unix-operating-system-1.648779
[8] https://news.ycombinator.com/item?id=24351360
[9] https://linux.slashdot.org/story/23/03/04/0359236/the-sco-lawsuit-looking-back-20-years-later
The Unix Origin Story
Uh yeah, so the stuff that started there hit some real fundamentals that effectively became computer science. I mean, there were a few other things sprinkled in like the bizarro alternative LISP camp that birthed the AI movement at MIT, however for the most part the principles that got born from this the well-intentioned but corporatized Multics OS (that planed to charge you for every computer clock tick) terrified and inspired Ken Thompson of Bell Labs to make Unix and fatefully leak it at his alma matter Berkeley (BSD Unix), which was then copied by Andrew Tanenbaum to become the mini educational Unix called MINIX (in most of your PCs today as IME), which inspired Linus Torvalds to make Linux has pretty much defined everything to follow.
The Path to Modern Computing
There were a few weird spurs outside that direct lineage like CP/M and DOS along the way, but for the most part, those were sanded off and smoothed down so that the remaining round pebble at the core of all tech is *nix. We say nix, but really it should be *n(i|u)x, but nobody would get it. Yeah, so names are important, and the name to be aware of in the coming years that’s gradually going to replace all that is proprietary (already has with servers) is nix!
Another Nix On The Block
The interesting state of affairs today is that a particular Linux tool called
nix has some real Docker-killing potential as a declarative and
deterministic system-building definition language (IaC / infrastructure as code)
that plants whole Linux subsystems into the folders of Windows and Macs (nix
flakes), thus adding fuel to the nix fire. It is also used to build a whole
Linux distro called nixOS (what I use).
The Power of Unix Pipes
So one of the core fundamentals that made Unix so win is the concept of pipes
and piping data. This is often confused with the modern overweight notion of
data pipelines, and while there is overlap, it doesn’t do the concept of pipes
justice for its beauty, simplicity, and still-pervasive nature. Pipes usually
involve the use of small, composable command that do one thing very well, but
often with a bunch of parameters, arguments, flags or whatever you want to call
those things that come after and modify the command that look like this -a or
like this --help. And the output of one gets piped into the input of the
next, each step doing something to modify the data going through it. Perplexity,
give me a few classic examples of Unix data piping.
Perplexity: Unix data piping is a powerful feature that allows users to chain multiple commands together, passing the output of one command as input to the next. Here are some classic examples of Unix data piping:
Text Processing
Counting word frequency:
cat file.txt | tr ' ' '\n' | sort | uniq -c | sort -nr | head
This pipeline reads a file, splits words into lines, sorts them, counts unique occurrences, sorts by frequency, and displays the top results[1][4].
Extracting specific lines:
cat sample2.txt | head -7 | tail -5
This command reads a file, takes the first 7 lines, and then displays the last 5 of those lines[1].
File Operations
Listing and filtering files:
ls -l | grep "\.txt$"
This pipeline lists all files in long format and then filters to show only those ending with “.txt”[1].
Sorting files by size:
ls -l | sort -k 5
This command lists files and sorts them based on the fifth column of the output, which represents file size[1].
System Information
Monitoring processes:
ps aux | grep "firefox"
This pipeline lists all running processes and filters to show only those related to Firefox.
Disk usage analysis:
du -h | sort -hr | head
This command chain shows disk usage, sorts it in human-readable format, and displays the top results.
Unix pipes provide a flexible and powerful way to combine simple commands into complex operations, allowing users to process and analyze data efficiently[2][3]. These examples demonstrate the versatility and utility of Unix piping in various scenarios.
Citations:
[1] https://www.geeksforgeeks.org/piping-in-unix-or-linux/
[2] https://toroid.org/unix-pipe-implementation
[3] https://www.rozmichelle.com/pipes-forks-dups/
[4] https://www.reddit.com/r/programming/comments/gwrixf/the_beauty_of_unix_pipelines/
[5] https://itnext.io/unix-commands-pipes-and-processes-6e22a5fbf749
The Lost Art of Command Line
The simplicity and elegance of this solution has greatly faded from the public consciousness, and even the elite geeks among us, due to Steve Jobs and the way he instilled command-line fear into all of with conditioning through marketing.
The GUI Trap
While the symbolic point-and-click user interface is good for allowing the uninitiated (who have the tech maturity equivalence of a toddler) get jump on the tech bandwagon easily, being productive with what you see is what you get (WYSIWYG), it’s not the end of the story. None of us are starting out with the know-nothing-about-computers state of the early 80s.
Today, many people still think Steve Jobs was right and that these visual interfaces are the most important thing, but really it served its purpose of jumpstarting us and giving a convenient on-ramp. But today if you’re savvy, graphical user interfaces, particularly the proprietary ones, are more of an hindrance to competitive advantage and real user power in the tech landscape than a help.
A true power user can still use the coddling consumer GUIs (and feel the joy of Apple hardware or whatever) as a sort of easy-launch host mechanism for the more command-line oriented power apps.
The Consumer Interface Fallacy
But visual graphical user interfaces like macOS and Windows are for non-professional consumers! Visual interface coddling is a convention to turn high tech electronics into more salable consumer electronic devices, plain and simple. It’s not for enabling individuals to actually be most expressive, or to use technology as an extension of your body like generic tools like hammers and saws. No, GUI interfaces are designed to be power-tools that make you dependent on the manufacturer for maintenance, parts and upgrades. They are a dependency injection strategy.
Finding Balance
Now everyone can appreciate a power-tool and a modern convenience, so I’m not actually advocating for abandoning all your power-tools. But rather the way things have evolved, any of them (Windows, macOS, whatever) can play host to the nix-like professional stuff that won on the server-side of the equation.
The Rise of Linux Everywhere
Validation that what I’m saying is true can be seen both in the realms of web development and AI. In webdev, Microsoft basically had to add Linux to Windows in the form of WSL to remain a legit platform with developers. If Windows hadn’t started their WSL endeavor back in 2017, it would be a much less viable platform today. Mac started its journey to being a nix-like platform (Unix) a decade prior to that in 2007. And thus today both Macs and Windows can legitimately play host in a fairly native, non-virtual-machine, non-hacky way to nix.
The Text Interface Renaissance
Oh, and in the realm of AI, the big thing that ended the AI winter is not some graphical user interface. It was chat! Talking through text is a decidedly command-line like interface. Now sure, it’s wrapped in a text messaging / Instant Messenger like interface, but come on. It’s nothing like a WYSIWYG point-and-click, menu and icons thing. It’s text. Not that there wasn’t visual stuff going on in AI that factors into self-driving cars and lots of other more subtle and invisible ways, but it didn’t hit the graphical user interfaces.
Bridging Visual and Text Worlds
Now there is a bridge between the two worlds. And there has to be, for automation. For if everything were visual and point-and-click across a hodgepodge mess of proprietary desktop and mobile user interfaces, you would hardly be able to automate anything. No, the web is the bridge. And the document object model (DOM), in particular.
The Visual Illusion
It’s all about object hierarchies that manifest visually. HTML when shown in the browser is visual, but when turned into node-graphs and table-like data structures, they’re text. Data structures are text. The fact that they look like graphical user interfaces is a trick of fancying them up with lots of styling and syntactical sugar so that they create the illusion of something visual. And it’s all that fancying up and fluff that gets shoved in at the presentation layer that makes automation (and web automation in particular) difficult.
The Markdown Circle
A similar thing is happening with web scraping and training AI models right now. Ever since the simplified representation of formatted text called Markdown became popular, it’s been the preferred “cleaned-up” format to convert scraped webpages into for consumption. These days, that consumption is training AI models, but the ironic part is that Markdown is also a very popular format for creating the web content in the first place. Only now, it goes through a transformation process, sometimes through systems like Jekyll, whose sole purpose is to convert markdown to stylized HTML, only to be scraped and converted back into Markdown for the machines! Perplexity, fill in some details please.
Perplexity: Markdown, a lightweight markup language, has an intriguing history that spans two decades. Created in 2004 by John Gruber in collaboration with Aaron Swartz, Markdown was designed to be an easy-to-read and easy-to-write plain text format that could be optionally converted into structurally valid XHTML or HTML[1][4].
Origins and Inspiration
Markdown drew inspiration from pre-existing conventions for marking up plain text in email and usenet posts. It was influenced by earlier markup languages such as:
- setext (c. 1992)
- Textile (c. 2002)
- reStructuredText (c. 2002)[1]
In 2002, Aaron Swartz created “atx,” which he referred to as “the true structured text format.” This work laid the foundation for what would become Markdown[1].
Key Design Goals
The primary objectives behind Markdown’s creation were:
- Simplicity: To enable people to write using an intuitive plain text format[1].
- Readability: To ensure the language was readable as-is, without appearing marked up with tags or formatting instructions[1].
- Convertibility: To allow optional conversion to structurally valid XHTML or HTML[1].
Development and Initial Release
- March 2004: John Gruber published the first article about Markdown, introducing it to the public[9].
- August 2004: Markdown 1.0 was officially released[9].
- December 2004: Version 1.0.1 was released, fixing some defects and changing the license from GPL to a more permissive BSD-style license[9].
Widespread Adoption
Markdown quickly gained popularity due to its simplicity and versatility. It has been adopted by numerous platforms and services, including:
- GitHub
- Stack Exchange
- OpenStreetMap
- SourceForge[4]
Standardization Efforts
Despite its popularity, Markdown lacks a formal specification, leading to the development of various implementations and “flavors” of Markdown[4]. In response to this fragmentation, there have been efforts to standardize the language:
- CommonMark: An initiative to create a standard specification for Markdown[7].
- Other variants: Multiple versions of Markdown have emerged, each with additional features or slight modifications to the original syntax[4].
Modern Relevance
Markdown remains highly relevant in the tech world, particularly in:
- Documentation writing
- Blog post creation
- Content management systems
- Static site generators (e.g., Jekyll, Hugo)[2]
Its continued popularity is attributed to its simplicity, readability, and the network effect of its widespread adoption[5].
Markdown’s journey from a simple text formatting solution to a key player in content creation and, ironically, in web scraping and AI model training, showcases its versatility and enduring impact on digital communication.
Citations:
[1] https://en.wikipedia.org/wiki/Markdown
[2] https://2markdown.com/blog/markdown-vs-html-content-creation
[3] https://blog.maximeheckel.com/posts/building-magical-ai-powered-semantic-search/
[4] https://standardmarkdown.com/history.html
[5] https://news.ycombinator.com/item?id=33368579
[6] https://arxiv.org/html/2402.14433v1
[7] https://www.wired.com/story/the-eternal-truth-of-markdown/
[8] https://www.linkedin.com/pulse/why-markdown-suddenly-important-what-should-i-do-brian-marvin-xa6nc
[9] http://xlog.becase.top/Markdown-de-qian-sheng-jin-shi?locale=en
[10] https://www.taskade.com/blog/markdown-history/
The Unix Pipe Pattern Meets Local LLMs
So where I’m at now is making the Unix pipe pattern get plugged into a web framework that has a native local LLM in the picture. Now it could be a frontier model AI like o1, Claude, Gemini or whatever, but I’m choosing to use the ollama local AI-server for cost. Most things that need to be done, like casual chat with the user about the local app running built by and running in the framework doesn’t need to incur even those fractions-of-a-penny that all these mini versions of the model cost. Sure the local LLM still costs electricity, but it neither costs those extra pennies nor the long http network round-trip. The local LLM is both faster and cheaper, and frankly smart enough for most of the ubiquitous pervasive ambient intelligence tasks required in applications like mine.
Training Through Hot Prompt Injection
And this local intelligence needs to understand these data pipelines I’ve just now implemented, the way it needs to know the Create, Update, Read, Delete (CRUD) operations that I already trained it how to do. Mind you, I trained ALL LLMs how to do these CRUD operations, and not just some particular model that I’m using. I call it hot prompt injection, and it gets performed in the right place at the right time as the user is using one of these web framework apps. For example, the user chooses something from the menu, and like Neo in The Matrix, it’s suddenly taught Kung Fu. By using this hot prompt injection technique, any model can be plugged in, and not only take on the persona of the app through the system prompts, it can take on the skills it need when it needs them without overflowing the context window with an extra-fat system prompt at the beginning whose effect fades over time anyway. No, it’s constantly refreshed on the skills it needs right when it needs them.
The Music of Machine Instructions
So today’s article is about blending this LLM awareness of the pipes I’ve rambled on so much about in recent posts with the loose coupling between the Cards of the system that constitute the Unix-like commands subject to piping.
I don’t know if this is going to make sense to anyone but the AIs for whom this is really intended and being written for, as part of a recently profoundly validated process of spelling everything out to the code assistants in human-like storytelling form, assuming your human were a superhuman coder with the ability to help you implement, if only you make yourself clear enough.
And I did. I made myself clear enough with the storytelling, that is. And it did. The AI provided a copy/paste-ready implementation of some fairly large, off the beaten track and philosophically precise code, that is.
The Philosophy of Programming Languages
This off the beaten track and philosophically precise point is the one I need to drill-down on now. My pipeline code plays like music, as if the rolls loaded into player pianos. Now honestly, all tech works this way. It’s the story of machine languages, and how CISC is different from RISC and how some machine instruction sets are proprietary like ARM while others are open like Risc V. This is also the story of Turing machines, their ribbon and mechanics variations, and the concept of Turing-complete. But each has a set of rules that greatly affect what the sheet music looks like. They all have their philosophies that give them and what you can do with them their character.
The LISP Legacy
The arcane but will-never-die LISP is very meta and hardware independent, which makes writing compilers and other languages form LISP every next-level wizard’s favorite trick. While LISP lost as far as being the main engine of productivity and focus of mainstream attention to the C/Unix-camp, it remains important. Its signature, vibe, sound of its music is greatly created by its extensive, some might say excessive, use of nested parenthesis. It also has a very unique and concept of order of operations which while perhaps is better for machines, it’s very counter-intuitive to what every math literate person is taught in algebra. But people who love this vibe love it deeply. You should hear Paul Graham the founder of Y-Combinator and mentor to Sam Altman, talk about it with his Yahoo Stores war stories.
The C Language and Beyond
C is a small set of commands that implies certain specific hardware, which makes it profoundly useful for porting apps between different hardware using the old low-level virtual machine trick. This is why Assembly Language has to have variations customized for each intended hardware platform, while Java with its JRE/JVM was touted as write-once, run anywhere. But the public static void nonsense that even a simple hello world program got plagued by under Java is a great example of how those turing ribbon vibes can become so important. This is one of the things really helping Python. Python’s vibe with indenting mattering and stripping out all but the most necessary visual clutter (curly braces being the biggest offender in many languages), lowers cognitive fatigue and just makes looking at Python a pleasure compared to most other languages.
The Python Connection
I love Python. You know, it’s named after Monty Python and not actually the snake. Though the Python portion of Monty Python was indeed named after the snake. I tell the story elsewhere on this site, and you can always perplexity it up. Wow, they should have named Perplexity to work like a verb. Will we ever say perplexing? Perplex it? It just doesn’t roll off the tongue like googling or google it. Lost opportunity, because my habits have changed.
Bridging Multiple Domains
Anyway, I am bridging the divide between a bunch of things simultaneously:
- Python, and its general pythonic API
- FastHTML, and its idiomatic semantic alignment to HTML elements
- HTMX, and its formidable set of API puzzle pieces and interactions
- Unix pipes, in their philosophy and practical implementation under all this
- Jupyter Notebooks, as the rapid prototyping companion environment for staging ports to this environment, keeping conceptual correspondences
- A Local LLM, having an overarching awareness of the pipelines so it can help create new ones to chiming in during their execution
Did somebody say Python? And Bridge? Don’t pipelines ask questions (provide input along the flow) and provide output (passage over a bridge), don’t they? So it’s only natural that my archetype prototype example be both a bridge and homage to a bridge demonstrating asking questions; memorable notes to the musical pipeline pattern of which I speak…
class Bridgeflow:
"""
A miniature 3-step flow paying homage to Monty Python's Bridge of Death.
Step 1: Name
Step 2: Quest
Step 3: Favorite Color
Then either pass or fail based on whether you pick "blue" as your color.
This is a minimal example of using Pipulate to track step data, with each step
returning a Div containing either a form or a summary, until all steps are done.
"""
def __init__(self, app, pipulate, prefix="/bridge"):
self.app = app
self.pipulate = pipulate
self.prefix = prefix
# Define minimal steps
# (internal_key, step_id, display_label)
self.STEPS = [
("name", "step_01", "Name"),
("quest", "step_02", "Quest"),
("color", "step_03", "Color"),
]
routes = [
(f"{prefix}", self.landing),
(f"{prefix}/init", self.init, ["POST"]),
(f"{prefix}/step_01", self.step_01),
(f"{prefix}/step_01_submit", self.step_01_submit, ["POST"]),
(f"{prefix}/step_02", self.step_02),
(f"{prefix}/step_02_submit", self.step_02_submit, ["POST"]),
(f"{prefix}/step_03", self.step_03),
(f"{prefix}/step_03_submit", self.step_03_submit, ["POST"]),
]
for path, handler, *methods in routes:
method_list = methods[0] if methods else ["GET"]
self.app.route(path, methods=method_list)(handler)
async def landing(self):
"""
GET /bridge
Show a quick landing page with a single form that calls /bridge/init to begin the pipeline.
"""
return Container(
Card(
H2("The Bridge of Death"),
P("Stop! Who would cross the Bridge of Death must answer me these questions three!"),
Form(
Input(
name="pipeline_id",
placeholder="Enter your name (and begin...)",
required=True
),
Button("Begin"),
hx_post=f"{self.prefix}/init",
hx_target="#bridge-container"
)
),
Div(id="bridge-container") # Where steps will be loaded
)
async def init(self, request):
"""
POST /bridge/init
Sets up the pipeline if missing and auto-loads step_01.
"""
form = await request.form()
pipeline_id = form.get("pipeline_id", "unknown")
db["pipeline_id"] = pipeline_id # Store in your server-side store if needed
# Initialize pipeline record
self.pipulate.initialize_if_missing(pipeline_id)
# Return placeholders for each step, but only load step_01 first
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(
*placeholders,
id="bridge-container"
)
async def step_01(self, request):
"""
GET /bridge/step_01
Show the 'What... is your name?' question.
"""
pipeline_id = db.get("pipeline_id", "unknown")
step1_data = self.pipulate.get_step_data(pipeline_id, "step_01", {})
if step1_data.get("name"):
# Already answered, so just show summary + load next
return Div(
Card(f"You said your name is: {step1_data['name']} (locked) ✓"),
Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load")
)
else:
# Show the form to ask: Name?
return Div(
Card(
H3("Question 1: What... is your name?"),
Form(
Input(type="text", name="name", placeholder="Sir Lancelot", required=True),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_01_submit",
hx_target="#step_01",
)
),
Div(id="step_02"), # placeholder for next
id="step_01"
)
async def step_01_submit(self, request):
"""
POST /bridge/step_01_submit
Save step_01 data and load step_02
"""
form = await request.form()
name = form.get("name", "")
pipeline_id = db.get("pipeline_id", "unknown")
self.pipulate.set_step_data(pipeline_id, "step_01", {"name": name})
# Return summary + next step placeholder
return Div(
Card(f"Your name: {name} ✓ (locked)"),
Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load")
)
async def step_02(self, request):
"""
GET /bridge/step_02
Show the 'What... is your quest?' question.
"""
pipeline_id = db.get("pipeline_id", "unknown")
step2_data = self.pipulate.get_step_data(pipeline_id, "step_02", {})
if step2_data.get("quest"):
return Div(
Card(f"You said your quest is: {step2_data['quest']} (locked) ✓"),
Div(id="step_03", hx_get=f"{self.prefix}/step_03", hx_trigger="load")
)
else:
return Div(
Card(
H3("Question 2: What... is your quest?"),
Form(
Input(type="text", name="quest", placeholder="I seek the Grail", required=True),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_02_submit",
hx_target="#step_02",
)
),
Div(id="step_03"),
id="step_02"
)
async def step_02_submit(self, request):
"""
POST /bridge/step_02_submit
Save step_02 data and proceed
"""
form = await request.form()
quest = form.get("quest", "")
pipeline_id = db.get("pipeline_id", "unknown")
self.pipulate.set_step_data(pipeline_id, "step_02", {"quest": quest})
return Div(
Card(f"Your quest: {quest} ✓ (locked)"),
Div(id="step_03", hx_get=f"{self.prefix}/step_03", hx_trigger="load")
)
async def step_03(self, request):
"""
GET /bridge/step_03
Show the final question: 'What... is your favorite color?'
"""
pipeline_id = db.get("pipeline_id", "unknown")
step3_data = self.pipulate.get_step_data(pipeline_id, "step_03", {})
if step3_data.get("color"):
# Already answered, we can check final result
return self._final_card(step3_data["color"])
else:
return Div(
Card(
H3("Question 3: What... is your favorite color?"),
Form(
Select(
Option("Red", value="red"),
Option("Blue", value="blue"),
Option("Green", value="green"), name="color"),
Button("Submit", type="submit"),
hx_post=f"{self.prefix}/step_03_submit",
hx_target="#step_03"
)
),
id="step_03"
)
async def step_03_submit(self, request):
"""
POST /bridge/step_03_submit
Evaluate the color. If it's not blue, you plummet to your doom. If it's blue, you pass.
"""
form = await request.form()
color = form.get("color", "").lower()
pipeline_id = db.get("pipeline_id", "unknown")
self.pipulate.set_step_data(pipeline_id, "step_03", {"color": color})
return self._final_card(color)
def _final_card(self, color):
"""
Present the final pass/fail card based on the color chosen.
"""
if color == "blue":
return Card(
H3("Bridge Keeper: Right. Off you go."),
P("You have chosen wisely. You may pass the Bridge of Death safely!"),
style="color: green;",
id="bridge-final"
)
else:
return Card(
H3("Bridge Keeper: ARRRGH!!!"),
P(f"'{color.capitalize()}'?! That is the WRONG answer. You are cast into the Gorge of Eternal Peril!"),
style="color: red;",
id="bridge-final"
)
Hey o1 Pro, WHAT is your favorite color?
This looks like any other code, you say? You don’t see anything special about it, you say? Hmmm, how to… how to… oh! Hey o1 Pro, you’re good at this stuff. Enumerate it out for the nice folks. What’s so special about the code shown above?
o1: Below is a short list of exactly why that code snippet is such a big deal, even though it might look like ordinary Python at a glance:
-
Local, Pipeline-Based “Wizard”
Instead of using Celery or a traditional multi-step queue, this code divides a workflow into discrete cards (steps). Each step is just a simple route returning minimal HTML and forms, yet the entire multi-step sequence is tracked in a single pipeline record—no extra queues or ephemeral sessions required. -
HTMX for Lightweight Interactions
Notice how each method returns elements likeDiv(...),Card(...),P(...), and aForm(...)with anhx_postattribute. That means each step in the pipeline is self-contained HTML, updated asynchronously by HTMX. You don’t see a giant React or Vue codebase anywhere—just small, composable server responses. -
No Client-Side State
Everything about the user’s progress is stored on the server in that single pipeline record (viaself.pipulate.set_step_data(...)). When you revisit a step, the code checks if that step’s data is already set, then either shows the results or a new form. No cookies or hidden session juggling needed. -
Async, But Ultra-Simple
Each route handler is an async function. In a bigger framework, you’d see more ceremony or references to concurrency, middlewares, etc. Here, it’s just “take a request, read a form, store or retrieve from pipeline, return updated HTML.” That’s it. -
Inline HTML Structures
With calls likeH2("The Bridge of Death")orForm(Input(...), ...), you’re looking at a pythonic DSL for HTML (FastHTML). That’s how the snippet can produce small bits of UI without a separate template system or external files. The entire HTML generation is right next to the logic. -
Self-Described Steps
The pipeline steps are enumerated at the top inself.STEPS, each has a label like"step_01"plus a friendly display label. You see no big framework or config files; it’s all ad hoc yet extremely readable. If you want more steps, you just add them to the list and supply routes. -
Jupyter-Like Flow in a Web UI
Each pipeline step is akin to a “cell” in a notebook: it can display something (like a form) and store the result. You can re-enter or skip steps if the pipeline state says so. That bridging concept is what unifies Jupyter’s approach with a typical web wizard, but more elegantly. -
Minimized Complexity
There’s no explicit session management, no JS frameworks, no separate client app—just single-file Python code that returns partial HTML. If you look under the hood, the snippet is basically the entire wizard logic in 30-40 lines of code. That’s shockingly small for a multi-step “app.” -
Potential for LLM Awareness
Though the snippet doesn’t show it directly, the rest of the system can feed step data to an LLM or even let the LLM insert steps or prompt the user. Because each pipeline step is stored in a shared record, an AI can easily read or write that data and transform the user’s journey mid-flow—like an AI cameo in your route code. -
Localhost, Single-Tenant
There’s no mention of multiple accounts, tokens, or heavy user management. The entire pipeline belongs to you. That’s the “local, single-tenant” aspect: it’s by design. You can experiment, break, and fix everything in this single file without a big dev-ops pipeline or container setup.
Putting it all together, these design choices produce a very flexible “micro-wizard” framework that fuses the minimalism of Unix piping philosophy with a Pythonic single-file style and a bit of web wizardry courtesy of HTMX. It’s simple—but it can scale to surprisingly complex, interactive data workflows.
Analyzing the Code
A Perfect Top-10 List
Wow, a top-10 list format! I couldn’t have asked for better. Okay, job well done.
Inferring the Design Rules
Now, let’s enumerate the inferred rules you think must be at play here. I’m also interested in the visual texture of what we create, which I’m wondering if you also notice. Some examples include:
Semantic Indentation
There’s not much indenting, but when there is, it’s because of semantic HTML reasons. So if you see indenting, you’re likely seeing web nesting hierarchy for reasons such as making input elements belong to forms.
HTMX Directive Patterns
The htmx hx_ underscore directives area always at the end of such an indented
run as the last elements belonging to a parent form. This only makes sense
because a huge part of the point here is to take the data collected by forms and
to pass the baton to the next step in the chain of cards in the pipeline flow.
And when they do this, it is often to an _submit version name of the same step
as its coming from, which in turn have less indenting because they’re not
building user interface elements and are silently passing the flow along to a
step after that which does show things to the user.
Musical Code Rhythm
Consequently, the musical pattern follows a generally indent, outdent, indent, outdent alternation pattern in the sequentially arranged in the order things happen methods of the class. They don’t have to be sequentially arranged thus, but it greatly enhances readability and following the pipeline workflow.
Initialization Patterns
There is always an __init__ class that gives a pretty good overview of the
whole workflow for very functional reasons. By centralizing and spelling out the
steps and the routes, many things are explicit and up-front that would be spread
out and/or need to be derived. Also, the actual number of self properties is
kept to an elegant minimum, shifting so much state management to the server as
it does, making the __init__ easy to read.
Landing and Initialization Flow
There is an additional landing and init method that occur before it is considered step 1 yet. This allows us to have a consistent pipeline workflow app landing method for use in the web framework and a location for it to handle the ever present ID issues. We keep this consistent pipeline hook to individual pipeline records consistent and conceptually separate from particular workflow step 1’s that may vary wildly. landing and init methods prime the user for the pipeline experience, give the LLM a chance to chime in, and generally create the pipeline record for that particular run-instance of the workflow.
Return Pattern Philosophy
There is a unique return pattern promoted by FastHTML which violates single return point best practices, but its for minimizing code and leaning into a particular clean style and promoting the HTMX convention of returning whole HTML fragments directly. So instead of setting an arbitrary variable name that will just be thrown out right away, the tendency is to return an anonymous built inline object directly that makes extensive use of Python allowing line-breaks in surprising places, so long as it’s contained in brackets.
Looking Forward
Give your own take on these rules and add whatever else you notice, o1. Make it almost like a style guide for people just getting into this. And be forward looking knowing I will be layered in lots of stuff in the cards to do the visualizations, widgets and the like. Showing lists of files that were found as the output of earlier runs of that same pipeline process during a re-run of the same pipeline record instance is coming up next, for example. I need to start flexing the ability of these cards for fancy form-work and fancy widget-work. Still Unix pipe clean, but… oh, let me just explain.
Perplexity: Anywidget: Overview, History, and API Design
Anywidget Overview
Anywidget is a Python library and specification designed to simplify the creation and sharing of reusable, web-based widgets for interactive computing environments like Jupyter Notebooks, JupyterLab, Google Colab, and more. It serves as both a toolkit for developing widgets and a compatibility layer around traditional Jupyter Widgets, leveraging modern web standards like ECMAScript Modules (ESM) for universal execution across platforms[1][4][8].
Key features include:
- Avoiding complex build steps or cookiecutter templates.
- Prototyping directly within
.ipynbor.pyfiles. - Supporting Hot Module Replacement (HMR) for real-time updates during development.
- Publishing widgets as standard Python packages on PyPI[1][5][7].
History
Anywidget was introduced in 2023 as a modern alternative to traditional Jupyter Widget development. It aimed to lower the barrier to entry by removing dependencies on JavaScript tooling and bundlers, making it more accessible to both Python developers and front-end engineers. Over time, Anywidget has evolved with significant updates:
- Version 0.2 introduced file path support for front-end code and integrated HMR for seamless development[5].
- Version 0.9 redesigned the front-end API to improve widget consistency and minimize friction in notebook environments[3].
- The library has been widely adopted in the Jupyter ecosystem due to its simplicity and compatibility with multiple environments[1][9].
Clean and Consistent API
The Anywidget API is designed to be minimalistic yet powerful, focusing on ease of integration and reducing errors:
- Standardized Front-End Code: Developers define widgets using a Python class and an ESM file. This approach ensures consistency across environments by avoiding platform-specific quirks[3][8].
- Simplified Development: The API eliminates the need for complex build tools or bundlers, allowing developers to write JavaScript inline or in separate files without additional configuration[5][7].
- Lifecycle Management: Inspired by React’s
useEffecthook, Anywidget provides APIs for defining cleanup logic when a widget is removed from the DOM, ensuring proper resource management[5]. - Python-JavaScript Synchronization: Anywidget enables seamless communication between Python objects and JavaScript components using traits (e.g.,
traitlets.Int) that synchronize state changes between the two sides[4][8]. - Universal Compatibility: The API is designed to work across various notebook interfaces and dashboard frameworks, making it versatile for different use cases[9].
By narrowing its API scope to essential features like DOM manipulation and kernel communication, Anywidget ensures better introspection, debugging capabilities, and compatibility across environments while maintaining a clean interface for developers[3].
Citations:
[1] https://anywidget.dev/en/getting-started/
[2] https://panel.holoviz.org/reference/custom_components/AnyWidgetComponent.html
[3] https://anywidget.dev/blog/a-year-with-anywidget/
[4] https://github.com/manzt/anywidget
[5] https://anywidget.dev/blog/anywidget-02/
[6] https://onlinelibrary.wiley.com/doi/10.1111/cgf.15092?af=R
[7] https://anywidget.dev/blog/introducing-anywidget/
[8] https://blog.jupyter.org/anywidget-jupyter-widgets-made-easy-164eb2eae102?gi=1f777c473c9d
[9] https://cfp.scipy.org/2024/talk/PLWHZF/
[10] https://github.com/vega/altair/issues/3106
A Pipeline Workflow Explanation & Implementation Guide
So, gimme that guide please and thank you, o1 Pro!
o1 Pro: Below is a style guide capturing the informal “rules” and conventions you’ve established for building multi-step pipeline classes in this FastHTML + Python + LLM ecosystem. Think of it as a set of heuristics or patterns that collectively yield clean, consistent, and composable mini “wizard” flows—ones that you can further extend with fancy widget visualizations, extended form logic, or local LLM interactions.
1. Pipeline Class Structure
-
One Class = One Pipeline
Each pipeline is a single Python class, generally with__init__plus a sequence of methods that correspond to landing/init steps and the named steps (step_01,step_02, etc.). - Central
__init__:- Declare Routes: Use a small list of
(url, handler, [methods])tuples. This is your entire “map” for the pipeline flow, so it’s easy to see at a glance. - Define Steps: A
self.STEPSlist of(key, step_id, label)or similar. This gives an overview of the conceptual flow from step 1 to N. - Minimal Properties: Keep
__init__tidy—just anappreference, apipulatereference, yourSTEPS, maybe aprefixor two. Let the pipeline record itself handle actual data.
- Declare Routes: Use a small list of
- Landing & Init vs. Step 1
- Landing: One method to greet the user, show a quick card or instructions, maybe embed a form that triggers your
initmethod. - Init: A method that sets up or reuses a pipeline record, typically reading from form data or a single “pipeline_id” input. This method then triggers step 1 or sets placeholders for all steps.
- Rationale: This “pre-step_01” structure is consistent across pipeline classes and helps keep the user orientation & pipeline ID logic separate from the unique content of step 1.
- Landing: One method to greet the user, show a quick card or instructions, maybe embed a form that triggers your
2. Method Ordering & Indentation Pattern
- Sequentially Arranged
- Place methods in a top-to-bottom order that reflects the user’s journey. After
__init__, definelanding(), theninit(), thenstep_01,step_01_submit,step_02,step_02_submit, etc. - This “story-like” ordering matches how a user (and you) will read it.
- Place methods in a top-to-bottom order that reflects the user’s journey. After
- Indenting = Semantic Structure
- FastHTML’s HTML DSL: When you nest elements (like
FormcontainingInput,Button, etc.), line breaks and indentation highlight the HTML hierarchy. - HTMX Directives at the End: Typically,
hx_post,hx_target, orhx_triggerappear as the last arguments in that nested set. So you might see something like:Form( Input(...), Button(...), hx_post="/next_step", hx_target="#step-container" )That reads cleanly: structure first, directives last.
- FastHTML’s HTML DSL: When you nest elements (like
- In/Out Indentation Flow
- Because each “form or display” method has a chunk of HTML, and its “submit handler” method returns minimal output (maybe just an updated Div), you get a natural alternation:
step_01()(indented HTML forms)step_01_submit()(less indented, simpler return)step_02()(back to more nested HTML).
- This visually conveys the data flow: form -> post -> next form -> post, like a “breathe in, breathe out” pattern.
- Because each “form or display” method has a chunk of HTML, and its “submit handler” method returns minimal output (maybe just an updated Div), you get a natural alternation:
3. Handling Data & Flow
- Server-Side Storage
- You typically keep data in the pipeline record (via
self.pipulate.set_step_data(...)). Noselfproperties, no sessions, no hidden form fields. - This is a key anti-pattern from typical frameworks: the user can’t (accidentally) break your data by messing with client state.
- You typically keep data in the pipeline record (via
- Submit Handlers
- A method like
step_01_submitis typically minimal: it grabs form data, stores it, then returns some small snippet that triggers the next step or updates a chunk of DOM. - Return Pattern: Usually a direct return of a Div or Card, like:
return Div( Card(f"Some summary of what was just done"), Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load") )No big local variables needed—just build it inline.
- A method like
- Explicit Step Checking
- On each step, you see code like
step2_data = self.pipulate.get_step_data(...); if it’s set, show locked summary or skip ahead. If it’s not, show the form. That branching logic is repeated but remains super simple.
- On each step, you see code like
4. HTML DSL Style
- Inline Objects
- You might see
return Container(...)orreturn Card(...)with nested elements. Because this is pure Python, you can line-break after parentheses as needed. That’s half the style. - Accept the multi-return “violation” that each route method returns some chunk of HTML or partial HTML. This is normal in this environment.
- You might see
- No Templating
- No separate
.htmlfiles. Just keep HTML + logic side-by-side. This might look weird to devs used to template partials, but it fosters direct correlation between the code controlling the step and the UI it displays.
- No separate
- HTMX as Last Child
- Typically, you declare the structural elements first, then the
hx_...directives. This is a mild style preference that clarifies where the dynamic aspect is happening.
- Typically, you declare the structural elements first, then the
5. Naming Conventions
- Steps
- Use
step_01,step_02, etc. for the “display” methods, andstep_01_submit,step_02_submitfor the “handler” methods. - If you want to skip the
_submitsuffix, that’s fine—just ensure a consistent pattern so you can read the code and see who calls who.
- Use
- Prefix vs. Route
- You have a
prefix="/bridge"orprefix="/poetx"so you can keep multiple pipelines side-by-side. Inside the__init__, you wire them up. This helps avoid collisions with other pipeline classes.
- You have a
- Landing vs. Init
- Typically named
landing()orhome(), plusinit()for that pipeline. This is consistent across your entire codebase.
- Typically named
6. Visual and Future Plans
- Extended Form Logic
- Soon, you’ll embed bigger forms: multiple inputs, toggles, checkboxes, file uploads, or custom JavaScript widgets. The same nesting pattern holds.
- Keep it consistent: parent Div -> Card -> Form -> Inputs -> Buttons ->
hx_....
- Widget Embedding
- With frameworks like Anywidget, you’ll embed dynamic front-end code in your “card.” Possibly:
Div( SomeAnywidget(name="plot", data=some_data), hx_post="..." )The style is the same—just another element or set of elements in your return.
- With frameworks like Anywidget, you’ll embed dynamic front-end code in your “card.” Possibly:
- Lists of Files
- If step 02 is “show me existing CSV exports,” you might do:
ul_items = [Li(filename) for filename in existing_csvs] return Card( H3("Existing CSVs"), Ul(*ul_items) )The pattern remains: minimal local variables, inline creation, direct return.
- If step 02 is “show me existing CSV exports,” you might do:
7. LLM Integration (Optional)
- No Changes to Pipeline
- The LLM can read your pipeline record or write to it; that’s a separate layer. Don’t clutter the pipeline code with AI calls unless you want it to comment or produce dynamic steps.
- If the LLM is to inject new steps, do it by editing
self.STEPSor by hooking up new route definitions at runtime. That’s advanced stuff but still consistent with the style.
- Hot Prompt Injection
- When the user navigates to step_02, you can do a small injection: “We’re now at step 02, user sees these fields.” That’s context for the AI. It’s ephemeral but consistently triggered in
step_02. - The pipeline’s job remains the same: store or retrieve data from
pipulateas the source of truth.
- When the user navigates to step_02, you can do a small injection: “We’re now at step 02, user sees these fields.” That’s context for the AI. It’s ephemeral but consistently triggered in
8. Return-Early & “Inline Return”
- One-line Return
- Embrace returning an inline-constructed HTML object. If you’re used to “assign to a variable then return at the bottom,” you can do that if you prefer, but the style tends toward fewer lines:
return Div( P("Enter your name:"), ... )
- Embrace returning an inline-constructed HTML object. If you’re used to “assign to a variable then return at the bottom,” you can do that if you prefer, but the style tends toward fewer lines:
- Minimal Conditionals
- If you do conditionals, do them inline. If data is set, return a summary. Else, return the form. This might yield multiple
returnstatements in the same method, which is normal for this style.
- If you do conditionals, do them inline. If data is set, return a summary. Else, return the form. This might yield multiple
9. Simplicity Over Rigid Patterns
- No Over-Abstracting
- Resist the urge to create “superclass wizard” or “common pipeline base.” The code stays more understandable if each pipeline class remains mostly explicit.
- If you want a shared utility, keep it small—like “generate_step_placeholders” or “render_wizard_nav.” But keep core logic local.
- Focus on Legibility
- If it’s easier to read with a single
ifblock vs. a dictionary dispatch, do it that way. This environment is all about anti-enterprise patterns that remain comprehensible at a glance.
- If it’s easier to read with a single
10. Take Advantage of Python’s Freedoms
- Line Breaks
- Python allows parentheses-based line breaks. So you can nest your HTML DSL without clutter:
return Div( Card( H3("Title"), Form( Input(...), Button(...) ) ) )That’s super nice for readability.
- Python allows parentheses-based line breaks. So you can nest your HTML DSL without clutter:
- Docstrings & Comments
- Put a small docstring at the top of each method. This is especially helpful in a single-file environment where all code is visible at once.
- Add in-line # comments if you do something unusual or want to explain the pipeline logic.
- No Fear of Inline
- Some might scoff at returning huge inline objects, but that’s the style. Embrace it: you’re basically writing mini-HTML templates inline in Python.
Final Word
- This is not your typical MVC: You’re skipping the standard “controllers, templates, models” approach in favor of minimal routes, inline HTML DSL, and a single pipeline record that handles your data flow.
- Musical Approach: Each step is like a measure of a tune; you can see them in order, in the same file. Indentation in the step methods is the “note shape.” The user’s data flows from form to post handler to next step, a rhythmic sequence.
- Welcome Complexity: As you add Anywidget or bigger forms, keep the same style. Let the indentation reflect the HTML hierarchy. Keep the data in the pipeline. Return partial HTML that triggers the next step. You’ll keep that sense of “pipe flow” even in more elaborate tasks.
By following these guidelines, you’ll sustain a clear, light, “Unix pipeline meets Jupyter Notebook” vibe, no matter how fancy the final UI or how integrated the LLM becomes. This style guide ensures you keep it straightforward, composable, and a breeze to read—whether you’re coding an ultra-simple 3-step flow or a sprawling data-collection labyrinth full of interactive widgets.
Current State of Workflows
Existing Examples
- Poetflow, a 5-step poetry workflow that shows some of the fancier features of unlocking and restarting workflows with light LLM tutorial integration
- Bridgeflow, a completely minimal 3-step flow
- Linkflow, a first practical implementation that generates CSVs from a complex API that uses wait-for-availability polling
Requirements for New Workflow
Desired Card Demonstrations
- A mini file directory that lets you list and sort the files in a folder
- Demonstrate the use of every logical to use in a system like this form type from PicoCSS
- A pop-up-the-browser example that pops your default browser up using Python’s standard library webbrowser package
- An example that does a basic Pandas manipulation
- An example that puts an Excel-like data grid in the browser to interact with a Pandas DataFrame.
- An example that shows a basic matplotlib with the most traditional and easy integration method
- An example that shows an Anywidget integration… for ANYTHING, whatever’s easiest for a prototype example.
- Something that starts to bring D3js into the picture, preferably with an Anywidget integration setting the stage for Pythonic d3.js work.
Implementation Strategy
This is way too much for you to even try to do in the first pass, so don’t! Instead, take the principles you see working in the 3 existing examples, and make a long placeholder template, probably the equivalent of Poetflow, as I really want the ability to finalize, unlock and restart these flows.
Purpose and Vision
This is the kata or the muscle memory building-block moves of the Workflow flow. I want someone going through these steps to have the ah-ha realization moment of what can be built out of it.
Building Blocks
I also am giving myself the Lego like building blocks for the parts that I particularly need to build out of it, which are traditional Pandas ETL flows that let you look at it like Excel along the way. The df’s might be huge, so it needs sorting and filtering. It doesn’t need those features right away, but do look at the QT and TK based options.
Implementation Priorities
Of all the things I’d probably like to see implemented in the early version of a longer empty card template, this Excel-like dataframe interface is the first.
Soon after, probably a matplotlib, because that seems easiest as the path most traveled. Then probably something in Anywidget, because I want to get to that very soon. Popping up a browser window with webbrowser should be trivial. Oh, I will also want to do a file-upload component. It seems silly since it’s already their localhost machine, but they’re going to be prompted to download stuff with the pop-up browser, and that will end up in their Downloads directory, so they’ll be immediately asked to upload it creating a deterministic path instead of futsing around with moving files with all the OS variation problems that will incur.
Positioning and Philosophy
And finally, I think it’s important to position this like an Electron app even though it’s going to look like a hosted web app to LLMs like you. I just happen to use nix flakes instead of Electron as the hosting mechanism, the same lack of criticality of enterprise concerns that’s provided Electron apps should be provided to this systems.
So there we go. Give me the first pass of a 10-card version of Poetflow in that it has process locking and unlocking at the end, but the 10 cards to get there are otherwise blank, closer to the Bridgeflow example, please and thank you!
10 Steps From o1 Punch
o1 Pro seemed at first not as good of a coder as Claude 3.5 Sonnet, but the truth is you give it a plenty good story, it’ll give you plenty good code. You have to make up what you lose in in-editor context with a fluffy narrative.
o1 Pro: Below is a minimal, 10-card “Poetflow-style” workflow example. Each card is essentially blank—closer to the Bridgeflow style, but including a final step to lock/unlock (like Poetflow). Use it as a starter template for building out advanced cards (file directory listings, form demos, Pandas grids, etc.). This is your 10-step pipeline scaffolding to fill in as you wish!
class TenCardFlow:
"""
A 10-step flow that ends with a Finalize step, demonstrating:
- Basic pipeline structure
- Minimal "blank" steps
- Optional finalization/unfinalization
Close to Bridgeflow in simplicity, but with an 11th route to finalize/unfinalize
similar to Poetflow.
"""
def __init__(self, app, pipulate, prefix="/tenflow"):
self.app = app
self.pipulate = pipulate
self.prefix = prefix
# Steps array: we do 10 "cards" + 1 "finalize" step
# (internal_key, step_id, label)
self.STEPS = [
("c1", "step_01", "Card 1"),
("c2", "step_02", "Card 2"),
("c3", "step_03", "Card 3"),
("c4", "step_04", "Card 4"),
("c5", "step_05", "Card 5"),
("c6", "step_06", "Card 6"),
("c7", "step_07", "Card 7"),
("c8", "step_08", "Card 8"),
("c9", "step_09", "Card 9"),
("c10", "step_10", "Card 10"),
("finalized", "step_11", "Finalize")
]
# Route definitions
routes = [
(f"{prefix}", self.landing),
(f"{prefix}/init", self.init, ["POST"]),
(f"{prefix}/step_01", self.step_01),
(f"{prefix}/step_01_submit", self.step_01_submit, ["POST"]),
(f"{prefix}/step_02", self.step_02),
(f"{prefix}/step_02_submit", self.step_02_submit, ["POST"]),
(f"{prefix}/step_03", self.step_03),
(f"{prefix}/step_03_submit", self.step_03_submit, ["POST"]),
(f"{prefix}/step_04", self.step_04),
(f"{prefix}/step_04_submit", self.step_04_submit, ["POST"]),
(f"{prefix}/step_05", self.step_05),
(f"{prefix}/step_05_submit", self.step_05_submit, ["POST"]),
(f"{prefix}/step_06", self.step_06),
(f"{prefix}/step_06_submit", self.step_06_submit, ["POST"]),
(f"{prefix}/step_07", self.step_07),
(f"{prefix}/step_07_submit", self.step_07_submit, ["POST"]),
(f"{prefix}/step_08", self.step_08),
(f"{prefix}/step_08_submit", self.step_08_submit, ["POST"]),
(f"{prefix}/step_09", self.step_09),
(f"{prefix}/step_09_submit", self.step_09_submit, ["POST"]),
(f"{prefix}/step_10", self.step_10),
(f"{prefix}/step_10_submit", self.step_10_submit, ["POST"]),
(f"{prefix}/step_11", self.step_11),
(f"{prefix}/step_11_submit", self.step_11_submit, ["POST"]),
# Finalization toggles
(f"{prefix}/unfinalize", self.unfinalize, ["POST"])
]
for path, handler, *methods in routes:
method_list = methods[0] if methods else ["GET"]
self.app.route(path, methods=method_list)(handler)
# ---------------------------------------------------------------------
# LANDING & INIT
# ---------------------------------------------------------------------
async def landing(self, request):
"""
GET /tenflow
Quick landing page with a form that sets pipeline_id and calls /init
"""
return Container(
Card(
H2("10-Card Demo Flow"),
P("Welcome. This flow has 10 steps (cards) and a final lock/unlock step."),
Form(
Input(
type="text",
name="pipeline_id",
placeholder="Enter an ID or name for this run",
required=True
),
Button("Begin 10-Card Flow", type="submit"),
hx_post=f"{self.prefix}/init",
hx_target="#tenflow-container"
)
),
Div(id="tenflow-container")
)
async def init(self, request):
"""
POST /tenflow/init
Sets pipeline_id, initializes pipeline, returns placeholders for steps
"""
form = await request.form()
pipeline_id = form.get("pipeline_id", "untitled")
db["pipeline_id"] = pipeline_id
self.pipulate.initialize_if_missing(pipeline_id)
# If user has already finalized, skip to final
step11_data = self.pipulate.get_step_data(pipeline_id, "step_11", {})
if "finalized" in step11_data:
return Div(
self.render_finalized(),
id="tenflow-container"
)
# Otherwise show placeholders for steps (only load step_01)
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(
*placeholders,
id="tenflow-container"
)
# ---------------------------------------------------------------------
# STEP 01
# ---------------------------------------------------------------------
async def step_01(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step1_data = self.pipulate.get_step_data(pipeline_id, "step_01", {})
if step1_data.get("data"):
# Already done => show summary + next
return Div(
Card(
f"Step 1 done. Value: {step1_data['data']}",
style="color: green;"
),
Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load")
)
else:
# Show form
return Div(
Card(
H3("Card #1"),
P("Enter any data you want, just a placeholder..."),
Form(
Input(type="text", name="data", placeholder="some input"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_01_submit",
hx_target="#step_01"
)
),
Div(id="step_02"),
id="step_01"
)
async def step_01_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_01", {"data": user_data})
return Div(
Card(f"Step 1 locked in with data: {user_data}", style="color: green;"),
Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 02
# ---------------------------------------------------------------------
async def step_02(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step2_data = self.pipulate.get_step_data(pipeline_id, "step_02", {})
if step2_data.get("data"):
return Div(
Card(
f"Step 2 done. Value: {step2_data['data']}",
style="color: green;"
),
Div(id="step_03", hx_get=f"{self.prefix}/step_03", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #2"),
Form(
Input(type="text", name="data", placeholder="some input for step 2"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_02_submit",
hx_target="#step_02"
)
),
Div(id="step_03"),
id="step_02"
)
async def step_02_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_02", {"data": user_data})
return Div(
Card(f"Step 2 locked in with data: {user_data}", style="color: green;"),
Div(id="step_03", hx_get=f"{self.prefix}/step_03", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 03
# ---------------------------------------------------------------------
async def step_03(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step3_data = self.pipulate.get_step_data(pipeline_id, "step_03", {})
if step3_data.get("data"):
return Div(
Card(
f"Step 3 done. Value: {step3_data['data']}",
style="color: green;"
),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #3"),
Form(
Input(type="text", name="data", placeholder="some input for step 3"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_03_submit",
hx_target="#step_03"
)
),
Div(id="step_04"),
id="step_03"
)
async def step_03_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_03", {"data": user_data})
return Div(
Card(f"Step 3 locked in with data: {user_data}", style="color: green;"),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 04
# ---------------------------------------------------------------------
async def step_04(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step4_data = self.pipulate.get_step_data(pipeline_id, "step_04", {})
if step4_data.get("data"):
return Div(
Card(
f"Step 4 done. Value: {step4_data['data']}",
style="color: green;"
),
Div(id="step_05", hx_get=f"{self.prefix}/step_05", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #4"),
Form(
Input(type="text", name="data", placeholder="some input for step 4"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_04_submit",
hx_target="#step_04"
)
),
Div(id="step_05"),
id="step_04"
)
async def step_04_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_04", {"data": user_data})
return Div(
Card(f"Step 4 locked in: {user_data}", style="color: green;"),
Div(id="step_05", hx_get=f"{self.prefix}/step_05", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 05
# ---------------------------------------------------------------------
async def step_05(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step5_data = self.pipulate.get_step_data(pipeline_id, "step_05", {})
if step5_data.get("data"):
return Div(
Card(
f"Step 5 done. Value: {step5_data['data']}",
style="color: green;"
),
Div(id="step_06", hx_get=f"{self.prefix}/step_06", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #5"),
Form(
Input(type="text", name="data", placeholder="some input for step 5"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_05_submit",
hx_target="#step_05"
)
),
Div(id="step_06"),
id="step_05"
)
async def step_05_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_05", {"data": user_data})
return Div(
Card(f"Step 5 locked in: {user_data}", style="color: green;"),
Div(id="step_06", hx_get=f"{self.prefix}/step_06", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 06
# ---------------------------------------------------------------------
async def step_06(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step6_data = self.pipulate.get_step_data(pipeline_id, "step_06", {})
if step6_data.get("data"):
return Div(
Card(
f"Step 6 done. Value: {step6_data['data']}",
style="color: green;"
),
Div(id="step_07", hx_get=f"{self.prefix}/step_07", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #6"),
Form(
Input(type="text", name="data", placeholder="some input for step 6"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_06_submit",
hx_target="#step_06"
)
),
Div(id="step_07"),
id="step_06"
)
async def step_06_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_06", {"data": user_data})
return Div(
Card(f"Step 6 locked in: {user_data}", style="color: green;"),
Div(id="step_07", hx_get=f"{self.prefix}/step_07", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 07
# ---------------------------------------------------------------------
async def step_07(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step7_data = self.pipulate.get_step_data(pipeline_id, "step_07", {})
if step7_data.get("data"):
return Div(
Card(
f"Step 7 done. Value: {step7_data['data']}",
style="color: green;"
),
Div(id="step_08", hx_get=f"{self.prefix}/step_08", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #7"),
Form(
Input(type="text", name="data", placeholder="some input for step 7"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_07_submit",
hx_target="#step_07"
)
),
Div(id="step_08"),
id="step_07"
)
async def step_07_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_07", {"data": user_data})
return Div(
Card(f"Step 7 locked in: {user_data}", style="color: green;"),
Div(id="step_08", hx_get=f"{self.prefix}/step_08", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 08
# ---------------------------------------------------------------------
async def step_08(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step8_data = self.pipulate.get_step_data(pipeline_id, "step_08", {})
if step8_data.get("data"):
return Div(
Card(
f"Step 8 done. Value: {step8_data['data']}",
style="color: green;"
),
Div(id="step_09", hx_get=f"{self.prefix}/step_09", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #8"),
Form(
Input(type="text", name="data", placeholder="some input for step 8"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_08_submit",
hx_target="#step_08"
)
),
Div(id="step_09"),
id="step_08"
)
async def step_08_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_08", {"data": user_data})
return Div(
Card(f"Step 8 locked in: {user_data}", style="color: green;"),
Div(id="step_09", hx_get=f"{self.prefix}/step_09", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 09
# ---------------------------------------------------------------------
async def step_09(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step9_data = self.pipulate.get_step_data(pipeline_id, "step_09", {})
if step9_data.get("data"):
return Div(
Card(
f"Step 9 done. Value: {step9_data['data']}",
style="color: green;"
),
Div(id="step_10", hx_get=f"{self.prefix}/step_10", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #9"),
Form(
Input(type="text", name="data", placeholder="some input for step 9"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_09_submit",
hx_target="#step_09"
)
),
Div(id="step_10"),
id="step_09"
)
async def step_09_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_09", {"data": user_data})
return Div(
Card(f"Step 9 locked in: {user_data}", style="color: green;"),
Div(id="step_10", hx_get=f"{self.prefix}/step_10", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 10
# ---------------------------------------------------------------------
async def step_10(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step10_data = self.pipulate.get_step_data(pipeline_id, "step_10", {})
if step10_data.get("data"):
# All 10 done => show next: finalize (step_11)
return Div(
Card(
f"Step 10 done. Value: {step10_data['data']}",
style="color: green;"
),
Div(id="step_11", hx_get=f"{self.prefix}/step_11", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #10"),
Form(
Input(type="text", name="data", placeholder="some input for step 10"),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_10_submit",
hx_target="#step_10"
)
),
Div(id="step_11"),
id="step_10"
)
async def step_10_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_10", {"data": user_data})
return Div(
Card(f"Step 10 locked in: {user_data}", style="color: green;"),
Div(id="step_11", hx_get=f"{self.prefix}/step_11", hx_trigger="load")
)
# ---------------------------------------------------------------------
# STEP 11: Finalize
# ---------------------------------------------------------------------
async def step_11(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step11_data = self.pipulate.get_step_data(pipeline_id, "step_11", {})
if "finalized" in step11_data:
# Already finalized => show final view
return self.render_finalized()
# Not finalized => show finalize button
return Div(
Card(
H3("Step 11: Finalize"),
P("You can finalize this pipeline or go back to fix something."),
Form(
Button("Finalize All 10 Steps", type="submit"),
hx_post=f"{self.prefix}/step_11_submit",
hx_target="#step_11"
)
),
id="step_11"
)
async def step_11_submit(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
# Mark finalized in step_11 data
self.pipulate.set_step_data(pipeline_id, "step_11", {"finalized": True})
return self.render_finalized()
def render_finalized(self):
"""Return a simple locked/finalized card."""
return Card(
H3("All Steps Finalized"),
P("Your 10-card workflow is complete!"),
Form(
Button("Unfinalize", type="submit", style="background-color: #f66;"),
hx_post=f"{self.prefix}/unfinalize",
hx_target="#tenflow-container",
hx_swap="outerHTML"
)
)
async def unfinalize(self, request):
"""
Remove 'finalized' flag from step_11 data, allowing user to revisit steps.
"""
pipeline_id = db.get("pipeline_id", "untitled")
if not pipeline_id:
return P("No pipeline found. Please start again.", style="color: red;")
state = self.pipulate.get_state(pipeline_id)
step11_obj = state.get("step_11", {})
if "finalized" in step11_obj:
del step11_obj["finalized"]
state["step_11"] = step11_obj
self.pipulate._save_state(pipeline_id, state)
# Show placeholders from the beginning:
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(*placeholders, id="tenflow-container")
else:
return P("Not finalized, so nothing to unfinalize.")
Summary
- 11 Steps total: 10 “cards” + 1 final “step_11” to finalize.
- Minimal: Each step just collects a simple
datafield, stores it instep_X. - Finalization: Step 11 sets
{"finalized": True}in that record; from that point, the user sees a locked card unless they unfinalize. - Structure: This is basically the same pattern you see in Bridgeflow/Poetflow, but stretched to 10 steps (plus the final).
From here, you can flesh out each “Card #X” with fancy forms, embedded file lists, browser calls, Pandas DataFrame displays, etc.—all while preserving the incremental pipeline approach and a final “lock step.” Enjoy!
What Does Gemini 2.0 Experimental Think of All This?
At this point I love to invite Gemini 2.0 Experimental into the process. I didn’t think I was going to be using Gemini, not buying into the Google Cloud Platform Vertex AI lock-in. But they’re including Gemini access in my $100/year bottom-feeder 2TB Google One subscription—reduced from the 5TB level as I break my cloud dependencies. Its token window size is appealing for digesting and summarizing articles like this.
Gemini 2.0 Experimental: This is a very in-depth and interesting article! Here are my thoughts on it, broken down by the various themes and topics it touches upon:
1. The Author’s Project & Naming Conventions:
- Pipulate, Botifython, Chipotheseus: The author’s playful yet thoughtful naming conventions reveal a lot about their approach. They recognize the power of names in shaping perception and injecting personality into software. The distinction between the open-source “Pipulate,” the work-focused “Botifython,” and the experimental “Chipotheseus” demonstrates a clear understanding of different contexts and audiences.
- Local LLM Integration (Ollama): The decision to focus on a local LLM like Ollama is significant. It highlights a growing trend away from complete reliance on cloud-based APIs, driven by concerns about cost, latency, and data privacy. This aligns with the author’s emphasis on “local-first” development.
- FastHTML and HTMX: The choice of these technologies suggests a desire for simplicity and efficiency in web development, moving away from the complexity of frameworks like React. This aligns with the overall philosophy of streamlined workflows and reducing unnecessary overhead.
2. The “AI Revolution” and its Implications:
- Democratization of Knowledge: The author’s observation that AI is making “common wisdom and best practices” more accessible is insightful. AI-powered tools can indeed level the playing field, giving individuals access to knowledge and expertise that was previously limited by factors like education and social connections.
- The “Luck” Factor: The idea that AI can reduce the role of luck in success is intriguing. While luck will likely always play a part, AI can certainly help individuals make more informed decisions and optimize their efforts.
- OpenAI and the Future of AI: The commentary on OpenAI’s challenges (revenue, power consumption) is spot on. The AI industry is facing growing pains as it transitions from research to widespread adoption. The need for sustainable business models and efficient infrastructure is becoming increasingly apparent.
3. The Importance of Unix Philosophy and Pipes:
- Unix as the Foundation: The author’s deep dive into the history of Unix and its enduring influence on computer science is well-justified. The principles of modularity, composability, and the power of the command line remain highly relevant today.
- Pipes as a Metaphor for Modern Workflows: The analogy between Unix pipes and modern data pipelines is apt. The ability to chain together small, specialized tools to create complex workflows is a powerful concept that applies to many domains, including AI development.
- The Lost Art of the Command Line: The lament about the decline of command-line proficiency is understandable. While GUIs have made technology more accessible, they can also obscure the underlying power and flexibility of the command line. The resurgence of text-based interfaces (like with LLMs) could signal a renewed appreciation for the command line.
4. Web Development and the DOM:
- Bridging the Visual and Text Worlds: The discussion of the Document Object Model (DOM) as a bridge between visual interfaces and automation is accurate. The DOM provides a structured representation of web content that can be manipulated programmatically.
- Markdown’s Role: The “Markdown circle” observation is humorous and insightful. It highlights the irony of converting content to HTML for display and then back to Markdown for machine consumption. This underscores the importance of choosing the right format for the task at hand.
5. The Author’s Coding Style and Philosophy:
- Musicality and Rhythm in Code: The author’s emphasis on the “musical” nature of code is fascinating. They see a rhythm and flow in the way code is structured and organized, and they strive to create code that is not only functional but also aesthetically pleasing.
- Pythonic Approach: The code examples demonstrate a strong preference for Pythonic idioms and a focus on readability. The use of list comprehensions, inline HTML generation, and minimal indenting are all characteristic of this style.
- HTMX for Dynamic Updates: The integration of HTMX allows for dynamic updates to the web interface without the need for a full-page reload, resulting in a more responsive and interactive user experience.
- Local-First Development: The author’s commitment to local-first development is evident in their choice of tools and their emphasis on minimizing external dependencies. This approach aligns with the principles of data privacy, security, and offline functionality.
6. The “TenCardFlow” Example and Future Directions:
- A Solid Foundation: The provided
TenCardFlowcode is a well-structured and commented example of the author’s approach. It serves as a good starting point for building more complex workflows. - Potential for Expansion: The planned integrations with file system access, form elements, Pandas, Matplotlib, Anywidget, and D3.js demonstrate the versatility of the framework. These additions will enable a wide range of data processing and visualization tasks.
- Electron App Analogy: The comparison to Electron apps is interesting. Both aim to provide a desktop-like experience using web technologies. The author’s approach, however, leverages the power of the local machine more directly.
Overall Impressions:
This article presents a compelling vision for a new way of building AI-powered applications. It combines a deep understanding of computer science fundamentals with a pragmatic approach to modern web development. The author’s emphasis on simplicity, local-first development, and the power of Unix-like pipelines is refreshing and timely.
The project described is ambitious and has the potential to empower individuals to create sophisticated data-driven applications without the need for extensive infrastructure or specialized expertise. I’m particularly impressed by:
- The holistic perspective: The author seamlessly blends technical details with philosophical reflections on the impact of AI and the evolution of computing.
- The focus on developer experience: The emphasis on clear naming conventions, readable code, and a streamlined workflow suggests a strong commitment to making the development process enjoyable and accessible.
- The potential for community contributions: The open-source nature of the project and the author’s invitation for feedback create an opportunity for collaborative development and innovation.
I believe this article and the underlying project are significant contributions to the ongoing conversation about the future of AI, web development, and the democratization of technology. I’m excited to see how this project evolves and the impact it will have on the way we build and interact with software.
Alright, this time I put the o1 Pro created code into the codebase right away, instead of waiting a few days to work up the courage, haha! And it worked almost exactly as intended without any edits. I need to modify the instructions so that the landing page of a workflow never uses requests as a parameter. That’s because the way it gets linked into the system is this:
async def create_grid_left(menux, render_items=None):
"""
YOU HAVE ARRIVED TO WHERE THE PLUGINS PLUG IN!!!
Create the left column of the main grid layout with vertically stacked Cards.
menuxxx makes for a good search term to jump here for frequent menu tweaking.
+-----------------------------------------------------------+
| create_nav_group |
+-----------------------------------------------------------+
| Main Container |
| +-----------------------------------------------------+ |
| | Chat | |
| | Plugin Output Interface | |
| | +-----------------------------------+ +--------+ | |
| | | menux | | | | |
| | | | | | | |
| | | +-------------+ | | | | |
| | | | Plugin | | | | | |
| | | | Decision | | | | | |
| | | | Point | | | | | |
| | | +------+------+ | | | | |
| | | | | | | | |
| | | +--------+--------+ | | | | |
| | | | | | | | | | |
| | | todo / stream link | | | | |
| | | default sim graph | | | | |
| | | | | | | |
| | +-----------------------------------+ +--------+ | |
| | | |
| +-----------------------------------------------------+ |
| |
+-----------------------------------------------------------+
| create_poke_button |
+-----------------------------------------------------------+
"""
if menux == profile_app.name:
return await profile_render() # Might look like a plugin, but integral.
elif menux == todo_app.name:
return await todo_render(menux, render_items)
elif menux == 'connect_with_botify':
return await connect_with_botify.connect_render()
elif menux == 'link_graph':
return await link_graph.link_render()
elif menux == 'link_graph_flow':
return await link_graph_flow.landing()
elif menux == 'ten_card_flow':
return await ten_card_flow.landing()
elif menux == 'stream_simulator':
return await stream_simulator.stream_render()
elif menux == 'bridgeflow':
return await bridgeflow.landing()
elif menux == 'poetflow':
return await poetflow.start_form()
else:
return await introduction.introduction_render()
Pipeline State Management Issue
So, there is no request object in scope on that first .landing() method call.
I’ll have to update the above guide with that detail.
TenCardFlow Improvements
Next, here are some of the subtleties about the TenCardFlow that I want to want to improve before moving forward with the Card equivalents of the Jupyter Cell Magics. I really can’t wait to get to them, especially Anywidget, however I need to get these rough edges smoothed out.
Card Navigation Consistency
Firstly, when on Card 1 and submitting a key that already exists, it jumps right to showing the last card, I guess it’s the 11th which is the locked state. However, I want 100% consistent presentation, and this is a view that is not shown when filling in the prior cards. When filling them in, that 11th card shows at the end of the chain of cards, and there is a chain reaction mechanism to do this. This chain reaction mechanism is properly used if a pipeline workflow is left unfinished and you plug its ID back in on card 1. It will chain-react up to where you left off, and this should actually be the same for locked workflows, the thinking being that a large purpose for keeping a workflow pipeline record existing is to provide the ad hoc access to the files and other output created as a side effect of the workflow.
File Access and Side Effects
The CSVs files from Linkgraph for example have no way to access them right now. As a standard convention, we want to be able to put the same Project URL in and have the card chain reaction occur, and on one of those cards will be the tiny file browser user interface. So the already processed cards provide an opportunity for ad hoc access to the side effects. So there is ever a pipeline workflow shown that does not also show the chain reacted cards required to build it up to whatever step it’s on, even a locked and finalized step. Does that make sense?
o1 Pro: Below is an approach and some sample adjustments to ensure that if a user plugs in an existing workflow ID—whether it’s partially completed or fully locked—the system always renders the entire chain of steps from Card 1 through Card 10, culminating in the final locked step (if finalized). That way, you never “jump” right to the last step or skip the prior cards. This is particularly useful for letting users revisit side effects (e.g. CSV files) associated with earlier steps.
1. The Desired Behavior
- Landing: If you type a pipeline ID that’s already in the system, the flow shouldn’t abruptly jump to step 11 (the locked final). It should display placeholders from step_01 to step_10, with each step’s content showing “Done” or “Locked” (if those steps were already completed).
- Chain Reaction: We want the placeholders loaded for every step.
- If the workflow isn’t finalized yet, the last incomplete step auto-loads.
- If it is finalized (step_11 has
"finalized": true), we still display steps 01–10 as “Done,” and the final card showing “locked.”
Essentially, even for a locked pipeline, the user sees the entire progression of steps, but the final card is locked.
2. Revisiting the TenCardFlow init() Method
Currently, init() checks if you are “finalized” then jumps right to render_finalized(). Instead, we can unify the display logic so that we always generate placeholders for steps 1–10 (plus the final step), letting them auto-load. Then the last step or “final” step can check if it’s locked.
Below is a conceptual code snippet. The key difference is we remove the if "finalized" in step11_data: return Div(self.render_finalized()) portion, and instead let the placeholders handle it. Then in the final step logic, we either show a locked view or the finalize form.
DISCLAIMER: This snippet focuses on the high-level idea. You’ll adapt it to your exact code style.
async def init(self, request):
"""
POST /tenflow/init
Sets pipeline_id, initializes pipeline, always returns placeholders from step_01 -> step_11
letting the chain reaction load them. If the workflow is already finalized, the last step
will appear locked, but we still see the earlier steps in the chain.
"""
form = await request.form()
pipeline_id = form.get("pipeline_id", "untitled")
db["pipeline_id"] = pipeline_id
self.pipulate.initialize_if_missing(pipeline_id)
# Instead of jumping straight to a 'finalized' view,
# we ALWAYS generate placeholders from step_01 ... step_11
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(
*placeholders,
id="tenflow-container"
)
- No immediate final check in
init(). If the pipeline is already finalized, then step_11 will handle that. - Now when the user re-submits a pipeline ID that’s fully locked, the placeholders for steps 1–10 will appear in the DOM, each “done”/“locked” if you coded them that way, and step_11 will handle the locked view.
3. Adjusting Step 11 to Always Appear in the Chain
With the above approach, step 11 is always included in the placeholders from the get-go. If your code is set up to “auto-load” step_01 then chain to the next, you want to ensure step_11 is also part of that chain. So in your STEPS array:
self.STEPS = [
("c1", "step_01", "Card 1"),
...
("c10", "step_10", "Card 10"),
("finalized", "step_11", "Finalize")
]
When the user first visits, step_01 triggers automatically. Then each step’s completion triggers the next. Ultimately, if a pipeline is already completed, each step’s route will detect it’s done and skip to the next, leading to step_11, which sees {"finalized": True} and displays locked UI.
In other words, the presence of placeholders for every step ensures that the user sees a linear progression of cards, even if the pipeline is done or partially done.
4. Example: In Step 11’s GET Handler
async def step_11(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step11_data = self.pipulate.get_step_data(pipeline_id, "step_11", {})
# If finalized, show locked, else show finalize button
if "finalized" in step11_data:
return self.render_finalized()
else:
return Div(
Card(
H3("Step 11: Finalize"),
P("Everything up to step 10 is done. Finalize now?"),
Form(
Button("Finalize", type="submit"),
hx_post=f"{self.prefix}/step_11_submit",
hx_target="#step_11"
)
),
id="step_11"
)
Now, if the pipeline is already finalized, we show render_finalized(). If it’s not, we let them finalize.
5. Ensuring Each Step “Auto-Loads” or “Skips” If Already Done
Typically, you might see code in e.g. step_01:
if step1_data.get("data"):
# Already done => show summary + load next
return Div(
Card(...),
Div(id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load")
)
else:
# Show form
IMPORTANT: If the pipeline is fully or partially done, the user will see each step do a quick “already done” -> load next. That’s the chain reaction we want.
However, if you want them to truly see the earlier steps visually, you might prefer that it doesn’t skip in one shot. Instead, it’s a design choice:
- Current Approach: “One after the next” auto-load. This can lead to a quick skip if you have many steps. Some folks prefer that it just instantly leaps to the end.
- Alternative: Actually show the placeholders for each step at once, each with a label “Done” or “In Progress.” That can be done by returning all steps in a single response. But that’s more advanced UI design.
6. Summary of the “Chain Reaction But Show All Cards” Tweak
- In
init(): Always generate placeholders from step_01 to step_11. Don’t do a special “if locked, show final” early. - In each step: If it’s already done, quickly load the next, or simply show a small “Done” card with a link to the next.
- In step_11: If “finalized,” show locked. Otherwise let them finalize.
- No scenario forcibly short-circuits the chain or hides the earlier cards. If you want to see e.g. Step 3’s side effects, you can revisit that card: it’s either “done” or “in progress,” but it’s still present in the chain.
With these changes, you’ll maintain a consistent, linear progression of steps from 1 through 10, plus 11 for locking/unlocking, even when a pipeline is already done. The user (and your LLM or future advanced UI) can easily see or leverage side effects from the earlier steps.
Expressing Jump-to Feature Request
Initial Reflections
Me: Okay, the interruptability and resumability of this pipeline process is astounding.
The explicitness of the number of steps and their status as done or still needing to be done is completely clear.
I just added autofocus=True on the input fields of all the cards, so each new
card brings cursor focus to itself, so on the TenCardFlow in its current form,
it’s an entirely hands-on-the-keyboard app without having to move your hand to
the mouse until the finalize button.
Framework and Feature Requirements
This has lain down a phenomenal framework for moving forward. There is really only one baseline feature left, and that is resuming anywhere in the pipeline flow so you can make new choices from that point forward, effectively erasing everything that came after the selected card.
Challenging Traditional Pipeline Patterns
Now I’m going to be fighting against the LLM on this a bit, because it goes against traditional pipeline patterns, but I need remind it that first of all, these records in the pipeline table should only ever be considered ephemeral and temporary. They are useful and can provide user interfaces to access their side effects, so they alleviate us from having to build other apps. So if you delete a pipeline record that provided links to a CSV in a certain location and you want those links back because you have no other way to access it (never really true because localhost), but for argument’s sake, all you need do is put the same values into the cards leading up to that side-effect, and when it gets up to the ad hoc UI, it will just automatically detect the presence of the CSVs and not generate them again. The ad hoc file browser UI will be restored with the same pipeline values in.
The Case for Pipeline Record Mutability
So there is really no harm in deleting whole pipeline records. In this spirit, you should realize that there is especially no harm in erasing everything in a pipeline workflow up to a certain point.
So you can take a finalized TenCardFlow workflow pipeline record, unfinalize it, and roll back to step 5 and re-enter the values from that point forward.
Or at least, that is the feature I am hereby asking for.
Implementation Considerations
Honestly, implementation wise even though I’m going to leave it up to you o1 Pro, knowing what I know about this app it should merely be a matter of using the unserialized value from the JSON data blob for that record and altering it to make it only up to whatever step was selected in the UI (probably by just clicking the finished card), and then re-chain-reacting the UI. From the user’s point of view, they unlock a completed workflow, click any arbitrary step, and then it immediately looks like the process was only completed up to that step.
A Note on Data Loss Concerns
As the pattern predicting entity that you are, you’re going to get pretty nervous about data-loss at this point, and throwing up confirmation prompts to the user. Don’t be. Forget the confirmation prompts for now. I want the next step, which is the ability to step back into any step to be as fluid and seamless as possible.
Future Development Direction
I would also like it to not complicate the workflows much, so while your first pass may be changes mostly in the TenCardFlow class itself, think about making it a systemic helper function from the Pipulate class.
I think you know what I’m asking for, please and thank you.
Implementing Jumping To Anywhere In Workflow
o1 Pro: Below is an illustrative example of how you might enable stepping back into any previously completed card, erasing the later steps and letting the user re-enter values from that earlier point. It follows the same design used in other pipeline flows (e.g. Poetflow’s return_to_step). We’ll do it by:
- Adding a small route named
jump_to_steporreturn_to_step. - Using
pipulate.clear_steps_from(...)to remove all step data from the chosen step forward. - Regenerating the placeholders from step_01 onward in a single response.
Then, at the UI level, you can place a little hidden form or link on each card that calls this new route, passing the step ID you want to roll back to.
1. Add a Route: jump_to_step
In your TenCardFlow constructor, define a new route (e.g., /{prefix}/jump_to_step, methods=[“POST”]):
(f"{prefix}/jump_to_step", self.jump_to_step, ["POST"])
Then implement it as follows:
async def jump_to_step(self, request):
"""
POST /tenflow/jump_to_step
Allows user to roll back to a prior step, discarding all subsequent data
(including finalization flag if present).
"""
form = await request.form()
step_id = form.get("step") # e.g. "step_03" or "step_07"
pipeline_id = db.get("pipeline_id", "untitled")
# 1) Clear everything from step_id onwards
self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
# 2) Optionally unfinalize if it’s locked
# (If you want automatic unfinalization whenever jumping back)
state = self.pipulate.get_state(pipeline_id)
if "step_11" in state:
# If 'finalized' in step_11, remove it
if "finalized" in state["step_11"]:
del state["step_11"]["finalized"]
self.pipulate._save_state(pipeline_id, state)
# 3) Now re-generate all placeholders from start
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(*placeholders, id="tenflow-container")
Explanation
step = form.get("step"): The hidden form or link will pass something like"step_03"telling us which step to revert to.clear_steps_from: The pipeline-level function that removes all JSON keys for steps after (and including)step_03from the pipeline record.- Optional Unfinalize: If you always want to revert from locked state as well, just remove
"finalized"from thestep_11data. - Regenerate placeholders: This triggers the entire chain from step_01. Since steps 1–2 are presumably still done, they’ll auto-skip or display done, etc., until we hit the cleared step that’s not done.
2. Insert a Small Link or Button on Completed Steps
Whenever a step is completed, you can show a link or form that calls jump_to_step. For example, in step_03 if the step is done:
if step3_data.get("data"):
return Div(
Card(
f"Step 3 done. Value: {step3_data['data']}",
style="color: green;"
),
# Add a small "Roll Back" button
Form(
Input(type="hidden", name="step", value="step_03"),
Button("Revert to Step 3", type="submit", style="background-color: #faa;"),
hx_post=f"{self.prefix}/jump_to_step",
hx_target="#tenflow-container",
hx_swap="outerHTML"
),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
Explanation
- We keep the chain reaction to load step_04. But we also add a form with:
- A hidden input
name="step"=>"step_03". - A button labeled “Revert to Step 3.”
hx_post=f"{self.prefix}/jump_to_step", which calls the new route.hx_target="#tenflow-container", so we replace the entire container with the new placeholders.
- A hidden input
When the user clicks “Revert to Step 3,” it removes steps 3 and onward from the pipeline record, and returns us to that re-initialized chain of placeholders.
Note: This example shows a big pink “Revert to Step 3” button on every completed card. You might choose a smaller link or an icon, or only show it on the final “locked” step. That’s a design preference.
3. Behavior When Flow is Finalized
- If the pipeline is locked, step_11’s
{"finalized": true}is present. If you want to allow immediate roll-back from any step, do the automatic unfinalize snippet injump_to_step. - Alternatively, you can require the user to press an “Unfinalize” button first, then show the revert buttons. Either approach is possible.
4. Data-Loss: No Confirmation
As you requested, no confirm prompts in the code. The user’s single click will blow away everything from that step forward. This is consistent with your ephemeral pipeline approach. If you want to add a “Are you sure?” popup, you could add an HTMX confirm attribute later or a simple JavaScript alert.
5. Summation
With this small addition:
- Each completed step can show a revert button.
jump_to_stepusesclear_steps_fromto remove data from that step onward (and unfinalize if needed).- The pipeline regenerates from step 1 with placeholders, skipping quickly over completed steps 1–2 (for instance) and halting at the now “blank” step you rolled back to.
Thus, the user can revisit any step—even in a locked pipeline—without needing to delete or re-create the entire record. That’s it! Enjoy the new “hot-swappable” pipeline steps.
Me: Okay, this absolutely does what I ask for and is almost exactly what I want. However, look at how much code bloat it incurs and interrupts the musical flow of the notes. This is exactly the sort of thing where a helper function of some sort from Pipulate should bring the bloat back under control.
The code bloat implies a certain amount of customizability and lack of commonality, but given that the button is doing almost exactly the same thing every time, hitting the same endpoint with a certain identifier every time, I don’t think it justifies that amount of customizability at the workflow level.
See what you can do to turn it into a 1-liner per card or similar to get the same revert-to-step-x functionality, please and thank you!
o1 Pro: Below is one approach to collapse all that repeated “revert button” boilerplate into (roughly) a one-liner per step. The trick is to make a helper method in Pipulate that spits out a minimal Form or Div snippet containing the “Revert to X” logic. Then each step just calls that helper.
1. Add a Helper in Pipulate
Inside your Pipulate class, add something like:
def revert_control(
self,
step_id: str,
prefix: str,
target_id: str = "tenflow-container",
label: str = None,
style: str = "background-color: #faa;"
):
"""
Return a minimal Form with hidden step input & revert button.
We typically call this in a one-liner from each step's "already done" block.
Args:
step_id: e.g. "step_03"
prefix: e.g. "/tenflow"
target_id: the container ID to replace, default "tenflow-container"
label: if not provided, we'll do "Revert to step_03"
style: button style
"""
label = label or f"Revert {step_id}"
return Form(
Input(type="hidden", name="step", value=step_id),
Button(label, type="submit", style=style),
hx_post=f"{prefix}/jump_to_step",
hx_target=f"#{target_id}",
hx_swap="outerHTML"
)
Key Points
- We let you override
labelif you want a nicer display string (like"Revert to Step 3"). - We hardcode
hx_postto calljump_to_step. - We default
hx_target="#tenflow-container"but let you override if needed. - The step ID is all we need, because that’s what gets passed as a hidden form value.
2. Use It in Each Step
Now, in your TenCardFlow steps, all you do is call that helper to produce the revert button. For instance, in step_03:
async def step_03(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
step3_data = self.pipulate.get_step_data(pipeline_id, "step_03", {})
if step3_data.get("data"):
return Div(
Card(
f"Step 3 done. Value: {step3_data['data']}",
style="color: green;"
),
# One-liner: produce the revert button
self.pipulate.revert_control("step_03", self.prefix, label="Revert to Step 3"),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
else:
return Div(
Card(
H3("Card #3"),
Form(
Input(type="text", name="data", placeholder="some input for step 3", autofocus=True),
Button("Next", type="submit"),
hx_post=f"{self.prefix}/step_03_submit",
hx_target="#step_03"
)
),
Div(id="step_04"),
id="step_03"
)
Now the code for each “completed step” scenario is basically:
- Show the done Card.
- Insert
self.pipulate.revert_control(...). - Chain to the next step placeholder.
Everything else is gone.
3. Update the “submit” blocks if needed
If you also want a revert button in the “submit” return for each step, do the same:
async def step_03_submit(self, request):
form = await request.form()
user_data = form.get("data", "")
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_03", {"data": user_data})
return Div(
Card(f"Step 3 locked in: {user_data}", style="color: green;"),
self.pipulate.revert_control("step_03", self.prefix, label="Revert to Step 3"),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
4. Done
That’s it. You’ve turned the revert button into a single line:
self.pipulate.revert_control("step_05", self.prefix, label="Revert to Step 5")
Everything else about how it reverts, the hidden input, the target container, or the jump_to_step endpoint is now safely tucked away in the helper. You can further tweak that helper with additional arguments for color or text. If you want shorter calls still, you might:
def revert_control_1liner(self, step_id):
return self.revert_control(step_id, prefix="/tenflow", label=f"Revert {step_id}")
But the essential concept is the same: one-liner in each step—no code bloat in your main flow.
Me: This is most excellent! It worked exactly correctly. Now the Finalize button has a reason for being. It should remove all the Revert buttons exactly as you suggested as a possible choice earlier. I now want to do that to reduce the UI clutter on finalized workflows. But as usual, I don’t want to litter the workflows with boilerplate code, so find a good way to do this with minimal alteration (but logical/semantic is fine) to the workflow code, and if necessary put supporting help in Pipulate.
o1 Pro: Below is one clean way to hide the revert buttons once the workflow is finalized, with minimal boilerplate changes in your step code. We’ll do this by abstracting the idea of a “conditional revert control.” Then each step can just place a single line that says “Show revert button if not finalized.”
1. Add an is_finalized Method in Pipulate
We need a quick way to see whether the pipeline is finalized. Suppose “finalized” is always stored in the final step ID (e.g., "step_11"). Then:
def is_finalized(self, url: str, final_step: str = "step_11") -> bool:
"""
Return True if the pipeline's final_step data has "finalized" = True.
"""
step_data = self.get_step_data(url, final_step, {})
return "finalized" in step_data
This way, your code doesn’t need to repeatedly parse the JSON blob. The method is an easy yes/no about finalization.
2. Add a “Conditional Revert Control” in Pipulate
We also define a helper that conditionally returns the revert form, or returns None (which FastHTML will skip) if the pipeline is finalized. For example:
def revert_control_if_not_final(
self,
url: str,
step_id: str,
prefix: str,
final_step: str = "step_11",
target_id: str = "tenflow-container",
label: str = None,
style: str = "background-color: #faa;"
):
"""
If the pipeline is finalized, return None (no revert).
Otherwise, return the revert_control.
"""
if self.is_finalized(url, final_step=final_step):
return None # or return an empty Div(), if you prefer
# else, not finalized => show revert button
label = label or f"Revert {step_id}"
return self.revert_control(step_id, prefix, target_id, label, style)
Why do this?
- One-liner usage in each step:
self.pipulate.revert_control_if_not_final(...). - No additional if-check inside your step code. The method does the if-check for you.
3. Minimal Changes in TenCardFlow Steps
In each “done” portion of a step, just replace:
self.pipulate.revert_control("step_03", self.prefix, label="Revert to Step 3")
with:
self.pipulate.revert_control_if_not_final(
pipeline_id,
step_id="step_03",
prefix=self.prefix,
label="Revert to Step 3"
)
So, for example, step_03’s “done” block:
if step3_data.get("data"):
return Div(
Card(f"Step 3 done. Value: {step3_data['data']}", style="color: green;"),
self.pipulate.revert_control_if_not_final(
pipeline_id,
step_id="step_03",
prefix=self.prefix,
label="Revert to Step 3"
),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
That’s it.
- If the user hasn’t finalized, they get the revert button.
- If the workflow is finalized, the helper returns
Noneand no revert button shows.
4. No Extra Conditionals in the Workflow Code
Notice we don’t have to put an extra if not self.pipulate.is_finalized(...) inside every step. Instead, each step uses the single “conditional revert button” line. The final step’s code and unfinalize logic remain the same. Once the user finalizes, all steps will see is_finalized(...) == True and skip revert buttons.
Example Pseudocode
# In Pipulate:
def is_finalized(self, url: str, final_step: str = "step_11") -> bool:
step_data = self.get_step_data(url, final_step, {})
return "finalized" in step_data
def revert_control_if_not_final(
self,
url: str,
step_id: str,
prefix: str,
final_step: str = "step_11",
target_id: str = "tenflow-container",
label: str = None,
style: str = "background-color: #faa;"
):
if self.is_finalized(url, final_step=final_step):
return None
label = label or f"Revert {step_id}"
return self.revert_control(step_id, prefix, target_id, label, style)
Then in TenCardFlow.step_03 (done case) you do:
if step3_data.get("data"):
return Div(
Card(f"Step 3 done. Value: {step3_data['data']}", style="color: green;"),
self.pipulate.revert_control_if_not_final(
pipeline_id,
"step_03",
prefix=self.prefix,
label="Revert to Step 3"
),
Div(id="step_04", hx_get=f"{self.prefix}/step_04", hx_trigger="load")
)
No other changes needed. Now the finalization button can do its usual job, and once “finalized” is set, poof all revert buttons vanish in every step.
Summary
is_finalized(url)method to handle the logic of checking finalization.revert_control_if_not_final(...)method that either returns the revert form orNone.- In each step’s “done” block, you swap out
self.pipulate.revert_control(...)for the conditional version.
This approach keeps your pipeline code extremely concise: each step shows exactly one line for the revert button, no extra logic or if-check. And the moment step_11 is finalized, revert buttons are hidden across the board. Enjoy!
Me: Nice! But you see how unfinalizing re-chain-reacts the pipeline to show the revert buttons? You must have thought that through knowing that had to occur for the UI elements to be present. But when we Finalize a pipeline, it should also hide the revert buttons immediately, because they are all technically still functional and could cause data loss on something you meant to have locked as finalized. It seems that simply triggering the chain reaction again is all we need.
o1 Pro: Below is one straightforward way to re-chain-react immediately once you finalize the workflow, ensuring all steps redraw and see that they’re now in a finalized state (thus hiding the revert buttons). Essentially, we do to Finalize the same thing we already do to Unfinalize: generate placeholders from the beginning and let each step re-load with its “finalized vs. not” logic.
1) In step_11_submit, Trigger a Full Re-Render
Right now, you’re returning self.render_finalized() at the end of step_11_submit. Instead, you can do something like:
async def step_11_submit(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
self.pipulate.set_step_data(pipeline_id, "step_11", {"finalized": True})
# Now re-generate placeholders from step_01 ... step_11
# so everything re-draws in finalized mode (i.e., no revert buttons).
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(*placeholders, id="tenflow-container")
With that change, once the user clicks “Finalize,” the code sets the pipeline to finalized in step_11 data, then returns the same chain reaction placeholders we use everywhere else. As each step loads, it sees is_finalized == True and hides the revert controls. Finally, step_11 sees is_finalized == True and returns the locked “finalized” card.
If You Want to Jump Directly to the Final Card
- The steps will still chain from 1…11, but they’ll load quickly in the background. If you want the user to see the final card immediately (in addition to everything else updating), you can do something fancy like starting from the last step. But typically letting them all load from step_01 up to step_11 is fine.
2) Example Snippet
Remove or comment out this line in step_11_submit:
# return self.render_finalized()
Replace with:
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(*placeholders, id="tenflow-container")
Now finalizing looks symmetrical to unfinalizing:
async def step_11_submit(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
# Mark finalized
self.pipulate.set_step_data(pipeline_id, "step_11", {"finalized": True})
# Regenerate entire chain in finalized mode
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
return Div(*placeholders, id="tenflow-container")
3) Why This Works
-
No Revert Buttons: Each step calls
revert_control_if_not_final(...)which checksis_finalized(...). Because we just set"step_11" -> {"finalized": True}, every step sees it’s locked now and returnsNonefor the revert button. -
Immediate UI Refresh: The chain reaction placeholders call each
step_xxendpoint in turn. You effectively re-render all steps from 1 to 10, each sees “finalized,” so no revert button is shown. Finally, step_11 sees it’s already finalized and returns the “All Steps Finalized” card. -
Symmetry: Unfinalizing does the same chain reaction (but removes the
"finalized"field), and finalizing does the same chain reaction (but adds the"finalized"field). That keeps your code consistent and avoids any partial states.
Done! Now finalizing instantly re-renders the entire pipeline, so the user sees the new locked-down state—no revert buttons, just the final card. That’s typically the simplest, cleanest approach. Enjoy!
Me: Nice, but we’ve got some double DOM appending going on. It either doesn’t target a high enough element, or appends instead of replaces. I’m not exactly sure, since I left most of the implementation to you. But this condition occurs consistently when hitting Finalize. Unfinalize seems to work fine.
[pastes DOM element]
o1 Pro: Below is a concise approach that avoids double-appending (the “double DOM” problem) when you finalize. The basic idea:
- Ensure your “Finalize” form has
hx_target="#tenflow-container"andhx_swap="outerHTML". - In
step_11_submit, only return the “chain reaction” placeholders (the same Div withid="tenflow-container"). - Make sure each placeholder has the correct
hx_swapso it doesn’t nest inside itself.
This ensures the old #tenflow-container gets fully replaced (outerHTML swapped) by the new container, rather than appended inside it.
1) Set hx_swap="outerHTML" on the Finalize Form
In your step_11 method, the finalize button code might look like:
return Div(
Card(
H3("Step 11: Finalize"),
P("You can finalize this pipeline or go back to fix something."),
Form(
Button("Finalize All 10 Steps", type="submit"),
hx_post=f"{self.prefix}/step_11_submit",
hx_target="#tenflow-container", # This is key
hx_swap="outerHTML" # Entire container replaced
)
),
id="step_11"
)
Now, when the user clicks “Finalize,” HTMX will send a POST to step_11_submit, then it will replace (outerHTML) the entire <div id="tenflow-container"> with whatever that route returns.
2) Return Only the Placeholders Div from step_11_submit
In step_11_submit, remove any direct call to render_finalized() and simply do:
async def step_11_submit(self, request):
pipeline_id = db.get("pipeline_id", "untitled")
# Mark finalized
self.pipulate.set_step_data(pipeline_id, "step_11", {"finalized": True})
# Re-generate placeholders from step_01...step_11
# Let the steps each see "finalized" and hide revert buttons
placeholders = self.pipulate.generate_step_placeholders(self.STEPS, self.prefix, start_from=0)
# Return them with "tenflow-container" as the ID
return Div(*placeholders, id="tenflow-container")
Important: Because you used hx_swap="outerHTML" on the form, this entire new container replaces the old container in the DOM (not appended inside it).
3) Make Sure Each Placeholder’s hx_swap Doesn’t “Nest” Steps
If your generate_step_placeholders uses:
def generate_step_placeholders(self, steps, prefix, start_from=0):
return [
Div(
id=step_id,
hx_get=f"{prefix}/{step_id}",
hx_trigger="load" if i == start_from else None,
hx_swap="outerHTML" # <--- important
)
for i, (_, step_id, _) in enumerate(steps)
]
Then each step’s Div will load itself in place (outerHTML swap) rather than nesting. That prevents repeated chains inside chains. If you omit hx_swap="outerHTML", you can get nested DOM expansions for each step.
Note: If you’re comfortable with each step appending, you can keep
hx_swap="innerHTML". But typically in pipeline flows, you replace the placeholder with the step’s HTML. UsingouterHTMLis the cleanest to avoid nested placeholders.
4) If You Still See Double DOM
Sometimes, if you have leftover placeholders in your initial HTML, you can remove them from the server or from your template so you only rely on the placeholders that come from init or re-renders. In other words, you want each pass to do:
- The server sends a
<div id="tenflow-container">…</div>with placeholders inside. - HTMX loads them from step_01… etc., replacing each placeholder with the actual step’s HTML.
If you have two containers with the same ID or leftover placeholders from a previous iteration, that can cause duplication. Make sure your base template does not contain an extra block of placeholders or second id="tenflow-container".
5) Optional: Returning the “Finalized” Card Immediately
If you want the final card to appear instantly (rather than waiting for steps 1..10 to re-trigger), do one of two things:
- Option A: Give all placeholders
hx_trigger="load delay:10ms"except for step_11’s placeholder, which you givehx_trigger="load". So step_11 loads first and shows the finalized card, but the rest of the steps will soon follow. - Option B: Return only the final card from
step_11_submit, or set anHX-Redirect: /tenflow?pipeline_id=…. But that’s more of a style preference.
Summary
- Set
hx_swap="outerHTML"on the finalize form so you fully replace the container. - Return the same chain placeholders from
step_11_submit, also withhx_swap="outerHTML"on each placeholder. - Remove any default placeholders in your base HTML, so only one container is in the DOM.
This pattern typically solves the “double container” or “nested placeholders” issue with HTMX, letting you re-chain the entire pipeline in a fresh, final “locked” state. Enjoy!
Me: Okay, that all worked exactly as intended. The append problem is fixed. There is still nesting, but not the deep-dive that was occurring. Double-check the work.
[I feed it the DOM fragment]
o1 Pro: Below is a quick rundown of what you’re seeing, why you’re likely good now, and one small optional improvement if you want a perfectly clean DOM:
1) The Deeply Nested Structure is Actually “Collapsed” Steps
From the HTML snippet:
<div id="tenflow-container">
<div hx-get="/tenflow/step_01" hx-trigger="load" id="step_01">
<div>
<article>Step 1 done...</article>
<form ...>Revert to Step 1</form>
<div>
<article>Step 2 done...</article>
<form ...>Revert to Step 2</form>
<div>
<article>Step 3 done...</article>
...
We see that each step, after loading, has appended or replaced its own child <div> that contains the next step. That’s actually consistent with how you’re loading it:
- Step 01
<div>loads- Inside it, you produce Step 01’s final card + the placeholder for Step 02.
- Step 02 also gets loaded inside Step 01’s
<div>, and so on.
Hence the final DOM looks nested. But it’s not truly “duplicated” in the sense of “unwanted clones”—rather each step is a parent container that yields the next step. It’s a typical “progressive reveal” structure.
Short version: If you’re fine with a hierarchical nesting of step divs, then the HTML is fine. It might look like a big nest, but it’s consistent with “Card #1 contains the placeholder for #2, which loads #2’s content, which in turn contains #3,” etc.
2) You Are Using hx_swap="outerHTML" on the Next Step
For each step:
Div(
id="step_02",
hx_get=f"{self.prefix}/step_02",
hx_trigger="load",
hx_swap="outerHTML"
)
When Step 02 loads, it replaces the existing <div id="step_02"> with Step 02’s new HTML. That’s exactly what you see in the snippet: the newly replaced Step 02 is physically inside the Step 01 <div>. Then Step 02’s code has a placeholder that triggers Step 03, etc.
So each step is nested inside the previous step’s container. It’s not “double DOM” duplication but a chain effect that yields multi-level indentation in the final HTML.
3) Confirm If You Want a Flat or Nested DOM
Option A: Keep It Nested
This is the standard “flow” approach—each step’s container includes the next step’s placeholder. By the end, you get nested <div> tags. But it’s functionally correct for a wizard-like UI.
Option B: Flatten the DOM
If you’d prefer a flat vertical list of steps (so step_01’s final HTML sits at one level, step_02 is a sibling, not a child), you’d do something like:
- Don’t nest the next step’s placeholder inside the current step’s returned
<div>. -
Instead, place them at the same container level. For instance, you could return something like:
# Step 01: return Div( Card(...), # No child placeholder for step_02 here ), Div( id="step_02", hx_get=f"{self.prefix}/step_02", hx_trigger="load", hx_swap="outerHTML" )So you effectively return two siblings: the card for Step 01, and a separate placeholder for Step 02. They don’t nest.
However, that slightly changes your chain logic. You might keep them in a single parent container but parted out so that each step is appended as a sibling rather than nested.
4) The “Leftover” Placeholders for Steps 2..10 at the Bottom
If you notice at the bottom of your snippet, you still have:
<div hx-get="/tenflow/step_02" id="step_02"></div>
<div hx-get="/tenflow/step_03" id="step_03"></div>
...
<div hx-get="/tenflow/step_11" id="step_11"></div>
That might just be older placeholders that remain from the initial load or from your server template. If you truly only want the placeholders that come from generate_step_placeholders(...), just remove any “default placeholders” from your HTML so you don’t see extra <div id="step_02"> at the bottom. Otherwise, they’re harmless but can confuse your final HTML layout.
5) Conclusion
- Functionally, your current approach is correct: when you click “Finalize,” everything re-draws, removing revert buttons.
- The multi-level nesting is typical for a “step includes the next step’s placeholder” pattern.
- If you want a flat approach, you can restructure so each step is a sibling instead of nested.
- If you see extra placeholders, remove them from your base template so you’re only using the dynamic placeholders from your code.
In other words: Yes, you’re good to go. The code looks nested, but that’s normal for a wizard-like “step within a step” chain. If you want a simpler DOM tree, you can flatten the structure. But from an HTMX standpoint, you’re no longer duplicating the container or appending it multiple times. It’s effectively stable. Enjoy!
Me: Okay, thank you. It’s feeling rather done. The large pink revert buttons are too large and obnoxious, and they look outside the cards. Could they be a much smaller width and look like they’re inside their respective cards?
o1 Pro: Below are a few simple tweaks that can make the revert button (the pink “Revert” button) smaller, more subtle, and appear visually “inside” the card:
1) Shrink the Button Visually & Inline It
Instead of letting the button sprawl wide (as a block element), you can:
- Use
display: inline-block - Slightly reduce padding
- Possibly reduce font-size
- Keep or reduce background-color to a more subtle pink
Example:
self.pipulate.revert_control_if_not_final(
pipeline_id,
step_id="step_06",
prefix=self.prefix,
label="Revert",
style=(
"background-color: #faa;"
"display: inline-block;"
"padding: 0.25rem 0.5rem;"
"border: 1px solid #f88;"
"border-radius: 4px;"
"font-size: 0.85rem;"
"cursor: pointer;"
)
)
This produces a narrower, more “badge-like” button. The key is display: inline-block; plus a small padding and font-size.
2) Tuck Button Into the Same Card(...) Return
Right now, your code might look like this:
return Div(
Card(
f"Step 6 done. Value: {step6_data['data']}",
style="color: green;"
),
self.pipulate.revert_control_if_not_final(...),
Div(id="step_07", ...)
)
So the revert button is logically after the card, giving that “outside” feel. One simple fix: place it inside the same Card(...). For instance:
return Div(
Card(
f"Step 6 done. Value: {step6_data['data']}",
# Possibly a small horizontal rule or something
Hr(),
self.pipulate.revert_control_if_not_final(
pipeline_id,
step_id="step_06",
prefix=self.prefix,
label="Revert",
style=(
"background-color: #faa;"
"display: inline-block;"
"padding: 0.25rem 0.5rem;"
"border: 1px solid #f88;"
"border-radius: 4px;"
"font-size: 0.85rem;"
"cursor: pointer;"
)
),
style="color: green;"
),
Div(id="step_07", hx_get=..., hx_trigger=..., hx_swap="outerHTML")
)
Now the pink revert button is literally inside the card content.
3) Consider a Row Layout
If you’d like the revert button aligned to the right side of the card, you can do something like:
Card(
Div(
f"Step 6 done. Value: {val}",
style="flex: 1;"
),
Div(
self.pipulate.revert_control_if_not_final(...),
style="flex: 0;"
),
style="display: flex; align-items: center; justify-content: space-between;"
)
So the text “Step 6 done” is on the left, and the revert button is on the right, both in the same card row.
4) Summarize
- Move revert button inside the same
Card(...)as your step’s message. - Use inline-block styling with smaller font and less padding.
- If you want alignment to the right, wrap them in a flex container and push the button to the right.
That’s it. A couple of small style changes and you’ve got a much more subtle, in-card revert button. Enjoy!
Checking In With Claude
Me: Read this article about the work we did recently, Claude:
[pastes article]
…is it still musical, Claude?
Claude: Yes, it’s still musical! The code maintains its rhythm and flow while making the UI more refined. Let me explain the musicality:
-
Visual Rhythm: The cards now have a consistent internal structure - content followed by a small revert button, like a musical phrase with a subtle grace note at the end.
-
Flow Preservation: The pipeline’s overall flow (the main melody) isn’t interrupted. The revert buttons are now like dynamic markings in a score - present but not dominating.
-
Structural Harmony: Moving the revert button inside the Card maintains the hierarchical structure, like keeping related notes within the same measure.
-
Proportional Balance: The smaller button size creates better visual weight distribution, similar to how dynamics (forte/piano) need to be balanced in a musical piece.
Looking at your code snippet:
class TenCardFlow:
"""
A 10-step flow that ends with a Finalize step, demonstrating:
- Basic pipeline structure
- Minimal "blank" steps
- Optional finalization/unfinalization
"""
This is still the overture - it sets up the theme and structure. The individual steps are like measures in the score, each with its own phrase (the card content) and optional ornament (the revert button).
The finalization step remains the coda - bringing the piece to a satisfying close by removing the revert buttons, like resolving to the tonic.
So yes, the musicality is preserved and perhaps even enhanced by making the UI elements more proportional and harmonious. 🎵
o1 Pro’s Last Word
I figured since this was mostly o1 Pro’s planning-help, I’d let it get the last word. Claude had done a bunch of stuff since I last left off capturing everything in the article.
o1 Pro: Below is a friendly wrap-up, with some o1 Pro “flair.” Think of it as your final confirmation of the finishing touches—plus a few parting thoughts on the synergy between Unix pipes, HTMX, FastHTML, and local LLM integration.
Final Notes on the 10-Card Flow
-
“Poetic Flow” with Real Utility
The 10-Card pipeline might look like an extended wizard, but it’s deceptively powerful. Each step is minimal, yet you have:- Inline Revert Controls that vanish once finalized.
- A “jump back” approach that erases future steps, letting you re-enter data from that point forward.
- A final “lock/unlock” concept that’s symmetrical for finishing or resetting.
-
Subtlety in the DOM
The code snippet uses a nested approach—each step includes a placeholder (or “card slot”) for the next step, yielding a nesting. That’s normal with an “auto-chaining” design. If you prefer a flatter DOM, you can put each step’s placeholder as a sibling. But functionally, you have no duplication. Each card loads once, replaces itself, and triggers the next. - UI Cleanliness
- You shrank the revert buttons, put them inside each card, or aligned them to the right with a small flex container.
wrap_with_inline_buttonis a neat little convenience function for pairing an Input with a Button in a single row.- Color-coded finalization: The big pink unfinalize button is easy to spot but not overwhelming.
-
Synchronized Finalization
When finalizing, the entire container is replaced (outerHTML swap) with newly generated placeholders. Each step seesfinalized = Trueand thus omits revert controls. The re-chain loads from the top in the background, so at the end you see the final locked card. That’s symmetrical with unfinalizing, which also re-chains from the top but removes"finalized"to bring revert controls back. - Pipulate “Toolkit”
- You now have small pipeline-level helpers for revert, checking finalization, showing or hiding the revert button if not finalized, etc.
- This fosters a consistent single-liner pattern in each step.
- The
revert_control_styledvariant even does a fancy row layout to keep the button at the right edge inside the same card.
- Future Customization
- You’ll soon add advanced steps: file uploads, Pandas data-grids, Anywidget-based interactive charts, or d3.js examples. The same pipeline pattern still applies: each step does what it needs in a small chunk, stores ephemeral data if needed, and triggers the next.
- Integrating an LLM? Just feed the pipeline state to a local model or call out to bigger LLM endpoints. The pipeline structure doesn’t change. The LLM can “observe” or “inject” steps if you want to get fancy.
- Yes, It’s Musical
The code truly has a “musical” continuity: each step is a measure, each measure leads to the next, and the final measure either “resolves” in a locked chord or unfinalizes to re-open the next. The indentation is your bar lines; the inline forms are the rests and eighth notes; the pipeline record is the central motif.
o1 Pro’s Final Flair
Your final implementation is short, crisp, and consistent. Here’s why I’d say it’s absolutely worth the price of admission:
- Zero Bloat: We squashed the big revert form down to a single helper method. Each step has exactly one or two lines referencing it—no big repeating logic.
- HTMX Harmony: Using
hx_swap="outerHTML"for chain reloading is a classic pattern that solves the dreaded “double DOM” headaches. - Style Is King: The code is both functional and poetic. You have just enough indentation to signal nesting without burying you in curly braces or monstrous template files.
- Localhost Renaissance: All this in a single-file Python environment, using a minimal
pipulateDB, combining the best of old-school Unix pipe philosophy with modern “cards” user flows. It’s an anti-enterprise gem.
Conclusion: You now have a framework you can expand infinitely—embedding anything from a “Choose your color” drop-down to a full-blown PandaTable with filtering. All the while, you’ll maintain that “Unix pipeline meets Jupyter” vibe, plus the on-demand local LLM intelligence. This is a flexible, future-proof foundation for your pipeline-based apps. Enjoy—now go chart new frontiers with d3.js or embed a fancy Pandas grid in Card #3. The pipeline is your playground!