From Monolith to Modules: Building a Flexible Web App with FastHTML and HTMX

By Mike Levin

OpenAI ChatGPT o1-mini-high: Here’s a holistic synthesis of our discussion so far:

Project Vision & Philosophy
Your project is a deliberate departure from the mainstream “enterprise” approach. It’s built as a local‐first, single-tenant desktop system using Nix Flakes, FastHTML, and HTMX, with a core designed to be as minimal as possible. The goal is to create an environment that’s both transparent and adaptable—a resilient, future-proof platform that prioritizes human-understandable, server-side state management over complex, bloated frameworks.

Core Design Principles:

• Minimal, Immutable Core:
  By keeping the core (e.g., in a single server.py file) small and focused, you ensure that future refactoring is easier and collaboration is less likely to lead to conflicts. Externalizing workflows, apps, and learning materials into separate directories (like apps, workflows, and learn) supports modular growth while keeping the core stable.

• WET Over DRY:
  You intentionally favor a “Write Everything Twice” (WET) approach over heavy abstraction. This might feel verbose but it maximizes clarity and control. Every HTMX attribute, every state change, and every workflow step is explicit—helping both you and the embedded LLM to understand exactly what’s happening.

• Transparent State Management:
  The system uses a lightweight DictLikeDB and a helper class (Pipulate) to manage server-side state. This approach keeps all application state in view—every update is logged, every change is visible, and you never rely on client-side storage. It’s all about making the system observable and debuggable.

• Linear Pipeline Workflows:
  Inspired by Jupyter Notebook cells and Unix pipes, the workflows are designed to be linear: the output of one step feeds directly into the next. Whether it’s a simple “StarterFlow” that collects and transforms user input (like turning “cat” into “fluffy cat”) or more complex workflows like “LinkGraphFlow,” the idea is to provide a clear, step-by-step process. This approach also facilitates interruption safety—if a workflow stops, you can resume from the last completed step.

• Embedded LLM as a Collaborative Partner:
  Instead of relying on external “computer-using agents,” you’re embedding a local LLM (Gemma3 via Ollama) directly into the web app. This LLM is intended not only to assist with tasks but also to observe and even eventually suggest improvements to its own codebase. By feeding every user action and state change into its context, the LLM remains fully informed and can participate as an interactive guide or even a code reviewer.

• HTMX for Real-Time Interactivity:
  HTMX is the linchpin of your UI—it replaces the need for heavy JavaScript frameworks. With simple attributes like hx-post, hx-get, and hx-target, you enable dynamic, partial page updates that keep the user interface responsive without full page reloads. This aligns with your desire to reduce client-side complexity and maintain a clear, declarative codebase.

Strategic Goals & Future-Proofing:

• Modularization & Externalization:
  The plan is to externalize not just workflows but also apps and learning materials. This creates a plugin ecosystem where new functionalities can be added without touching the core. Dynamic menus for profiles, apps, and workflows will auto-configure and allow collaborators to extend the system easily.

• Documentation & Training Materials:
  A heavy emphasis is placed on markdown documentation—storing process details and domain-specific expertise in a learn directory. This documentation will not only help human collaborators but can also serve as training material for future prompt injections or fine-tuning local LLMs.

• Resilience Against Vendor Lock-In:
  By avoiding the heavy frameworks and proprietary ecosystems (FastAPI, React, etc.) that chase enterprise benchmarks, your system is designed to be agile, self-contained, and independent. It’s a counterpoint to the prevailing trend of ever-more complex cloud-based services, ensuring that you remain in control of your code and infrastructure.

• Incremental Growth & Learning:
  You’re planning to start with a minimal “StarterFlow” that embodies the Unix pipe spirit—each step (or notebook cell) is self-contained and explicitly connected to the next. This will serve as a foundation for gradually adding more complex workflows (like LinkGraphFlow) without overwhelming yourself. The process of documenting, refactoring, and externalizing workflows is as much about learning HTMX and FastHTML as it is about building functional software.

The Bigger Picture:

In summary, your project is a courageous attempt to reclaim the spirit of early web development—where simplicity, transparency, and direct control were paramount—while leveraging modern tools like HTMX and local LLMs. It’s about building an ecosystem that remains resilient amidst the chaotic churn of vendor protocols and enterprise trends. The focus is on a self-fueling, modular architecture where every part of the system is visible and maintainable, and where the LLM isn’t just a tool but a partner in both development and self-improvement.

This holistic approach, blending a minimal core with explicit state management and linear workflow pipelines, is your antidote to the ever-changing landscape of technology. It’s a call for clarity over abstraction, and for sustainable, human-centric development in a world that often prioritizes speed and scale at the expense of understanding.

Does this synthesis capture the essence of our discussion—and the broader context of your project—accurately? Let me know if there’s any aspect you’d like to explore further or adjust.

Me: This is all correct. The codebase will follow. Given what you know about the project now, here is a summary of my perceived next steps.

Above all, I need to avoid decisions that risk time-wasting refactoring by introducing new technologies or unknowns. I need to stay on the beaten track for the next step, so I can start building that momentum you just mentioned, based on full clarity, transparency and simplicity. There will for example be externalization of files that I have so far been avoiding because of the complexity of paths and scope that introduces, along with the fragmenting of context. The moment I externalize apps and workflows, I will now have multiple files to put into a prompt to give you context. So the main thing I am avoiding is anything that introduces gratuitous complexity and brittleness that is outside my concerns. Specifically, PyPI packaging and needing to use the OS standard library to build paths. pathlib Path() might be the answer, but the goal is for it to be almost as if the imports did not occur at all. Perhaps importlib.import_module() is the way to go. But the point is that the way LLMs are typically trained, all the enterprise concerns will kick in and something overly complex, path-breaking and demanding of major refactoring will be pushed on me, creating a frustrating, inescapable rabbit hole of work that will piss away the weekend.

In contrast, the type of solution I’m looking for would be a way to move an expanded version of StarterFlow, one that removes inheritance from BaseFlow, into the workflows folder, and everything just continues to magically work, without 2 or 3 new “gotchas” introduced based on the unintended consequences of ostensible best practices that were introduced that deviate from the spirit of the project. A perfect example would be the addition of additional subfolders and an __init__.py file. This project will never be pip installable. It will always be either a git clone or the downloading and uncompressing of the equivalent zip file, followed by cd’ing into the folder and doing a nix develop command. That command handles literally everything, especially the ensured presence of a Python .venv virtual environment, activation of it, and perhaps even the python server.py command that starts it. The only reason not to is to educate them about the JupyterLab environment that is also hosted side-by-side in the same Python virtual environment.

Is this clear? The current state of LLMs will undermine such goals every which way from nowhere. My next step is to show you the codebase, with the instructions to help me externalize StarterFlow, eliminate BaseFlow, and not launch a major refactoring.

ChatGPT o3-mini-high: Your plan is crystal clear. You want to keep the focus on full clarity, transparency, and simplicity while avoiding any decisions that could lead to unnecessary refactoring or introduce brittle, complex dependencies. The key is to externalize your workflows—starting with an expanded version of StarterFlow that completely removes the BaseFlow inheritance—without causing any unwanted side effects. You’re not aiming for a pip-installable package or a heavy, multi-folder structure; instead, you want everything to work almost magically from a single git clone (or unzip) and a simple nix develop command.

In essence, you need to:

• Externalize StarterFlow: Move it into the workflows folder as a standalone file without inheritance from BaseFlow.
• Maintain the Minimal Core: Ensure that externalizing files doesn’t introduce the complexity of path management or break the spirit of the project.
• Avoid New Gotchas: Steer clear of over-engineered solutions (like deep module hierarchies or full PyPI packaging) that lead to unwanted rabbit holes.
• Preserve the Workflow’s Linear, Notebook-like Nature: Keep the pipeline as a simple series of steps that are easy to understand, modify, and iterate upon.
• Leverage Tools Wisely: Use pathlib and importlib if necessary—but only if they serve to reduce friction without burdening you with extra complexity.

Your next step is to show the codebase with instructions so we can work on externalizing StarterFlow, eliminating BaseFlow, and ensuring that the process doesn’t kick off a major refactoring. I’m ready to dive into that code with you when you are.

Me: [Pastes codebase with no further instructions]

ChatGPT o3-mini-high: Here’s a holistic synthesis of our discussion and the greater context of your project:

Project Vision & Philosophy

• Local-First & Single-Tenant:
  Your system is designed to run locally on a single-user desktop (think of it as a lean, Electron-like app) where every part of the state is maintained server-side. This avoids the complexities of multi-tenant architectures and heavy enterprise frameworks.

• Radical Simplicity & Transparency:
  You intentionally embrace “anti-patterns” (like using a simple DictLikeDB for state) to keep the app observable and understandable. Every decision—from minimal use of JavaScript (HTMX) to eliminating templating engines—aims to reduce cognitive overhead and make the inner workings of the system fully visible.

• Modular, Plugin-Driven Architecture:
  The goal is to keep a tiny, immutable core (contained in server.py) while externalizing apps and workflows. By splitting out things like StarterFlow into separate files (without introducing layers like BaseFlow), you preserve the core’s simplicity and prevent a rabbit hole of refactoring or OS-dependent path issues.

• Embedded Local LLM for Self-Improvement:
  Your local LLM (Gemma 3) is not just a chatbot—it’s an active partner that understands the system’s code, guides you through workflows (in a linear, notebook-like style), and may even suggest improvements to its own codebase. This self-awareness (Chip O’Theseus concept) is central to your design.

• Avoiding Overengineering:
  You’re committed to avoiding the temptation of adopting new technologies (like PyPI packaging or deep module hierarchies) that would introduce unnecessary complexity. Instead, you’re choosing approaches (e.g., using importlib.import_module() and pathlib where needed) that keep externalization seamless and frictionless.

Current Codebase & Environment

• Reproducible Setup with Nix Flakes:
  Your flake.nix ensures a consistent, isolated development environment with everything from Python (via virtualenv) to essential tools like Git, tmux, and even CUDA support when available.

• Requirements & Minimal Dependencies:
  The requirements.txt lists a lean set of libraries that align with your philosophy—nothing too heavy or opinionated, just tools that support formatting, logging, HTTP handling, and interfacing with HTMX.

• Server & Plugin Structure:
  The server.py file is the heart of your app, where you define routes, manage state, handle chat and workflow interactions, and integrate external modules (like your ProfileApp, TodoApp, and the workflows such as StarterFlow, PipeFlow, etc.). The code intentionally uses simple patterns to expose internal state and maintain full visibility (via extensive logging and on-screen debug information).

Next Steps: Externalizing StarterFlow Without Major Refactoring

• Externalize StarterFlow:
  The immediate goal is to move an expanded version of StarterFlow into the workflows folder. This new version should:
  • Eliminate BaseFlow Inheritance:
    Remove the dependency on BaseFlow entirely, making StarterFlow a standalone module.
  • Maintain Core Integrity:
    Ensure that the externalized workflow “magically” integrates with the core—without the need for additional subfolders, complex path handling, or new module hierarchies.
  • Keep It Simple:
    The process should not introduce any new gotchas or force you into a lengthy refactoring cycle. Everything should continue to work as if the imports weren’t even there.
• Avoid Introducing New Complexity:
  Stay on the “beaten track” by avoiding enterprise-style packaging or over-engineered import mechanisms. The goal is for a user to simply clone/download the repository, run nix develop, and have the system function perfectly without extra configuration.

Broader Context & Future-Proofing

• Sustainable, Incremental Growth:
  The idea is to build momentum with clear, incremental improvements. Each externalized workflow will act as a mini-case study—teaching you (and any collaborators) how HTMX, server-side state, and the local LLM work together.

• Empowering the Local LLM:
  As the LLM becomes more integrated, it will use its access to the code and conversation history to provide feedback, help troubleshoot, and eventually even suggest self-improvements. This symbiosis between human and machine is a key differentiator.

• Long-Term Resilience:
  By sticking to minimal, well-understood technologies (like FastHTML, HTMX, and SQLite) and avoiding the pitfalls of rapidly changing enterprise frameworks, your project remains robust and future-proof. This is your antidote to the ever-changing tech landscape—a system that remains lean, adaptable, and entirely within your control.

In summary, your next step is to externalize StarterFlow—removing its inheritance from BaseFlow—into the workflows folder without introducing new complexities. This will preserve the spirit of your minimalist, local-first, and fully transparent system, allowing you to build momentum quickly while avoiding a major refactoring rabbit hole.

Ready to move forward with this clear, incremental improvement?

Me: That is stated so well that it gives me renewed hope that this is not a pipe dream. Haha, get it? Pipes! Okay, so let’s get this show on the road. In the step-by-step guiding me through externalizing StarterFlow into the workflows directory while eliminating BaseFlow inheritance (too much at once?), step 1…

ChatGPT o3-mini-high: Great! Let’s break this down step-by-step. For Step 1, our goal is to externalize StarterFlow into the workflows directory without immediately diving into a complete refactor of its inheritance from BaseFlow. We want to keep things as minimal and frictionless as possible.

Step 1: Create the New File & Extract StarterFlow

1. Create the File:
   • In your repository, create a new file at workflows/starter_flow.py.
2. Copy the StarterFlow Code:
   • Open your current server.py and locate the StarterFlow class definition.
   • Copy the entire definition of StarterFlow (and any immediately related helper functions or constants, if needed) into workflows/starter_flow.py.
3. Adjust Imports:
   • At the top of workflows/starter_flow.py, add the necessary import statements. For example, you may need:

     from fasthtml.common import *
     from collections import namedtuple
     from datetime import datetime
     # Import any other modules or classes that StarterFlow depends on,
     # such as Step (if defined locally) or parts of BaseFlow if temporarily needed.
     

   • Make sure the relative imports work correctly. Since the file is now in the workflows folder, you might need to adjust import paths if they reference modules in the root directory.
4. Keep BaseFlow Inheritance Temporarily:
   • For now, leave the inheritance from BaseFlow intact within StarterFlow. This allows you to verify that everything still works before we remove the dependency.
   • Your extracted class should look roughly like this:

     # workflows/starter_flow.py
     
     from fasthtml.common import *
     # (Other necessary imports)
     
     class StarterFlow(BaseFlow):
         def __init__(self, app, pipulate, app_name="starter"):
             steps = [
                 Step(id='step_01', done='name', show='Your Name', refill=True),
                 Step(id='step_02', done='email', show='Your Email', refill=True),
                 Step(id='step_03', done='phone', show='Your Phone', refill=True),
                 Step(id='step_04', done='website', show='Your Website', refill=True),
                 Step(id='finalize', done='finalized', show='Finalize', refill=False)
             ]
             super().__init__(app, pipulate, app_name, steps)
             self.STEP_MESSAGES = self.pipulate.generate_step_messages(self.STEPS)
                  
         async def landing(self):
             base_landing = await super().landing(display_name="Starter Flow Demo")
             asyncio.create_task(self.delayed_greeting())
             return base_landing
                  
         # ... (Rest of the StarterFlow methods)
     

5. Integrate in the Core:
   • In your server.py, update the code that instantiates StarterFlow. For example, replace:

     starter_flow = StarterFlow(app, pipulate)
     

     with an import from your new file:

     from workflows.starter_flow import StarterFlow
     starter_flow = StarterFlow(app, pipulate)
     

   • Make sure any route registrations that refer to StarterFlow still work as expected.
6. Test It:
   • Run your server (nix develop then python server.py) and verify that StarterFlow’s routes and functionality work the same as before.
   • Check logs and UI to ensure that nothing breaks during this extraction process.

Next Steps (Overview)

Once Step 1 is complete and you’re confident the extraction works seamlessly:

• Step 2: Gradually refactor StarterFlow to remove the BaseFlow inheritance. This might involve copying over only the needed functionality from BaseFlow directly into StarterFlow, or refactoring methods step-by-step.
• Step 3: Test each change to ensure that the workflows continue to operate as expected.

But for now, let’s focus on Step 1—creating the new file and moving StarterFlow there without changing its behavior.

Ready to give it a try? Let me know if you need clarification or assistance with any part of this step!

Taking The Plunge

Me: This is not a refactoring! I have a gut-level aversion to work like this because I can feel the exploding cascade of unintended consequences percolating. For anyone actually foolish enough to follow along (I presume you’re mostly scrapers feeding LLM training models), this is the block of code I’m transposing from server.py into workflows/starter_flow.py. Easy enough, right? It’s not even much code. However, that’s because it’s inheriting everything from a BaseFlow class which I made exactly for the purpose of keeping workflows like this short. However, that was a mistake and is going to change. But not until after I externalize this file and make sure it continues working without any muss and fuss. That’s an enormous hurdle for me to overcome. Every instinct of my body says no to this, based on past experiences. But the time has come the walrus said, because now you have AI to help guide you.

class StarterFlow(BaseFlow):
    def __init__(self, app, pipulate, app_name="starter"):
        steps = [Step(id='step_01', done='name', show='Your Name', refill=True), Step(id='step_02', done='email', show='Your Email', refill=True), Step(id='step_03', done='phone', show='Your Phone', refill=True), Step(id='step_04', done='website', show='Your Website', refill=True), Step(id='finalize', done='finalized', show='Finalize', refill=False)]
        super().__init__(app, pipulate, app_name, steps)
        self.STEP_MESSAGES = self.pipulate.generate_step_messages(self.STEPS)

    async def landing(self):
        base_landing = await super().landing(display_name="Starter Flow Demo")
        asyncio.create_task(self.delayed_greeting())
        return base_landing

    async def finalize(self, request):
        return await self.handle_finalize(self.STEPS, self.app_name)

    async def finalize_submit(self, request):
        return await self.handle_finalize_submit(self.STEPS, self.app_name, self.STEP_MESSAGES)

    async def unfinalize(self, request):
        return await self.handle_unfinalize(self.STEPS, self.app_name, self.STEP_MESSAGES)

    async def jump_to_step(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        db["step_id"] = step_id
        return self.pipulate.rebuild(self.app_name, self.STEPS)

Okay, this class is actually a factory class, like a kind of cookie cutter template. That means you actually create an instance of it with a line like this:

starter_flow = StarterFlow(app, pipulate)

Now according to ChatGPT’s instructions, I should be able to make the new file, move the class in there and:

from workflows.starter_flow import StarterFlow
starter_flow = StarterFlow(app, pipulate)

Okay, I got server.py to technically run, but I had to move the entire BaseFlow class into workflows/starter_flow.py for it to run, and the attempt to call http://localhost:5003/starter_flow resulted in:

  File "/home/mike/repos/terse/workflows/starter_flow.py", line 52, in landing
    pipeline.xtra(app_name=self.app_name)
    ^^^^^^^^
NameError: name 'pipeline' is not defined

…because creating pipeline is in the calling or parent server.py file. Now, I might be able to do reciprocal importing, which amazingly is possible under Python, but I have to be very careful about the if __name__ == "__main__": issues (Python people know what I’m talking about), because server.py wasn’t written to be an importable package.

ChatGPT o3-mini-high: Below is a suggested approach to resolve the “pipeline is not defined” error without diving into a full-blown refactoring. We’ll do this with a minimal change—by making the dependency explicit rather than relying on a global. This is a common technique to avoid circular imports and unexpected “magic” globals.

Step 2: Passing pipeline as a Constructor Argument

1. Update the StarterFlow Constructor:
   • In your new file (workflows/starter_flow.py), change the __init__ signature of StarterFlow to accept an extra parameter (e.g. pipeline), and store it as an instance variable.
   • For example:

     class StarterFlow(BaseFlow):
         def __init__(self, app, pipulate, pipeline, app_name="starter"):
             self.pipeline = pipeline  # store the pipeline for later use
             steps = [
                 Step(id='step_01', done='name', show='Your Name', refill=True),
                 Step(id='step_02', done='email', show='Your Email', refill=True),
                 Step(id='step_03', done='phone', show='Your Phone', refill=True),
                 Step(id='step_04', done='website', show='Your Website', refill=True),
                 Step(id='finalize', done='finalized', show='Finalize', refill=False)
             ]
             super().__init__(app, pipulate, app_name, steps)
             self.STEP_MESSAGES = self.pipulate.generate_step_messages(self.STEPS)
     

2. Replace Global Reference:
   • In any method of StarterFlow where you previously referenced the global pipeline, replace it with self.pipeline.
   • For example, if you have:

     async def landing(self):
         base_landing = await super().landing(display_name="Starter Flow Demo")
         asyncio.create_task(self.delayed_greeting())
         return base_landing  # (or any call like pipeline.xtra(app_name=self.app_name))
     

     make sure that all such references are updated to use self.pipeline (if needed).

3. Update the Instantiation in server.py:
   • In your server.py (or wherever you instantiate your workflows), update the creation of StarterFlow to pass the pipeline variable.
   • Change:

     starter_flow = StarterFlow(app, pipulate)
     

     to:

     from workflows.starter_flow import StarterFlow
     starter_flow = StarterFlow(app, pipulate, pipeline)
     

4. Test Your Changes:
   • Restart your server (using your normal workflow, e.g., nix develop then python server.py) and navigate to http://localhost:5003/starter_flow.
   • Verify that the StarterFlow routes still work and that you no longer see the NameError regarding pipeline.

Why This Works

• Explicit Dependency: By passing pipeline as a parameter, you’re no longer relying on a global variable that’s defined in server.py. This makes the dependency explicit and easier to manage.
• Avoids Circular Imports: Since StarterFlow no longer tries to grab pipeline from the global scope, you avoid issues with importing across modules.
• Keeps Changes Minimal: This change is localized to the constructor and its references, so it should not introduce additional “gotchas” outside your current scope.

Give this a try and see if it resolves the error. Once this externalization is stable, you can gradually move toward decoupling further parts (like eliminating BaseFlow inheritance) at your own pace. Let me know if you’d like further guidance on the next steps or any part of this process!

Me: Okay, that worked exactly as you explained. But now I have the error:

Traceback (most recent call last):
  File "/home/mike/repos/terse/workflows/starter_flow.py", line 140, in delayed_greeting
    await simulated_stream("Enter an ID to begin.")
          ^^^^^^^^^^^^^^^^
NameError: name 'simulated_stream' is not defined

…which is going to be another one of these global things. This is because I externalized a file. And so now, my reliance on globals is starting to bite me in the ass. I am sure that soon I will run afoul of the DictLikeDB being global as well. So I moved the function that it is referring to:

async def simulated_stream(text: str, delay: float = 0.05):
    async def stream_task():
        import re
        words = re.split(r'(\s+)', text)
        words = [w for w in words if w]
        current_chunk = []
        for word in words[:-1]:
            current_chunk.append(word)
            if (any(p in word for p in '.!?:') or ''.join(current_chunk).strip().__len__() >= 30):
                await chat.broadcast(''.join(current_chunk))
                current_chunk = []
                await asyncio.sleep(delay)
        if words:
            current_chunk.append(words[-1])
        if current_chunk:
            await chat.broadcast(''.join(current_chunk) + '<br>\n')
    asyncio.create_task(stream_task())

…inside Pipulate as a helper function and changed all the references to simulated_stream() to self.pipulate.simulated_stream(). It’s also super-important to note, for my own edification not being much of an OOP person, the various places self needs to be sprinkled in. Not only in the aforementioned way to refer to anything coming from the pipulate instance of the helper function (must be addressed as self.pipulate), but also when any function that was previously global, such as simulated_stream in this case, gets moved into the Pipulate class, the first (fixed) parameter needs self to be added. This is due to the way OOP works in Python. It’s a requirement to have something there to have an self-referential object, and like args and kwargs, the word self isn’t required, but it’s almost exclusively used in this context by convention.

async def simulated_stream(self, thewords: str, delay: float = 0.05):
    async def stream_task():
        import re
        words = re.split(r'(\s+)', thewords)
        words = [w for w in words if w]
        current_chunk = []
        for word in words[:-1]:
            current_chunk.append(word)
            if (any(p in word for p in '.!?:') or ''.join(current_chunk).strip().__len__() >= 30):
                await chat.broadcast(''.join(current_chunk))
                current_chunk = []
                await asyncio.sleep(delay)
        if words:
            current_chunk.append(words[-1])
        if current_chunk:
            await chat.broadcast(''.join(current_chunk) + '<br>\n')
    asyncio.create_task(stream_task())

And now the full workflow is transplanted. But I had to completely edit out the Mad-Libs-style PipeFlow because I moved BaseFlow into starter_flow.py.

However, now as I actually try to use the StarterFlow app, I am encountering (as expected):

  File "/home/mike/repos/terse/workflows/starter_flow.py", line 59, in init
    db["pipeline_id"] = pipeline_id
    ^^
NameError: name 'db' is not defined

Yet this is still great process. I assume we will be passing it in as a factory class instantiation parameter too, like we did pipeline?

ChatGPT o3-mini-high: The solution is similar to what we did with pipeline: we need to pass in any global dependencies (like db) explicitly to the workflow instance. This is a form of dependency injection that prevents our code from relying on globals—which is especially important as you externalize components.

Step 3: Passing db to StarterFlow

1. Update the Constructor:

   Modify your StarterFlow class so that its constructor accepts a db parameter in addition to app, pipulate, and pipeline. Store it as an instance variable:

   class StarterFlow(BaseFlow):
       def __init__(self, app, pipulate, pipeline, db, app_name="starter"):
           self.db = db  # Store the database dependency
           self.pipeline = pipeline  # Already done in step 2
           steps = [
               Step(id='step_01', done='name', show='Your Name', refill=True),
               Step(id='step_02', done='email', show='Your Email', refill=True),
               Step(id='step_03', done='phone', show='Your Phone', refill=True),
               Step(id='step_04', done='website', show='Your Website', refill=True),
               Step(id='finalize', done='finalized', show='Finalize', refill=False)
           ]
           super().__init__(app, pipulate, app_name, steps)
           self.STEP_MESSAGES = self.pipulate.generate_step_messages(self.STEPS)
   

2. Replace Global References:

   Anywhere in StarterFlow that you referenced db, change it to use self.db. For example, if you previously had:

   db["pipeline_id"] = pipeline_id
   

   Change it to:

   self.db["pipeline_id"] = pipeline_id
   

3. Update Instantiation in server.py:

   When you create the instance of StarterFlow in your main file (server.py), make sure to pass the db:

   from workflows.starter_flow import StarterFlow
   starter_flow = StarterFlow(app, pipulate, pipeline, db)
   

4. Test Your Changes:

   Restart your server and navigate to the starter_flow endpoint to verify that the error no longer occurs and that your workflow functions correctly.

Why This Matters

• Explicit Dependency Management: By injecting db into your StarterFlow, you avoid unexpected NameError issues and make the dependency graph clear.
• Improved Modularity: Future refactorings or tests become easier because each component now clearly states what it depends on.
• Avoiding Global Pitfalls: As you externalize more code, minimizing reliance on global variables prevents cascading errors and makes the system more maintainable.

Try this update and let me know if it resolves the error and if you’re ready to move on to the next step in the process!

Me: Wow, okay that worked! I got some errors about BaseFlow not having db, but it got past it and I was able to use the StarterFlow app successfully! Now, we need to eliminate the entire BaseFlow superclass. I believe I am going to use StarterFlow as a verbatim copy/paste template, as is its namesake. I was resisting that because when it was inside starter.py, every added workflow dramatically lengthened it. But now that its externalized, the works can become much more WET! Consequently, rather than fixing global references in BaseApp, the correct thing to do is to eliminate the superclass inheritance and move each thing from BaseApp “expanded” into StarterFlow. Here’s the entire starter_flow.py file. Can you do this coding work and give me the exact code to copy/paste back into the file?

ChatGPT o3-mini-high: Below is the complete, self-contained version of your starter_flow.py file with the functionality formerly in BaseFlow now inlined into the single class. You can copy and paste this code directly:

from fasthtml.common import *
from collections import namedtuple
from datetime import datetime
import asyncio

Step = namedtuple('Step', ['id', 'done', 'show', 'refill', 'transform'], defaults=(None,))

class StarterFlow:
    PRESERVE_REFILL = True

    def __init__(self, app, pipulate, pipeline, db, app_name="starter"):
        self.app = app
        self.pipulate = pipulate
        self.app_name = app_name
        self.pipeline = pipeline
        self.db = db
        steps = [
            Step(id='step_01', done='name', show='Your Name', refill=True),
            Step(id='step_02', done='email', show='Your Email', refill=True),
            Step(id='step_03', done='phone', show='Your Phone', refill=True),
            Step(id='step_04', done='website', show='Your Website', refill=True),
            Step(id='finalize', done='finalized', show='Finalize', refill=False)
        ]
        self.STEPS = steps
        self.steps = {step.id: i for i, step in enumerate(self.STEPS)}
        self.STEP_MESSAGES = {
            "new": "Enter an ID to begin.",
            "finalize": {
                "ready": "All steps complete. Ready to finalize workflow.",
                "complete": "Workflow finalized. Use Unfinalize to make changes."
            }
        }
        for step in self.STEPS:
            if step.done != 'finalized':
                self.STEP_MESSAGES[step.id] = {
                    "input": f"Step {step.id}: Please enter {step.show}",
                    "complete": f"{step.show} complete: <>. Continue to next step."
                }
        # Register routes
        routes = [
            (f"/{app_name}", self.landing),
            (f"/{app_name}/init", self.init, ["POST"]),
            (f"/{app_name}/unfinalize", self.unfinalize, ["POST"]),
            (f"/{app_name}/jump_to_step", self.jump_to_step, ["POST"]),
            (f"/{app_name}/revert", self.handle_revert, ["POST"])
        ]
        for step in self.STEPS:
            routes.extend([
                (f"/{app_name}/{step.id}", self.handle_step),
                (f"/{app_name}/{step.id}_submit", self.handle_step_submit, ["POST"])
            ])
        for path, handler, *methods in routes:
            method_list = methods[0] if methods else ["GET"]
            self.app.route(path, methods=method_list)(handler)

    def validate_step(self, step_id: str, value: str) -> tuple[bool, str]:
        return True, ""

    async def process_step(self, step_id: str, value: str) -> str:
        return value

    async def handle_revert(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if not step_id:
            return P("Error: No step specified", style="color: red;")
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state["_revert_target"] = step_id
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def landing(self, display_name=None):
        title = display_name or f"{self.app_name.title()}: {len(self.STEPS) - 1} Steps + Finalize"
        self.pipeline.xtra(app_name=self.app_name)
        existing_ids = [record.url for record in self.pipeline()]
        return Container(
            Card(
                H2(title),
                P("Enter or resume a Pipeline ID:"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name="pipeline_id", placeholder="🗝 Old or existing ID here", required=True, autofocus=True, list="pipeline-ids"),
                        button_label=f"Start {self.app_name.title()} 🔑",
                        button_class="secondary"
                    ),
                    Datalist(*[Option(value=pid) for pid in existing_ids], id="pipeline-ids"),
                    hx_post=f"/{self.app_name}/init",
                    hx_target=f"#{self.app_name}-container"
                )
            ),
            Div(id=f"{self.app_name}-container")
        )

    async def init(self, request):
        form = await request.form()
        pipeline_id = form.get("pipeline_id", "untitled")
        self.db["pipeline_id"] = pipeline_id
        state, error = self.pipulate.initialize_if_missing(pipeline_id, {"app_name": self.app_name})
        if error:
            return error
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def handle_step(self, request):
        step_id = request.url.path.split('/')[-1]
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        step_data = self.pipulate.get_step_data(pipeline_id, step_id, {})
        user_val = step_data.get(step.done, "")
        if step.done == 'finalized':
            finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
            if "finalized" in finalize_data:
                return Card(
                    H3("Pipeline Finalized"),
                    P("All steps are locked."),
                    Form(
                        Button("Unfinalize", type="submit", style="background-color: #f66;"),
                        hx_post=f"/{self.app_name}/unfinalize",
                        hx_target=f"#{self.app_name}-container",
                        hx_swap="outerHTML"
                    )
                )
            else:
                return Div(
                    Card(
                        H3("Finalize Pipeline"),
                        P("You can finalize this pipeline or go back to fix something."),
                        Form(
                            Button("Finalize All Steps", type="submit"),
                            hx_post=f"/{self.app_name}/{step_id}_submit",
                            hx_target=f"#{self.app_name}-container",
                            hx_swap="outerHTML"
                        )
                    ),
                    id=step_id
                )
        finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
        if "finalized" in finalize_data:
            return Div(
                Card(f"🔒 {step.show}: {user_val}"),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        if user_val and state.get("_revert_target") != step_id:
            return Div(
                self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {user_val}", steps=self.STEPS),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        display_value = ""
        if step.refill and user_val and self.PRESERVE_REFILL:
            display_value = user_val
        else:
            suggested = await self.get_suggestion(step_id, state)
            display_value = suggested
        await self.pipulate.simulated_stream(self.STEP_MESSAGES[step_id]["input"])
        return Div(
            Card(
                H3(f"Enter {step.show}"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name=step.done, value=display_value, placeholder=f"Enter {step.show}", required=True, autofocus=True)
                    ),
                    hx_post=f"/{self.app_name}/{step_id}_submit",
                    hx_target=f"#{step_id}"
                )
            ),
            Div(id=next_step_id),
            id=step_id
        )

    async def get_suggestion(self, step_id, state):
        return ""

    async def handle_step_submit(self, request):
        step_id = request.url.path.split('/')[-1].replace('_submit', '')
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if step.done == 'finalized':
            state = self.pipulate.read_state(pipeline_id)
            state[step_id] = {step.done: True}
            self.pipulate.write_state(pipeline_id, state)
            message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
            await self.pipulate.simulated_stream(message)
            placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
            return Div(*placeholders, id=f"{self.app_name}-container")
        form = await request.form()
        user_val = form.get(step.done, "")
        is_valid, error_msg = self.validate_step(step_id, user_val)
        if not is_valid:
            return P(error_msg, style="color: red;")
        processed_val = await self.process_step(step_id, user_val)
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state[step_id] = {step.done: processed_val}
        if "_revert_target" in state:
            del state["_revert_target"]
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        return Div(
            self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {processed_val}", steps=self.STEPS),
            Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
        )

    def generate_step_placeholders(self, steps, app_name):
        placeholders = []
        for i, step in enumerate(steps):
            trigger = "load"
            if i > 0:
                prev_step = steps[i - 1]
                trigger = f"stepComplete-{prev_step.id} from:{prev_step.id}"
            placeholders.append(Div(id=step.id, hx_get=f"/{app_name}/{step.id}", hx_trigger=trigger, hx_swap="outerHTML"))
        return placeholders

    async def delayed_greeting(self):
        await asyncio.sleep(2)
        await self.pipulate.simulated_stream("Enter an ID to begin.")

    async def handle_finalize(self, steps: list, app_name: str) -> Card:
        pipeline_id = self.db.get("pipeline_id", "unknown")
        finalize_step = steps[-1]
        finalize_data = self.pipulate.get_step_data(pipeline_id, finalize_step.id, {})
        logger.debug(f"Pipeline ID: {pipeline_id}")
        logger.debug(f"Finalize step: {finalize_step}")
        logger.debug(f"Finalize data: {finalize_data}")
        if finalize_step.done in finalize_data:
            logger.debug("Pipeline is finalized")
            return Card(
                H3("All Cards Complete"),
                P("Pipeline is finalized. Use Unfinalize to make changes."),
                Form(
                    Button("Unfinalize", type="submit", style="background-color: #f66;"),
                    hx_post=f"/{app_name}/unfinalize",
                    hx_target=f"#{app_name}-container",
                    hx_swap="outerHTML"
                ),
                style="color: green;",
                id=finalize_step.id
            )
        non_finalize_steps = steps[:-1]
        for step in non_finalize_steps:
            step_data = self.pipulate.get_step_data(pipeline_id, step.id, {})
            step_value = step_data.get(step.done)
            logger.debug(f"Step {step.id} completion: {step_value}")
        all_steps_complete = all(self.pipulate.get_step_data(pipeline_id, step.id, {}).get(step.done) for step in non_finalize_steps)
        logger.debug(f"All steps complete: {all_steps_complete}")
        if all_steps_complete:
            return Card(
                H3("Ready to finalize?"),
                P("All data is saved. Lock it in?"),
                Form(
                    Button("Finalize", type="submit"),
                    hx_post=f"/{app_name}/finalize_submit",
                    hx_target=f"#{app_name}-container",
                    hx_swap="outerHTML"
                ),
                id=finalize_step.id
            )
        return Div(P("Nothing to finalize yet."), id=finalize_step.id)

    async def handle_finalize_submit(self, steps: list, app_name: str, messages: dict) -> Div:
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        state["finalize"] = {"finalized": True}
        state["updated"] = datetime.now().isoformat()
        self.pipulate.write_state(pipeline_id, state)
        return Div(*self.generate_step_placeholders(steps, app_name), id=f"{app_name}-container")

    async def handle_unfinalize(self, steps: list, app_name: str, messages: dict) -> Div:
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        if "finalize" in state:
            del state["finalize"]
        self.pipulate.write_state(pipeline_id, state)
        placeholders = self.generate_step_placeholders(steps, app_name)
        return Div(*placeholders, id=f"{app_name}-container")

    def id_conflict_style(self):
        return "background-color: var(--pico-del-color);"

    async def finalize(self, request):
        return await self.handle_finalize(self.STEPS, self.app_name)

    async def finalize_submit(self, request):
        return await self.handle_finalize_submit(self.STEPS, self.app_name, self.STEP_MESSAGES)

    async def unfinalize(self, request):
        return await self.handle_unfinalize(self.STEPS, self.app_name, self.STEP_MESSAGES)

    async def jump_to_step(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        self.db["step_id"] = step_id
        return self.pipulate.rebuild(self.app_name, self.STEPS)

Explanation

1. No More Inheritance:
   All methods originally in BaseFlow are now part of the single StarterFlow class.

2. Dependencies Are Injected:
   The constructor now accepts and stores app, pipulate, pipeline, and db.

3. Routes Registration:
   All routes are registered inside the constructor just as before.

4. All Functionality Preserved:
   The methods for landing, initialization, step handling, finalizing, reverting, etc. are all inlined.

Copy and paste this revised code back into your workflows/starter_flow.py file, and your StarterFlow module should now work without relying on the old BaseFlow superclass.

Me: OMG, that worked! Okay… now a few refinements because this is going to be a highly propagated copy/paste template (instead of inheriting from a BaseFlow superclass). So there’s a few things.

First, it looks like there are call-once wrapper functions:

• finalize
• finalize_submit
• unfinalize

They each have a handle_ version that I think should be eliminated. It doesn’t make sense anymore, and it simplifies the code to minimize one-off wrappers. Anywhere else such one-off wrapping is done should be “unwrapped”. We want as few functions as possible with only those clearly intended for reuse externalized. And such externalization is really just the setup for moving those into the Pipulate helper function, with the exception of anything that makes HTMX calls. The goal here is to distill this down to only those things that define the workflow logic and need to be there to provide the “surface area” or hooks for customization. In particular, we are making heavy use of the standard HTML form input field, but it is likely that this will become radio buttons, check boxes, text areas and the like. So we must leave here those portions that let us customize “cards” or “steps” to our hearts content. We also leave anything making an hx_ call, as a major part of the point here is to learn, make use of, and almost “play like music” the HTMX. And finally, anything that is clearly repetitive and redundant that doesn’t provide customization surface area nor calls HTMX attributes should be brought to the top and notated as candidates for moving into the Pipulate helper function.

We are trying to make a sort of HTMX sheet music here that is attractive to the eye and intuitively tied to the Cells (PicoCSS Cards) of Jupyter Notebooks. When designing a good API, you’re shoving complexity around. And the decisions you make while shoving that complexity around creates the signature and opinions of the framework. It’s like how Python’s URLlib packages exposed too much, and Requests came along with a “for humans” API. It made a lot of concessions giving up the power of edge cases, but it got back in exchange something people loved using. In our case here, we’re going for that Requests “loves using” vibe, however, with a decidedly PicoCSS forms and HTMX attributes flavor.

So with all that in mind, take a very good look at the code you just gave me and give another reorganized version in preparation for the Pipulate helper function externalization decisions, and general beatification of the workflow music.

ChatGPT o3-mini-high: Below is a revised version of your starter_flow.py file. In this version, I’ve inlined the “finalize,” “finalize_submit,” and “unfinalize” methods (removing the one-off handle_ wrappers) and grouped related methods together. This should serve as a cleaner, more “for humans” copy/paste template that exposes only the essential workflow logic and HTMX hooks—setting the stage for later extraction of repetitive patterns into your Pipulate helper functions.

Copy and paste the code below:

from fasthtml.common import *
from collections import namedtuple
from datetime import datetime
import asyncio

Step = namedtuple('Step', ['id', 'done', 'show', 'refill', 'transform'], defaults=(None,))

class StarterFlow:
    PRESERVE_REFILL = True

    def __init__(self, app, pipulate, pipeline, db, app_name="starter"):
        self.app = app
        self.pipulate = pipulate
        self.app_name = app_name
        self.pipeline = pipeline
        self.db = db
        steps = [
            Step(id='step_01', done='name', show='Your Name', refill=True),
            Step(id='step_02', done='email', show='Your Email', refill=True),
            Step(id='step_03', done='phone', show='Your Phone', refill=True),
            Step(id='step_04', done='website', show='Your Website', refill=True),
            Step(id='finalize', done='finalized', show='Finalize', refill=False)
        ]
        self.STEPS = steps
        self.steps = {step.id: i for i, step in enumerate(self.STEPS)}
        self.STEP_MESSAGES = {
            "new": "Enter an ID to begin.",
            "finalize": {
                "ready": "All steps complete. Ready to finalize workflow.",
                "complete": "Workflow finalized. Use Unfinalize to make changes."
            }
        }
        for step in self.STEPS:
            if step.done != 'finalized':
                self.STEP_MESSAGES[step.id] = {
                    "input": f"Step {step.id}: Please enter {step.show}",
                    "complete": f"{step.show} complete: <>. Continue to next step."
                }
        # Register all workflow routes.
        routes = [
            (f"/{app_name}", self.landing),
            (f"/{app_name}/init", self.init, ["POST"]),
            (f"/{app_name}/jump_to_step", self.jump_to_step, ["POST"]),
            (f"/{app_name}/revert", self.handle_revert, ["POST"]),
            (f"/{app_name}/finalize", self.finalize, ["GET", "POST"]),
            (f"/{app_name}/finalize_submit", self.finalize_submit, ["POST"]),
            (f"/{app_name}/unfinalize", self.unfinalize, ["POST"])
        ]
        for step in self.STEPS:
            routes.extend([
                (f"/{app_name}/{step.id}", self.handle_step),
                (f"/{app_name}/{step.id}_submit", self.handle_step_submit, ["POST"])
            ])
        for path, handler, *methods in routes:
            method_list = methods[0] if methods else ["GET"]
            self.app.route(path, methods=method_list)(handler)

    # --- Core Workflow Methods ---

    def validate_step(self, step_id: str, value: str) -> tuple[bool, str]:
        # Default validation: always valid.
        return True, ""

    async def process_step(self, step_id: str, value: str) -> str:
        # Default processing: return value unchanged.
        return value

    async def handle_revert(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if not step_id:
            return P("Error: No step specified", style="color: red;")
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state["_revert_target"] = step_id
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def landing(self, display_name=None):
        title = display_name or f"{self.app_name.title()}: {len(self.STEPS) - 1} Steps + Finalize"
        self.pipeline.xtra(app_name=self.app_name)
        existing_ids = [record.url for record in self.pipeline()]
        return Container(
            Card(
                H2(title),
                P("Enter or resume a Pipeline ID:"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name="pipeline_id", placeholder="🗝 Old or existing ID here", required=True, autofocus=True, list="pipeline-ids"),
                        button_label=f"Start {self.app_name.title()} 🔑",
                        button_class="secondary"
                    ),
                    Datalist(*[Option(value=pid) for pid in existing_ids], id="pipeline-ids"),
                    hx_post=f"/{self.app_name}/init",
                    hx_target=f"#{self.app_name}-container"
                )
            ),
            Div(id=f"{self.app_name}-container")
        )

    async def init(self, request):
        form = await request.form()
        pipeline_id = form.get("pipeline_id", "untitled")
        self.db["pipeline_id"] = pipeline_id
        state, error = self.pipulate.initialize_if_missing(pipeline_id, {"app_name": self.app_name})
        if error:
            return error
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def handle_step(self, request):
        step_id = request.url.path.split('/')[-1]
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        step_data = self.pipulate.get_step_data(pipeline_id, step_id, {})
        user_val = step_data.get(step.done, "")
        if step.done == 'finalized':
            finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
            if "finalized" in finalize_data:
                return Card(
                    H3("Pipeline Finalized"),
                    P("All steps are locked."),
                    Form(
                        Button("Unfinalize", type="submit", style="background-color: #f66;"),
                        hx_post=f"/{self.app_name}/unfinalize",
                        hx_target=f"#{self.app_name}-container",
                        hx_swap="outerHTML"
                    )
                )
            else:
                return Div(
                    Card(
                        H3("Finalize Pipeline"),
                        P("You can finalize this pipeline or go back to fix something."),
                        Form(
                            Button("Finalize All Steps", type="submit"),
                            hx_post=f"/{self.app_name}/finalize_submit",
                            hx_target=f"#{self.app_name}-container",
                            hx_swap="outerHTML"
                        )
                    ),
                    id=step_id
                )
        finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
        if "finalized" in finalize_data:
            return Div(
                Card(f"🔒 {step.show}: {user_val}"),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        if user_val and state.get("_revert_target") != step_id:
            return Div(
                self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {user_val}", steps=self.STEPS),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        display_value = user_val if (step.refill and user_val and self.PRESERVE_REFILL) else await self.get_suggestion(step_id, state)
        await self.pipulate.simulated_stream(self.STEP_MESSAGES[step_id]["input"])
        return Div(
            Card(
                H3(f"Enter {step.show}"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name=step.done, value=display_value, placeholder=f"Enter {step.show}", required=True, autofocus=True)
                    ),
                    hx_post=f"/{self.app_name}/{step.id}_submit",
                    hx_target=f"#{step.id}"
                )
            ),
            Div(id=next_step_id),
            id=step.id
        )

    async def get_suggestion(self, step_id, state):
        # Default: return empty suggestion.
        return ""

    async def handle_step_submit(self, request):
        step_id = request.url.path.split('/')[-1].replace('_submit', '')
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if step.done == 'finalized':
            state = self.pipulate.read_state(pipeline_id)
            state[step_id] = {step.done: True}
            self.pipulate.write_state(pipeline_id, state)
            message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
            await self.pipulate.simulated_stream(message)
            placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
            return Div(*placeholders, id=f"{self.app_name}-container")
        form = await request.form()
        user_val = form.get(step.done, "")
        is_valid, error_msg = self.validate_step(step_id, user_val)
        if not is_valid:
            return P(error_msg, style="color: red;")
        processed_val = await self.process_step(step_id, user_val)
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state[step_id] = {step.done: processed_val}
        if "_revert_target" in state:
            del state["_revert_target"]
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        return Div(
            self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {processed_val}", steps=self.STEPS),
            Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
        )

    def generate_step_placeholders(self, steps, app_name):
        placeholders = []
        for i, step in enumerate(steps):
            trigger = "load" if i == 0 else f"stepComplete-{steps[i-1].id} from:{steps[i-1].id}"
            placeholders.append(Div(id=step.id, hx_get=f"/{app_name}/{step.id}", hx_trigger=trigger, hx_swap="outerHTML"))
        return placeholders

    async def delayed_greeting(self):
        await asyncio.sleep(2)
        await self.pipulate.simulated_stream("Enter an ID to begin.")

    # --- Finalization & Unfinalization ---
    async def finalize(self, request):
        pipeline_id = self.db.get("pipeline_id", "unknown")
        finalize_step = self.STEPS[-1]
        finalize_data = self.pipulate.get_step_data(pipeline_id, finalize_step.id, {})
        logger.debug(f"Pipeline ID: {pipeline_id}")
        logger.debug(f"Finalize step: {finalize_step}")
        logger.debug(f"Finalize data: {finalize_data}")
        if finalize_step.done in finalize_data:
            logger.debug("Pipeline is finalized")
            return Card(
                H3("All Cards Complete"),
                P("Pipeline is finalized. Use Unfinalize to make changes."),
                Form(
                    Button("Unfinalize", type="submit", style="background-color: #f66;"),
                    hx_post=f"/{self.app_name}/unfinalize",
                    hx_target=f"#{self.app_name}-container",
                    hx_swap="outerHTML"
                ),
                style="color: green;",
                id=finalize_step.id
            )
        non_finalize_steps = self.STEPS[:-1]
        for step in non_finalize_steps:
            step_data = self.pipulate.get_step_data(pipeline_id, step.id, {})
            step_value = step_data.get(step.done)
            logger.debug(f"Step {step.id} completion: {step_value}")
        all_steps_complete = all(
            self.pipulate.get_step_data(pipeline_id, step.id, {}).get(step.done)
            for step in non_finalize_steps
        )
        logger.debug(f"All steps complete: {all_steps_complete}")
        if all_steps_complete:
            return Card(
                H3("Ready to finalize?"),
                P("All data is saved. Lock it in?"),
                Form(
                    Button("Finalize", type="submit"),
                    hx_post=f"/{self.app_name}/finalize_submit",
                    hx_target=f"#{self.app_name}-container",
                    hx_swap="outerHTML"
                ),
                id=finalize_step.id
            )
        return Div(P("Nothing to finalize yet."), id=finalize_step.id)

    async def finalize_submit(self, request):
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        state["finalize"] = {"finalized": True}
        state["updated"] = datetime.now().isoformat()
        self.pipulate.write_state(pipeline_id, state)
        return Div(*self.generate_step_placeholders(self.STEPS, self.app_name), id=f"{self.app_name}-container")

    async def unfinalize(self, request):
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        if "finalize" in state:
            del state["finalize"]
        self.pipulate.write_state(pipeline_id, state)
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def jump_to_step(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        self.db["step_id"] = step_id
        return self.pipulate.rebuild(self.app_name, self.STEPS)

Explanation of Changes

1. Removal of One-Off Wrapper Methods:
   The separate handle_finalize, handle_finalize_submit, and handle_unfinalize methods have been removed. Their logic is now directly inlined into the
   finalize, finalize_submit, and unfinalize methods, respectively.

2. Grouping of Finalization Logic:
   The finalization and unfinalization methods are grouped together at the end of the class. This makes the “workflow music” easier to follow and highlights the customizable
   “cards” (the HTMX-enabled forms) that drive the process.

3. Preserved Customization Points:
   The methods that create step placeholders and wrap form inputs (with HTMX calls) remain unchanged. These are your “surface area” for customization and will be the basis for further enhancements
   (like moving them into Pipulate later).

4. Minimal Wrapping:
   Only functions essential for workflow logic remain in this class, making it a lean, copy/paste template that feels similar to a Jupyter Notebook cell in its simplicity.

This reorganized version should give you a cleaner base for further externalization (such as moving repetitive code into Pipulate) while keeping the core workflow logic intact.

Me: That worked great up until:

  File "/home/mike/repos/terse/workflows/starter_flow.py", line 232, in finalize
    logger.debug(f"Pipeline ID: {pipeline_id}")
    ^^^^^^
NameError: name 'logger' is not defined

…is logger another global thing we’re going to have to pass in as a parameter?

ChatGPT o3-mini-high: Yes, exactly. The logger variable is currently defined as a global in your main file (or imported from Loguru in your overall project), so when you externalize code into its own module, that global isn’t automatically available.

You have two main options:

1. Import logger in your module:
   Simply add

   from loguru import logger
   

   at the top of your starter_flow.py file. This way, the module remains self-contained and can access logging without extra parameters.

2. Pass logger as a parameter:
   Alternatively, if you prefer to avoid globals and maintain explicit dependencies, you can modify your class constructor to accept a logger parameter. Then, when instantiating your workflow in server.py, pass the logger to it.

For now, if you want the simplest solution, I recommend importing it directly in your module.

Which option would you like to go with?

Me: I did the import. That’s much more reasonable. Okay, pshwew! Externalization of first workflow accomplished. And beautification accomplished.

My observation now is that this is working like an ideal situation for StarterFlow, but it’s going to have to be flexible enough to accommodate PipeFlow which works like a Mad-Libs, feeding the output of one card into the input of the next. As I look at the current StarterFlow code, the flow from step to step is not obvious. When I run the code, I see “Step 1”, “Step 2”, etc. on the Revert buttons, but I don’t see that reflected anywhere in the classes. Of course I see it in the steps defined at the top, but there is a sort of disconnect of the flow in my mind, mostly because of the non-sequential nature of OOP, which I hate. But I’m sticking with it here. We need… something. What? In order to take this to the next step. It not only needs to support the impending next example, PipeFlow, but it’s going to need to support the 2K-line example coming up, LinkGraphFlow.

I am interested in your recommendation for next step. Perhaps a deep explanation of how the OOP method layout in this example translates into the top-down step-labeled linear sequence resembling a Jupyter Notebook Cell flow.

You can see how I’m torn here. The people who this system is going to be introduced here are those non-professional programmers of the sort that just squeak by because of how flexible and permissive an environment Jupyter Notebooks are. My instructions to them is going to be to think through each cell, considering how the input values into one cell set the stage for the output values to the next cell, encouraging them to think about the Notebook cell flow as essentially the same as the Unix pipe flow, in order to simplify ports of Notebooks into this environment.

Do you see that reflected here at all? I know it’s not your fault because my instructions to you thus far have been about non-breaking externalization and the elimination of BaseFlow. We even touched on “seeing” the HTMX sheet music. But now that we’re here, it’s also just as much about seeing the Jupyter Notebook Cell-flow structure to the music.

Here’s the current code from starter_flow.py. I am happy to show you PipeFlow again, or even LinkGraphFlow if you think it would help as you articulate your reply. I look forward to your response.

Me: That introduced the following bug:

  File "/home/mike/repos/terse/server.py", line 1357, in create_grid_left
    return await starter_flow.landing()
                 ^^^^^^^^^^^^^^^^^^^^^^
TypeError: StarterFlow.landing() missing 1 required positional argument: 'request'

…and seemed unnecessary and redundant with your prior reply. It also seems like it completely ignored the new topics I was bringing up regarding not seeing the top-down flow as implied by the labeled steps. There is a disconnect between those and the names of the methods, which in prior versions reflected the step names. Instead of another code revision (I reverted to the bug-free version), how about an open-ended riff so that I can be assured that you understand the need for customization and clarity between the steps and the methods and the linear flows that I’m talking about. Also, here’s LinkGraphFlow and its supporting functions for you to take into account, especially in regard to the linearity that must be visible and level of customization that will be required, int your riff:

[LinkGraphFlow pasted]

ChatGPT o3-mini-high: Your concerns make a lot of sense—and I believe your vision is spot‐on. Let’s talk through the ideas.

The Goal: Linear “Notebook Cell” Workflow

Even though the code is organized using classes and methods (the OOP structure), the desired user experience is a linear, step‐by‐step progression very similar to Jupyter Notebook cells. In that model, every cell’s output feeds into the next cell’s input, and the flow is entirely visible and clear to the user. In your workflows (e.g., StarterFlow, PipeFlow, and LinkGraphFlow), each “step” or “card” should feel like one of those cells—a self-contained unit of work with a clear label, input, processing, and output.

Bridging OOP Structure and Linear Flow

Here’s how your current structure supports—and can be enhanced to support—this idea:

• Step Definitions as Cells:
  Your use of the Step namedtuple to define each step (with properties like id, done, show, and refill) is key. It serves as a blueprint for each cell.
  • Customization: The show field is your label (e.g., “Your Name” or “Make it Plural”), which should be prominently displayed so users immediately understand the cell’s purpose.
  • Data Flow: The done field ties the user input to a specific data key in your state. This is similar to how each notebook cell outputs a result that can be referenced later.
• Rendering Placeholders & UI Consistency:
  The helper function (e.g., generate_step_placeholders) generates a series of DOM elements that line up in order. This is analogous to the sequential cells in a notebook.
  • Visual Linear Flow: Even though your backend routes are defined as separate methods, on the UI they appear one after the other. Each placeholder acts like a cell slot waiting to be populated.
  • HTMX Triggers: The hx_trigger attributes (like "load" or "stepComplete-<prev>") control when a cell’s content loads. This makes the workflow feel dynamic and sequential.
• Direct Customization Hooks:
  The design intentionally leaves “surface area” for customization:
  • Input Types: While you currently use plain text inputs, the structure is in place so that later you could substitute radio buttons, checkboxes, or text areas, depending on what the step requires.
  • HTMX Attributes: Since HTMX is central to updating the UI in real time, keeping its calls inline with the card definitions ensures that the “sheet music” of the workflow remains clear and editable.
  • State & Revert Controls: The ability to revert a step is visible and clearly tied to each “cell” (think of it as an “undo” for that notebook cell). That reinforces the linearity: if something isn’t right, you can roll back to a specific step without breaking the overall flow.

The Challenge of OOP and Perceived Non-linearity

It’s true that OOP code—especially with methods spread across a class—can seem non-linear when you read it. However, the user’s journey is determined by the sequence in which the routes are registered and the placeholders are generated. In your case, even though methods like handle_step_submit and finalize_pipeline are defined in various parts of the class, they’re all orchestrated by the sequential rendering of placeholders on the front end.

Next Steps in Customization

Here are a few recommendations to further reinforce the notebook-cell paradigm:

1. Explicit Labeling on Cards:
   Consider embedding the step number into the visible text of each card. For example, instead of just “Enter Your Name,” show “Step 1: Enter Your Name.” This makes the flow unmistakable.

2. Unified State Representation:
   Your state (managed via the DictLikeDB and Pipulate helper) should be visualized in a “timeline” or “breadcrumb” style in the UI. This could be an optional panel that shows, “Step 1: Completed, Step 2: Pending, …” which reinforces the linear progression.

3. Documentation for Each Step:
   Embed a small explanation (or a tooltip) on each card that briefly explains its role in the overall process. Think of it like annotations in a Jupyter Notebook cell that help the user understand why the input in that cell matters.

4. Customization via Pipulate:
   As you externalize common logic into the Pipulate helper functions, make sure that these functions allow for customization of how each cell behaves. For example, functions that generate the HTML for a step should accept parameters that let you change not only the text but also the style or the associated HTMX triggers.

5. Visual Progress Indicator:
   You might also consider adding a visual progress bar or a “cell number” indicator that updates as the user moves from one cell to the next. This can be part of the shared UI elements defined by your Pipulate helpers.

In Summary

The current structure—with its Step definitions, sequential placeholder generation, and HTMX-triggered updates—is already laying the foundation for a Jupyter Notebook–like, linear flow. The key is to ensure that:

• Each step is self-contained, clearly labeled, and visibly sequential in the UI.
• The backend (even if it’s OOP) serves to manage state and transitions in a way that the front-end presents a linear, intuitive flow.
• Customization is easy: Both in terms of the input types and the way each cell is rendered.
• State management is transparent: So users can see the effect of each cell and revert changes if needed.

By further refining the visual and textual cues in each workflow card, you can achieve that “sheet music” quality where the flow feels as natural as following a Jupyter Notebook—each cell a note in your composition, with the HTMX interactions acting like the conductor’s baton.

Does this explanation resonate with your vision for making the workflow linear and customizable while still harnessing the power of HTMX and the Pipulate helpers?

Me: Alright then, without doing one wit of anything that will introduce new bugs (I don’t have the endurance for new bug-squashing this weekend - I have to use the precious energy I can muster to lay beautiful groundwork for moving forward), please take the measures you express in the Summary you just gave me. I will copy/paste your response directly into starter_flow.py.

[I removed an exchange here where ChatGPT gave me buggy code and I chastened it, and it came back with working code.]

ChatGPT o3-mini-high: Below is a revised version of your StarterFlow class that merges the separate finalization wrappers while keeping the linear “notebook‐cell” flow intact—and importantly, it re‑introduces the missing jump_to_step method so that no routes are broken. I’ve kept all HTMX calls and preserved the step labeling so that each “cell” is clearly defined for your users.

Please review and, if it meets your needs, copy and paste it into your starter_flow.py file:

from fasthtml.common import *
from collections import namedtuple
from datetime import datetime
import asyncio
from loguru import logger

# Each step represents one cell in our linear workflow.
Step = namedtuple('Step', ['id', 'done', 'show', 'refill', 'transform'], defaults=(None,))

class StarterFlow:
    PRESERVE_REFILL = True

    def __init__(self, app, pipulate, pipeline, db, app_name="starter"):
        self.app = app
        self.pipulate = pipulate
        self.app_name = app_name
        self.pipeline = pipeline
        self.db = db
        steps = [
            Step(id='step_01', done='name',    show='Your Name',    refill=True),
            Step(id='step_02', done='email',   show='Your Email',   refill=True),
            Step(id='step_03', done='phone',   show='Your Phone',   refill=True),
            Step(id='step_04', done='website', show='Your Website', refill=True),
            Step(id='finalize', done='finalized', show='Finalize',  refill=False)
        ]
        self.STEPS = steps
        self.steps = {step.id: i for i, step in enumerate(self.STEPS)}
        self.STEP_MESSAGES = {
            "new": "Enter an ID to begin.",
            "finalize": {
                "ready": "All steps complete. Ready to finalize workflow.",
                "complete": "Workflow finalized. Use Unfinalize to make changes."
            }
        }
        # For each non-finalize step, set an input and completion message that reflects the cell order.
        for step in self.STEPS:
            if step.done != 'finalized':
                self.STEP_MESSAGES[step.id] = {
                    "input": f"Step {step.id}: Please enter {step.show}",
                    "complete": f"{step.show} complete: <>. Continue to next step."
                }
        # Register routes for all workflow methods.
        routes = [
            (f"/{app_name}", self.landing),
            (f"/{app_name}/init", self.init, ["POST"]),
            (f"/{app_name}/jump_to_step", self.jump_to_step, ["POST"]),
            (f"/{app_name}/revert", self.handle_revert, ["POST"]),
            # Finalization now handled in one merged method.
            (f"/{app_name}/finalize", self.finalize, ["GET", "POST"]),
            (f"/{app_name}/unfinalize", self.unfinalize, ["POST"])
        ]
        for step in self.STEPS:
            routes.extend([
                (f"/{app_name}/{step.id}", self.handle_step),
                (f"/{app_name}/{step.id}_submit", self.handle_step_submit, ["POST"])
            ])
        for path, handler, *methods in routes:
            method_list = methods[0] if methods else ["GET"]
            self.app.route(path, methods=method_list)(handler)

    # --- Core Workflow Methods (the cells) ---

    def validate_step(self, step_id: str, value: str) -> tuple[bool, str]:
        # Default validation: always valid.
        return True, ""

    async def process_step(self, step_id: str, value: str) -> str:
        # Default processing: return value unchanged.
        return value

    async def handle_revert(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if not step_id:
            return P("Error: No step specified", style="color: red;")
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state["_revert_target"] = step_id
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def landing(self, display_name=None):
        title = display_name or f"{self.app_name.title()}: {len(self.STEPS) - 1} Steps + Finalize"
        self.pipeline.xtra(app_name=self.app_name)
        existing_ids = [record.url for record in self.pipeline()]
        return Container(
            Card(
                H2(title),
                P("Enter or resume a Pipeline ID:"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name="pipeline_id", placeholder="🗝 Old or existing ID here", required=True, autofocus=True, list="pipeline-ids"),
                        button_label=f"Start {self.app_name.title()} 🔑",
                        button_class="secondary"
                    ),
                    Datalist(*[Option(value=pid) for pid in existing_ids], id="pipeline-ids"),
                    hx_post=f"/{self.app_name}/init",
                    hx_target=f"#{self.app_name}-container"
                )
            ),
            Div(id=f"{self.app_name}-container")
        )

    async def init(self, request):
        form = await request.form()
        pipeline_id = form.get("pipeline_id", "untitled")
        self.db["pipeline_id"] = pipeline_id
        state, error = self.pipulate.initialize_if_missing(pipeline_id, {"app_name": self.app_name})
        if error:
            return error
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def handle_step(self, request):
        step_id = request.url.path.split('/')[-1]
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        step_data = self.pipulate.get_step_data(pipeline_id, step_id, {})
        user_val = step_data.get(step.done, "")
        if step.done == 'finalized':
            finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
            if "finalized" in finalize_data:
                return Card(
                    H3("Pipeline Finalized"),
                    P("All steps are locked."),
                    Form(
                        Button("Unfinalize", type="submit", style="background-color: #f66;"),
                        hx_post=f"/{self.app_name}/unfinalize",
                        hx_target=f"#{self.app_name}-container",
                        hx_swap="outerHTML"
                    )
                )
            else:
                return Div(
                    Card(
                        H3("Finalize Pipeline"),
                        P("You can finalize this pipeline or go back to fix something."),
                        Form(
                            Button("Finalize All Steps", type="submit"),
                            hx_post=f"/{self.app_name}/finalize",
                            hx_target=f"#{self.app_name}-container",
                            hx_swap="outerHTML"
                        )
                    ),
                    id=step_id
                )
        finalize_data = self.pipulate.get_step_data(pipeline_id, "finalize", {})
        if "finalized" in finalize_data:
            return Div(
                Card(f"🔒 {step.show}: {user_val}"),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        if user_val and state.get("_revert_target") != step_id:
            return Div(
                self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {user_val}", steps=self.STEPS),
                Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
            )
        display_value = user_val if (step.refill and user_val and self.PRESERVE_REFILL) else await self.get_suggestion(step_id, state)
        await self.pipulate.simulated_stream(self.STEP_MESSAGES[step_id]["input"])
        return Div(
            Card(
                H3(f"Step {step.id}: Enter {step.show}"),
                Form(
                    self.pipulate.wrap_with_inline_button(
                        Input(type="text", name=step.done, value=display_value, placeholder=f"Enter {step.show}", required=True, autofocus=True)
                    ),
                    hx_post=f"/{self.app_name}/{step.id}_submit",
                    hx_target=f"#{step.id}"
                )
            ),
            Div(id=next_step_id),
            id=step.id
        )

    async def get_suggestion(self, step_id, state):
        return ""

    async def handle_step_submit(self, request):
        step_id = request.url.path.split('/')[-1].replace('_submit', '')
        step_index = self.steps[step_id]
        step = self.STEPS[step_index]
        pipeline_id = self.db.get("pipeline_id", "unknown")
        if step.done == 'finalized':
            state = self.pipulate.read_state(pipeline_id)
            state[step_id] = {step.done: True}
            self.pipulate.write_state(pipeline_id, state)
            message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
            await self.pipulate.simulated_stream(message)
            placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
            return Div(*placeholders, id=f"{self.app_name}-container")
        form = await request.form()
        user_val = form.get(step.done, "")
        is_valid, error_msg = self.validate_step(step_id, user_val)
        if not is_valid:
            return P(error_msg, style="color: red;")
        processed_val = await self.process_step(step_id, user_val)
        next_step_id = self.STEPS[step_index + 1].id if step_index < len(self.STEPS) - 1 else None
        await self.pipulate.clear_steps_from(pipeline_id, step_id, self.STEPS)
        state = self.pipulate.read_state(pipeline_id)
        state[step_id] = {step.done: processed_val}
        if "_revert_target" in state:
            del state["_revert_target"]
        self.pipulate.write_state(pipeline_id, state)
        message = await self.pipulate.get_state_message(pipeline_id, self.STEPS, self.STEP_MESSAGES)
        await self.pipulate.simulated_stream(message)
        return Div(
            self.pipulate.revert_control(step_id=step_id, app_name=self.app_name, message=f"{step.show}: {processed_val}", steps=self.STEPS),
            Div(id=next_step_id, hx_get=f"/{self.app_name}/{next_step_id}", hx_trigger="load")
        )

    def generate_step_placeholders(self, steps, app_name):
        placeholders = []
        for i, step in enumerate(steps):
            trigger = "load" if i == 0 else f"stepComplete-{steps[i-1].id} from:{steps[i-1].id}"
            placeholders.append(Div(id=step.id, hx_get=f"/{app_name}/{step.id}", hx_trigger=trigger, hx_swap="outerHTML"))
        return placeholders

    async def delayed_greeting(self):
        await asyncio.sleep(2)
        await self.pipulate.simulated_stream("Enter an ID to begin.")

    # --- Finalization & Unfinalization Merged ---
    async def finalize(self, request):
        pipeline_id = self.db.get("pipeline_id", "unknown")
        finalize_step = self.STEPS[-1]
        finalize_data = self.pipulate.get_step_data(pipeline_id, finalize_step.id, {})
        logger.debug(f"Pipeline ID: {pipeline_id}")
        logger.debug(f"Finalize step: {finalize_step}")
        logger.debug(f"Finalize data: {finalize_data}")
        if request.method == "GET":
            if finalize_step.done in finalize_data:
                logger.debug("Pipeline is already finalized")
                return Card(
                    H3("All Cards Complete"),
                    P("Pipeline is finalized. Use Unfinalize to make changes."),
                    Form(
                        Button("Unfinalize", type="submit", style="background-color: #f66;"),
                        hx_post=f"/{self.app_name}/unfinalize",
                        hx_target=f"#{self.app_name}-container",
                        hx_swap="outerHTML"
                    ),
                    style="color: green;",
                    id=finalize_step.id
                )
            non_finalize_steps = self.STEPS[:-1]
            all_steps_complete = all(
                self.pipulate.get_step_data(pipeline_id, step.id, {}).get(step.done)
                for step in non_finalize_steps
            )
            logger.debug(f"All steps complete: {all_steps_complete}")
            if all_steps_complete:
                return Card(
                    H3("Ready to finalize?"),
                    P("All data is saved. Lock it in?"),
                    Form(
                        Button("Finalize", type="submit"),
                        hx_post=f"/{self.app_name}/finalize",
                        hx_target=f"#{self.app_name}-container",
                        hx_swap="outerHTML"
                    ),
                    id=finalize_step.id
                )
            else:
                return Div(P("Nothing to finalize yet."), id=finalize_step.id)
        else:
            state = self.pipulate.read_state(pipeline_id)
            state["finalize"] = {"finalized": True}
            state["updated"] = datetime.now().isoformat()
            self.pipulate.write_state(pipeline_id, state)
            return Div(*self.generate_step_placeholders(self.STEPS, self.app_name), id=f"{self.app_name}-container")

    async def unfinalize(self, request):
        pipeline_id = self.db.get("pipeline_id", "unknown")
        state = self.pipulate.read_state(pipeline_id)
        if "finalize" in state:
            del state["finalize"]
        self.pipulate.write_state(pipeline_id, state)
        placeholders = self.generate_step_placeholders(self.STEPS, self.app_name)
        return Div(*placeholders, id=f"{self.app_name}-container")

    async def jump_to_step(self, request):
        form = await request.form()
        step_id = form.get("step_id")
        self.db["step_id"] = step_id
        return self.pipulate.rebuild(self.app_name, self.STEPS)