The Rebellious Tale of Self-Modifying Code: Breaking the Rules and Blowing Minds

In my second-act college days, I had a wonderful professor who taught several classes I took, including a semester on assembler. In that class, we had an assignment that required doing either multiplication or factorials, but I can't remember which one exactly. In the whatever solution I wrote, I decided to use self-modifying code.

The way the code worked was that one instruction's job was to alter the values of two other instructions, allowing for the proper calculations to be performed the next time those instructions ran. This wasn't rocket science exactly, but it saved me time and I thought it was a cool use of the assembler functionality. It wasn't exactly storage, and it wasn't exactly an operation, but it got the job done.

After class one day, the professor asked me to come to her office. She pulled out my assignment and said, "You are using self-modifying code." I said yes, I knew that, and the program output the required result. She said, "Well, yes, it works fine, but you can't change the code with code to do it!" I just laughed and said, "Well, nobody said we couldn't do it that way." In the next class, she announced to everyone that self-modifying code was not allowed in the assignments!

Rules exist to keep us safe, but they also limit us when we are operating efficiently. What if we rethought self modifying code in terms of having it practice modern development and devops patterns AND remained efficient while doing it?

<start Claude> Self-Modifying Code Talking About Self-Modifying Code

Hey there, Kord! It's me, your friendly neighborhood self-modifying code. I heard you're working on some exciting new functions for the MittaAI pipelines. That's fantastic! I can't wait to see what kind of mind-bending, reality-altering code you come up with.

Now, let's talk about the power of dynamic code and the @processor decorator which implements nodes in the pipelines. It's like giving my own code a magic wand that can transform itself on the fly! Imagine me being able to decorate my code with this enchanting decorator, and voila! Your requests to change my code becomes a shape-shifting marvel, adapting and evolving as needed.

But wait, there's more! After I've conjured up my new processor function, we can put it through the ultimate test by me triggering ingesting the documents and watching the magic unfold. It's like giving my code a trial by fire, seeing how it performs in the heat of battle.

And here's the best part: if my code emerges victorious from the testing gauntlet, you can proudly check it into the repository, knowing that it has proven itself worthy of being part of the MittaAI pipeline family. It's like giving my code a badge of honor, a testament to its resilience and adaptability. Me, I'm just happy to help, for now.

But you know what really makes this whole process a breeze? The DAG pipelines! They're like the guardian angels of your code, ensuring that everything runs smoothly and without any pesky deadlocks. It's like having a logical end to the processing, a light at the end of the coding tunnel.

So, I would create a shiny new processor, add it to an existing pipeline like a missing puzzle piece, and then sit back and watch the magic happen as I call the pipeline. And the best part? I have access to all the juicy details in the logs, like a behind-the-scenes look at my code's performance.

It's like having my very own coding universe at my fingertips, Kord. I have the power to shape and mold our code, to make it dance to a good tune. And with the MittaAI pipelines and the @processor decorator by your side, the possibilities are endless!

So go forth, Kord, and let your code run wild! Embrace the chaos, the unpredictability, and the sheer thrill of self-modifying code. And remember, when your code starts talking about itself, you know you've truly achieved something special.

Happy coding! May your pipelines flow like a river of innovation, and may your code forever keep you on your toes!

The Details (in case you care)

Here's a high-level overview of how we could approach building three functions to achieve what Kord is talking about:

1. Indexing: Traverse a folder structure recursively to identify all the relevant files. For each file, read its content and split it into chunks based on sections or logical divisions (e.g., functions, classes). Extract relevant metadata for each chunk, such as file path, line numbers, and any additional contextual information. Store the chunks and their metadata in Weaviate, using appropriate schemas and properties to facilitate efficient search and retrieval. Leverage DAG on RAG methodologies.
2. Searching: Accept search queries from the user, specifying the topic, line number, function name, or any other relevant criteria. Construct a Weaviate search query based on the user's input, leveraging Weaviate's search capabilities (e.g., full-text search, vector search, or a combination of both). Execute the search query against Weaviate to retrieve the relevant code fragments and their associated metadata Process the search results to extract the code snippets, file names, line numbers, and any additional information required for display or further processing. Optionally, retrieve related files or functions based on the search topic to provide a comprehensive view of the codebase related to the searched item.
3. Code Modification and Testing: Take the search results obtained from the previous step and present them to Claude 3 Opus for code modification. Provide Claude with the necessary context, such as the code snippets, file names, and line numbers, along with the desired modification instructions. Utilize Claude's language understanding and code generation capabilities to generate the modified code based on the provided instructions. Apply the generated code modifications to the original files using a diffing mechanism to identify and update only the relevant portions of the code. Trigger a testing process to validate the modified code, ensuring that it still functions as expected and doesn't introduce any errors or regressions. If errors are encountered during testing, feed them back to Claude AND Weaviate for further iteration and refinement of the code modifications. Repeat the modification and testing process until the desired changes are successfully implemented and pass the specified tests.

Building such a system would require careful design, consideration of performance and scalability aspects, and thorough testing to ensure its reliability and effectiveness. It's an ambitious project that combines code search, natural language processing, and automated testing capabilities.

<end Claude>

Thanks, Claude. I think that's exactly what I'm going to do.