Auto-Coder Config: Local Paths Take Priority!

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Auto-Coder Config: Local Paths Take Priority!_Hey guys, ever felt like your configuration files were playing hide-and-seek? Especially when you're jumping between different projects and trying to keep things neat? Well, get ready, because we're diving deep into a super important update for **Auto-Coder** that's going to make your life a whole lot easier! This isn't just a tiny tweak; it's a fundamental improvement to how *Auto-Coder* handles its brain — its configuration. We're talking about streamlining the entire `configuration loading` process, making it more intuitive, more powerful, and frankly, just *smarter*. The main goal here is to ensure that when you're working on a specific project, `Auto-Coder` understands that your local, project-specific settings should take precedence. This means less hassle, fewer headaches, and more time focusing on what you do best: coding awesome stuff! We're fixing the way `Auto-Coder` resolves where to load its settings from, moving towards a much more logical `path resolution` system. This means if you have a special configuration for your current project, `Auto-Coder` will find and use it first, before looking at your general settings. Imagine trying to use a specific set of tools for a unique task, but your toolkit keeps grabbing the default, general-purpose tools instead. Frustrating, right? This update is like teaching your toolkit to be *aware* of your immediate needs, prioritizing the right tools for the job at hand. This update is specifically designed to enhance your `developer workflow` by making `Auto-Coder` more adaptable to your immediate working environment. So, let's unpack this crucial change and see how it's going to make your `Auto-Coder` experience even smoother._## Why This Update Matters: Setting the Stage for Smarter Configs_Alright, let's be real for a sec. When you're building cool things with `Auto-Coder`, you often need to fine-tune its behavior. Maybe you're experimenting with different LLM backends for a particular project, or you've got specific API keys that are unique to one client's setup. The current `configuration loading` mechanism, while functional, could sometimes feel a bit rigid. It primarily looked for a global configuration in your `home directory`, which is `~/.auto-coder/llm_config.toml`. While this is great for a general, system-wide setup, it could become a bit of a juggling act when you needed *local configuration* to take precedence. Imagine you're working on Project A, which needs a specific LLM model config. Then you switch to Project B, which uses a completely different one. If `Auto-Coder` always defaults to your global home directory config, you'd have to constantly switch out files or manually specify paths every single time. That's not ideal, and it definitely breaks the flow!_This is precisely where this update shines. We're talking about making `Auto-Coder`'s `path resolution` more intelligent and context-aware. The problem we're solving is the potential for configuration conflicts or the inconvenience of repeatedly overriding global settings for local project needs. We're enhancing the `LLMBackendConfiguration.load_from_file()` method, which is essentially the gatekeeper for all your `Auto-Coder`'s backend settings. The goal is to prioritize a *local configuration* file over a global one when available. This means if you've got a `.auto-coder/llm_config.toml` file right there in your project directory, `Auto-Coder` will know to grab that one first. Think about it: this drastically improves the `developer experience` by allowing you to have truly isolated project settings. No more accidental global config overrides messing up your local experiments! This change is all about giving you more control and making `Auto-Coder` adapt to *your* project structure, rather than the other way around. It's a small code change with a massive impact on daily usage, moving us towards a much more `flexible and intuitive configuration` system for `Auto-Coder` users everywhere._## Diving Deep into the Problem: The Old Way (and Why It's Getting an Upgrade)_Let's zoom in on the specific challenge we're tackling, guys. Before this awesome update, the `LLMBackendConfiguration.load_from_file()` method, which is the heart of how *Auto-Coder* finds and loads its backend settings, had a fairly straightforward approach to `config loading issues`. If you didn't explicitly tell it where your configuration file was, it would typically fall back to a default location. This default was almost always your `home directory config`, specifically `~/.auto-coder/llm_config.toml`. While simple, this approach presented a few pain points, especially for those of us who juggle multiple projects, each with its own unique requirements. The primary issue was that there wasn't an inherent mechanism to prioritize a *project-specific* configuration over that general, system-wide one. For example, if you were developing a new feature for Client X and needed *Auto-Coder* to interact with a specific, proprietary LLM endpoint, you'd create a `llm_config.toml` file for that. But if you then switched to an internal project that used a standard OpenAI setup, *Auto-Coder* might still try to load Client X's config if it was the last one you manually pointed to, or if your global config was still set that way. This meant dealing with `configuration conflicts` or having to *constantly* manage which file was being loaded._This old logic, specifically lines 76-79 in `src/auto_coder/llm_backend_config.py`, looked something like this: `if config_path is None: config_path = os.path.expanduser("~/.auto-coder/llm_config.toml") else: config_path = os.path.expanduser(config_path)`. See? It's pretty direct: if you give it a path, it uses it; otherwise, it just goes straight to your home directory. There was no step in between to say,