Reasonix

Reasonix is an open-source terminal coding agent that uses DeepSeek AI. Unlike other apps that focus purely on the console, here you work in an environment that feels closer to Codex or Antigravity, with organized chats, visible context control, and quick access to both local models and the DeepSeek API to code while using fewer tokens and knowing what information the AI is reading at all times.

Chat sessions and active project context

In the left sidebar you can organize your sessions, create new workspaces and start separate conversations according to the task or repository you are working on, while at the top you keep several chats open in tabs to jump between correction, refactoring, or a specific query without closing anything. The most useful section is in the panel on the right, because there you can clearly see how many tokens you are consuming and which specific files are part of the current context, which is especially practical when working with large projects and you want to check if the AI has the necessary pieces loaded before requesting a review or a new implementation.

Cloud models and local alternatives

Reasonix also stands out for just how flexible it is when it comes to choosing the model you want to work with at any given time. It is heavily oriented towards DeepSeek by default, but the app doesn't force you to always depend on the cloud, because it also allows you to use local models via Ollama, which is useful if you prefer to keep your code more isolated or reserve API spending for the moments when you really need more quality. There is a quick selector in the input bar to switch models on the fly and adjust memory usage between various profiles, so the AI's behavior can be adapted to the device you are using.

Quick commands and file reading

The Reasonix text box is not a simple chat where you type a question and wait for an answer. The forward slash can be used to open quick commands that better guide the AI according to what you need to do, which is very convenient when you want to go directly to a review, planning, or more autonomous execution without writing detailed instructions every time. On top of that, the @mention system streamlines daily work as it allows you to point to specific files on your computer to instantly include them in the conversation. As a result, if you are debugging or extending a function, you can add a configuration, class, or dependency file in seconds and continue working without leaving the chat. Added to this are direct actions like review, plan, or auto which turn the app into an assisted programming environment that is much more agile than a pure terminal.

Usage control and balance monitoring

Another important aspect of Reasonix is that it doesn't attempt to hide the cost of your queries behind secondary menus or difficult-to-read statistics. If you opt for paid models via the API, in the bottom right corner you can see in real time how much the current interaction is costing you and your available balance, so you can adjust the length of your prompts or decide when it is worth switching from a local model to a remote one. This continuous monitoring is very helpful when working with long sessions and a great deal of context, because it doesn't force you to code blindly without knowing how much you are consuming. And, if you run out of credit, the app stops the transmission and displays a clear notice within the chat itself, avoiding that confusing moment when the AI seems to get stuck and you don't know if the problem is with the prompt, the network, or your account.

My experience with Reasonix

I opened Reasonix to build a small Stream Deck plugin that would read the temperature from my Netatmo weather station and display it on a custom key. I started by creating a new chat with a local model based on DeepSeek and asked it for an initial project structure, but I immediately realized I needed to add a configuration file, so I incorporated it directly using the '@' symbol in the text box. From that point on, I started chaining questions about authentication, API reading, and output format, and later I switched to the DeepSeek model via API to resolve a bug that was preventing certain data from being saved correctly. When I made that change, the debugging response became more precise and I managed to generate a functional version of the extension that I later imported into my Stream Deck software without any issues.

What I liked most about Reasonix and what could be improved

· What I liked most: The panel shows you the actual conversation context and token usage, allowing you to program with greater peace of mind and control.

· What could be improved: The configuration of local models needs some work, as it remains more complex than it should be when you want to switch between several options quickly or fine-tune the use of DeepSeek on your own equipment.

Download Reasonix to code with DeepSeek and other models from a desktop interface that unifies context, cost control, and quick actions designed for real development.