🧠 Building Transparent AI Reasoning Pipelines with CodeMaster
“Prompting isn’t enough. Great AI systems need to think — not just respond.”
Modern LLM applications are getting faster, flashier, and more capable — but there’s one problem that persists: we don’t know how they think. Responses are often opaque. Reasoning is buried in the prompt or implied in the output. And debugging? A guessing game.
That’s why I built CodeMaster Reasoning Pipe — a modular, multi-model pipeline for step-by-step reasoning, transparent output traces, and chain-of-thought refinement.
🔍 What It Does
CodeMaster is a FastAPI-ready backend pipeline that turns any Open WebUI setup into an LLM reasoning engine. Instead of responding directly to user input, it breaks tasks into phases:
- Initial Reasoning: Structured analysis of the user query.
- Chain-of-Thought Iterations: Step-by-step refinement of the plan.
- Final Response Generation: Clean, executable, or context-aware answers.
Each stage can run on different models — even across APIs (OpenAI or Ollama). You can trace output at every phase, log token usage, and cap reasoning time.
Think of it as a brainstem for your AI agent.
🛠 Why I Built It
As a Technical Lead and AI Specialist, I’ve shipped LLM-powered systems across domains:
fraud prevention, generative music visualizers, deepfake detection, and GPT legal bots.
One thing I consistently needed?
A way to reason before responding — to simulate cognition, not just completion.
CodeMaster is the foundation I wanted for AI agents that can plan, reflect, and refine.
🧪 Try It, Hack It, Extend It
Whether you’re building:
- 🦾 Autonomous agents with memory and task planning
- 🔒 Secure decision pipelines with auditable reasoning
- 🧠 Prompt debugging tools that expose token-by-token logic
CodeMaster’s modular valve system makes it simple to integrate, adapt, or extend.
▶️ GitHub: CodeMaster Reasoning Pipe
🧬 What’s Next
I’m already working on:
- LangChain plugin adapters
- Reasoning embeddings for prompt memory
- Visualization dashboards for trace debugging
- Agentic state carryover across sessions
If you're working on anything agentic, explainable, or edge-deployable — let's talk.
👋 About Me
I'm Sam Paniagua, an AI engineer, technical lead, and founder of Hive Forensics A.I.™
I build intelligent systems at the edge of security, generation, and cognition.
Check out more of my work at theeseus.dev or connect with me on LinkedIn.
“Reasoning isn't a luxury in AI — it's the foundation for trust.”
Let’s build more transparent, powerful, and responsible LLM systems — one step at a time.
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