Deterministic Safety Gates Before The LLM

Learn how to implement deterministic safety gates before LLMs for high-stakes applications, ensuring robust input interpretation and analysis through a confidence triad and tiered approach.

Ollama Llama 3 FastAPI Python Make / Bash

Overview

I built LanguageMCP, which is an assistive-communication (AAC) service that has an interpretation and safety layer for all user inputs before an LLM is called. For the demo I will show the code workflow in the routing core (communication_interpretation_layer.py), the user interface and terminal logs.

Links

https://github.com/daniella-laguerre/LanguageMCP_Demo
https://daniella-resume-2026.surge.sh/
Daniella LaGuerre's portfolio showcases enterprise observability consulting, systems architecture, and her "System Physics" framework, which applies thermodynamic principles to infrastructure monitoring using technologies like Splunk, Cribl, OpenTelemetry, and AWS.
https://substack.com/@lapaixlaguerre
Personal Substack profile of sci-tech writer Daniella LaGuerre.

Tech stack

Ollama

Deploy and run open-source Large Language Models (LLMs) like Llama 3 and Mistral locally on your machine: achieve private, cost-effective AI via a simple command-line interface.

Ollama is the essential tool for running LLMs locally: consider it the Docker for AI models. It packages complex models and dependencies into a single, easy-to-use application for macOS, Linux, and Windows systems. You get immediate access to models like Gemma 2 and DeepSeek-R1 via a straightforward CLI or REST API. This local-first approach guarantees data privacy and security, eliminating cloud dependency and high API costs. Ollama also optimizes performance on consumer hardware using techniques like quantization, ensuring efficient execution even on standard desktops.

https://ollama.com

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Llama 3

Meta's state-of-the-art, openly available Large Language Model: Llama 3 delivers superior performance with 8B and 70B parameter versions.

Llama 3 is Meta's next-generation LLM, setting new benchmarks for openly available models. We released initial versions at 8B and 70B parameters, both instruction-tuned for peak performance (outperforming models like Gemini Pro 1.5 and Claude 3 Sonnet on key industry metrics). The model was trained on a massive 15 trillion token dataset (7x Llama 2's data) and features a 128,000-token vocabulary and 8,192-token context length: this architecture enables enhanced reasoning and multilingual capabilities across over 30 languages. Llama 3 is designed for scale and efficiency, integrating Grouped Query Attention (GQA) for faster inference.

https://llama.com

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FastAPI

FastAPI is a modern, high-performance Python web framework for building APIs with automatic OpenAPI documentation.

FastAPI is a robust, high-speed Python web framework: it is built on Starlette (for async capabilities) and Pydantic (for data validation and serialization). Leveraging standard Python 3.8+ type hints, the framework automatically generates interactive API documentation (Swagger UI/ReDoc) and enforces data validation, effectively reducing developer-induced errors by an estimated 40%. This architecture delivers performance on par with Node.js and Go, significantly increasing feature development speed (up to 300% faster). It is production-ready, fully supporting OpenAPI and JSON Schema standards for all API specifications.

https://fastapi.tiangolo.com

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Python

Python: The high-level, general-purpose language built for readability, powering everything from web backends to advanced machine learning models.

Python is the high-level, general-purpose language prioritizing clear, readable syntax (via significant indentation), ensuring rapid development for any team . Its ecosystem is massive: use it for robust web development with frameworks like Django and Flask, or leverage its power in data science with libraries such as Pandas and NumPy . The Python Package Index (PyPI) provides thousands of community-contributed modules, offering immediate solutions for tasks from network programming to GUI creation . The language is actively maintained by the Python Software Foundation (PSF), with the stable release currently at Python 3.14.0 (as of November 2025) .

https://python.org

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Make / Bash

A powerful combination of GNU Make for dependency-based task orchestration and Bash for direct, low-level system scripting.

Combining GNU Make and Bash creates a highly efficient, lightweight workflow engine for local development and CI/CD pipelines. Make handles the high-level dependency graph (ensuring steps run only when source files change) while Bash executes the actual commands (managing files, environment variables, and system utilities). This pairing eliminates the overhead of heavy orchestration frameworks, relying instead on standard Unix tools to build, test, and deploy software reliably.

https://www.gnu.org/software/make/

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Deterministic Safety Gates Before The LLM

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