Certifiedunder the Production-Grade Agentic System module in the Agentic AI In Production program.Certifiedunder the Production-Grade Agentic System module in the Agentic AI In Production program.
A Production-Ready, High-Performance AI Architecture for Python Learning, Deep Research, and Document Summarization
ALPHA AI is a multi-agent orchestration system designed to combine precision, speed, and reliability.
It integrates three specialized agents:
The system is built to support students, developers, researchers, and enterprises looking for a unified, trusted AI platform.
🔹 Python Learning (RAG)
🔹 Deep Research
🔹 Document Summarization
Below is the final architecture diagram representing ALPHA AI’s multi-agent workflow:
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git clone
https://github.com/mohamadlamg/Module3
.git
ALPHA AI user interface is based on Streamlit.
Streamlit is a simple and fast Python framework that allows you to create interactive web applications without having to code a real website. It is mainly used to:
Display data, graphs, or tables, create interfaces for AI models or Python scripts, and quickly prototype dashboards or internal tools.
All you have to do is write Python, and Streamlit automatically generates the interface. You can also use CSS style and HTML. It is one of the most popular tools for creating data or AI apps in minutes.
For example :
With this Python code, you can generate this interface :
Streamlit is a very interesting library and is used for the ALPHA AI interface.
For more information about Streamlit, visit the documentation page: https://docs.streamlit.io/
###Some code of ALPHA AI interface
Right here, we are using HTML and applying the CSS style defined previously
CSS style
User Experience
Clear navigation, Instant responses, Clean formatting
ALPHA AI has been designed to meet core production-grade standards.
Modular multi-agent architecture
Fast inference through Groq
Clean separation of concerns
Stateless design for scalability
Dedicated unit test suite
Manual scenario tests for edge cases
Verified agent-to-agent consistency
Input/output checks
ALPHA AI inputs are validated using Detoxify
Detoxify is an AI model designed to analyze text and automatically detect toxicity. It can identify various types of harmful behavior, such as insults, hate speech, harassment, and aggressive or vulgar language.
The RAG model is based only on the source documents provided.
Sanitized external search
ALPHA AI only makes searches on the internet in the positive sense of the term. It will never make searches that are unethical or compromise personal data.
Unit tests
As a production-level system, we need to ensure that everything goes according to plan and that there are no unpleasant surprises.
To do this, we check each item individually: our input validation, our agents calls, and state management.
We use pytest.
Pytest is a simple and powerful testing framework for Python that allows you to write and run automated tests. It is used to verify that the code works correctly, detect bugs quickly, facilitate project maintenance, test both small functions and complex systems.
Firstly, we check if toxic inputs are correctly replaced
We also check if the corrects inputs are passing correctly.
Secondly, we verify if we can access correctly to our agents.
Simple console-based logging using prints
Modular code for monitoring integrations
Future-ready structure for logging/metrics providers
Open Source
This allows modification, commercial use, distribution, and private use.
GitHub: [https://github.com/mohamadlamg]
Project: ALPHA AI
For issues or suggestions, please open a GitHub issue.