🧠
Agentic Ai Systems model by alirezadir
⭐ 43.1
🧠
Model

Agentic Ai Systems

by alirezadir gh-model--alirezadir--agentic-ai-systems
Nexus Index
43.1 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 61
R: Recency 75
Q: Quality 50
Tech Context
Vital Performance
0 DL / 30D
0.0%
Source →
Audited 43.1 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID gh-model--alirezadir--agentic-ai-systems
License MIT
Provider github
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{gh_model__alirezadir__agentic_ai_systems,
  author = {alirezadir},
  title = {Agentic Ai Systems Model},
  year = {2026},
  howpublished = {\url{https://github.com/alirezadir/agentic-ai-systems}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
alirezadir. (2026). Agentic Ai Systems [Model]. Free2AITools. https://github.com/alirezadir/agentic-ai-systems

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone
git clone https://github.com/alirezadir/agentic-ai-systems

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
43.1
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 61
Recency (R) 75
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Agentic Ai Systems: Semantic (S:50), Authority (A:0), Popularity (P:61), Recency (R:75), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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Technical Deep Dive

Agentic AI Systems

A comprehensive guide to building production-ready AI agents and multi-agent systems

Welcome to Agentic-AI-Systems a curated and evolving knowledge base and hands-on guide for learning about Agents, Agentic AI system design, and building production-ready AI agents and multi-agent systems. This repository is a collection of resources and examples that I have found useful in my journey of building agentic AI systems.

Agentic-AI-Systems

Contents

Chapter Description
1. Foundations GenAI concepts and design, LLMs, evaluation, modern Python, and more.
2. Frameworks Tutorials and example codes for OpenAI, LangGraph, LlamaIndex, LangChain, CrewAI, Chainlit, and more.
3. Agentic System Design Agentic AI System Design: Architectures, layers, design patterns, diagrams, and code.
4. Use Cases Real-world and example agent projects and applications.
5. Resources Courses, tool stacks, protocols, and list of resources.

Highlights

Agentic AI Systems

  • Agentic AI Design Patterns: A comprehensive overview of reusable design patterns in Gen-AI and agentic AI systems.
  • RAGs: A comprehensive overview of RAG architectures, including basic RAGs, agentic RAGs, multi-modal RAGs, and advanced RAGs.
  • Cookbooks: A comprehensive overview of the most useful cookbooks in designing and building agentic AI systems.
  • OpenAI Agents: Comprehensive guides, tutorials, and code examples for building AI agents using the OpenAI API and Agents SDK.
  • Architectures: A comprehensive overview of architectures in agentic AI systems, inlcuding architecture layers, AI-native architectures, step-by-step system design, and example architectures used by tech companies.
  • Agentic AI Evaluation: A comprehensive overview of evaluating Agentic AI Systems, including evaluation layers, dimensions, methods, and frameworks.
  • Code Examples: Step-by-step guides, example codes, and tutorials for building agentic workflows with Open AI agents, LangGraph, LangChain, CrewAI, LlamaIndex, and more.
  • Multi-Agent Systems Examples: Building multi-agent systems using LlamaIndex, Crew AI, and more.
  • Resource Library: Curated list of courses, tools, protocols, and further reading.

Compund Gen-AI Systems

Why Agentic-AI-Systems?

  • Practical: Real code, real projects, real-world patterns
  • Curated: Only the most useful frameworks, tools, and concepts
  • Reference-first: Designed for quick lookup and deep dives
  • Production-ready: Tested examples with deployment guides
  • Community-driven: Continuously updated with latest best practices

Contributing

More coming soon contributions welcome! You can start by forking and submitting your own code-based experiments.

Pull requests are welcome! If you'd like to add new frameworks, examples, or summaries, fork the repo and submit a PR.

Made with love by Alireza Dirafzoon.

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

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📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository
282Stars
Repo Issues
🐙 Data Source: GitHub ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

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🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
gh-model--alirezadir--agentic-ai-systems
slug
alirezadir--agentic-ai-systems
source
github
author
alirezadir
license
MIT
tags
agentic-ai, agents, ai-agents, ai-systems, generative-ai, langgraph, llama-index, llms, openai, agentic-framework, agentic-workflow, chatbots, genai, openai-agents, rag, python

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
feature-extraction

📊 Engagement & Metrics

downloads
0
stars
282
forks
0

Data indexed from public sources. Updated daily.