-
Notifications
You must be signed in to change notification settings - Fork 63
Expand file tree
/
Copy pathllms.txt
More file actions
38 lines (30 loc) · 2.17 KB
/
llms.txt
File metadata and controls
38 lines (30 loc) · 2.17 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
# Context Engineering for Multi-Agent Systems
> In 21st century AI, LLMs are the agents, and the MAS is the environment they operate in.
This repository provides a production-ready, glass-box framework for building domain-agnostic Multi-Agent Systems (MAS). It moves beyond prompting into Context Engineering, utilizing the Model Context Protocol (MCP) to orchestrate specialized agents within a verifiable "Context Engine" architecture.
## Core Metadata
- **Author:** Denis Rothman
- **Key Concepts:** Context Engineering, Multi-Agent Systems (MAS), Semantic Blueprints, High-Fidelity RAG, Model Context Protocol (MCP)
- **Primary Model Support:** Optimized for GPT-5.1 (adaptive reasoning) and backward compatible with GPT-4 series
- **Status:** Updated February 2026
## Key Features
- **Universal Context Engine:** A domain-agnostic core that runs cross-domain use cases (e.g., Legal and Marketing) without changing code.
- **High-Fidelity RAG:** Research agent with automated input sanitization and source-verifiable citations.
- **Token Analytics:** Integrated tracking of Input/Output tokens and cost-efficiency dashboards.
- **Sovereign Architecture:** A "Glass Box" approach providing full transparency into agent reasoning traces.
## Technical Stack
- **Languages:** Python 3.10+
- **Protocols:** Model Context Protocol (MCP)
- **Vector DB:** Pinecone
- **LLM APIs:** OpenAI (latest standards)
- **Dependencies:** Tenacity (>=9.0.0), Tiktoken, FastAPI, OpenAI
## Project Structure
- `/Chapter10/`: Universal Context Engine (Batch & UI versions)
- `/commons/engine/`: Core logic including `engine.py`, `agents.py`, and `registry.py`
- `/Chapter08-09/`: Specialized implementations for Legal and Strategic Marketing domains
- `CHANGELOG.md`: Detailed history of GPT-5.1 upgrades and framework evolution
## Getting Started
1. Obtain OpenAI and Pinecone API keys.
2. Use provided Google Colab or Kaggle badges in the README for instant deployment.
3. Reference `engine.py` for the main execution logic and `agents.py` for specialist agent definitions.
---
*For a detailed narrative of the software evolution from 1980s Latent Semantic Structures to the 2026 Agentic Era, see the media/index.html timeline.*