Skillget

ERPNext-AI-Agent-Project

agent
Guvenlik Denetimi
Uyari
Health Uyari
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 10 GitHub stars
Code Gecti
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This project provides an intelligent assistant for ERPNext systems. It uses a multi-agent architecture, semantic search, and knowledge graphs to automatically generate business schemas, map data relationships, and process documents.

Security Assessment
Overall risk is rated Medium. The automated code scan found no dangerous patterns, hardcoded secrets, or dangerous permission requests. However, the tool inherently makes network requests to connect to external APIs (like OpenAI and Anthropic) and local databases (Neo4j, ChromaDB, Redis). It also accesses and indexes potentially sensitive ERP business data (invoices, orders, and customer details). Sending this proprietary information to third-party AI providers poses a significant data privacy risk depending on your configuration.

Quality Assessment
The repository is active, with its most recent push occurring today, and has accumulated a modest 10 GitHub stars, indicating early-stage community interest. It features a comprehensive and well-documented README. However, it completely lacks an open-source license. Without a defined license, all rights are technically reserved by the creator, meaning the code cannot be legally copied, modified, or used in commercial environments without explicit permission.

Verdict
Use with caution. The tool's code is safe from a static analysis perspective, but you must configure it to handle sensitive ERP data responsibly, and the absence of a license makes formal adoption a legal gray area.
SUMMARY

Advanced AI agent system for ERPNext with reinforcement learning-based retrieval, multi-agent orchestration, and intelligent document processing.

README.md

ERPNext AI Agent

Intelligent assistant for ERPNext that uses semantic search, knowledge graphs, and multi-agent workflows to speed up ERP development and document processing.

What it does

  • Semantic Search — Find any ERPNext document (invoices, orders, customers) using natural language
  • Auto-generate DocTypes — Describe a business need → get Frappe doctype JSON, controllers, and workflows
  • Knowledge Graphs — Maps relationships between customers, orders, items, and projects
  • Multi-Agent Pipeline — Specialized agents handle requirements analysis → architecture → schema → implementation
  • Document Processing — PDF, DOCX, Excel ingestion with automatic indexing

Tech Stack

Component Technology
AI/LLM LangChain, OpenAI, Anthropic, Sentence Transformers
Vector DB ChromaDB, FAISS
Knowledge Graph Neo4j, NetworkX
RL Training Gymnasium, Stable-Baselines3
Multi-Agent CrewAI, AutoGen
API Server FastAPI + Uvicorn
Document Processing spaCy, PyPDF2, python-docx
Monitoring Prometheus, structlog

Quick Start

# Install dependencies
pip install -r requirements.txt

# Start the AI agent
python start_erpnext_ai_agent.py

The agent auto-detects your ERPNext instance and begins indexing documents immediately.

Requirements: Python 3.10+, Neo4j (for knowledge graphs), ChromaDB (for vector search), Redis (for caching). Docker recommended for full setup — see docker/README.md.

Architecture

User Request
    │
    ▼
┌─────────────────────────────────┐
│     Multi-Agent Orchestrator     │
│  (requirements → arch → schema)  │
└──────────────┬──────────────────┘
               │
     ┌─────────┼─────────┐
     ▼         ▼         ▼
┌─────────┐ ┌──────┐ ┌──────────┐
│ Semantic│ │Knowl-│ │Document  │
│ Search  │ │edge  │ │Processor │
│(Chroma) │ │Graph │ │(spaCy)   │
└────┬────┘ └──┬───┘ └────┬─────┘
     │         │          │
     └─────────┼──────────┘
               ▼
        ERPNext Instance

Real Examples

from integrations.multi_agent_workflows import MultiAgentOrchestrator

orchestrator = MultiAgentOrchestrator()

# Generate a complete sales management system
result = orchestrator.execute_workflow(
    "Design a sales management system with quotes, orders, and invoicing"
)

# Build an inventory system with automated reordering
result = orchestrator.execute_workflow(
    "Create inventory system with automated reordering and low stock alerts"
)

Project Structure

integrations/
├── erpnext_connector.py      — ERPNext API client
├── document_indexer.py       — Semantic indexing pipeline
├── knowledge_graph_builder.py — Neo4j relationship mapper
├── multi_agent_workflows.py  — Agent orchestration
├── rl_training_dataset.py    — RL training data generation
└── mcp_server_config.py      — MCP server for IDE integration

start_erpnext_ai_agent.py     — One-command launcher
docker/                        — Docker & container configs

License

MIT

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