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Harness the power of next-generation AI while maintaining complete control and reliability.
The AI revolution is transforming how we work - but with great power comes great responsibility. LION provides the control mechanisms and reliability features needed to safely integrate advanced AI capabilities into enterprise workflows.
LION is designed to be:
from lionagi import Branch, iModel
# Initialize model
gpt4o = iModel(provider="openai", model="gpt-4o")
# Create a branch with personality
comedian = Branch(
system="you are a sarcastic dragon hunter",
imodel=gpt4o
)
# Chat asynchronously
response = await comedian.chat(
"tell me a joke on knight vs dragon"
)
LION maintains minimal dependencies for maximum reliability:
pip install lionagi
Dependencies:
Below is an example of what you can build with LION. Note that these are sample implementations - LION provides the building blocks, you create the workflows that fit your needs.
sequenceDiagram
autonumber
participant Client
participant Orchestrator
participant ResearchAgent
participant AnalysisAgent
participant ValidationAgent
participant Tools
Client->>+Orchestrator: Submit Complex Task
Note over Orchestrator: Task Analysis & Planning
%% Research Phase
Orchestrator->>+ResearchAgent: Delegate Research
activate ResearchAgent
ResearchAgent->>Tools: Access Data Sources
Tools-->>ResearchAgent: Raw Data
ResearchAgent-->>-Orchestrator: Research Results
deactivate ResearchAgent
%% Analysis Phase
Orchestrator->>+AnalysisAgent: Process Data
activate AnalysisAgent
AnalysisAgent->>Tools: Apply Models
Tools-->>AnalysisAgent: Analysis Results
AnalysisAgent-->>-Orchestrator: Processed Insights
deactivate AnalysisAgent
%% Validation Phase
Orchestrator->>+ValidationAgent: Verify Results
activate ValidationAgent
ValidationAgent->>Tools: Apply Safety Checks
Tools-->>ValidationAgent: Validation Status
ValidationAgent-->>-Orchestrator: Verified Results
deactivate ValidationAgent
Orchestrator-->>-Client: Return Validated Output
Here's how you can structure your LION-powered system. Each component can be customized to your specific needs.
graph TB
subgraph Client Layer
CL[Client Application]
end
subgraph Orchestration Layer
ORC[Orchestrator]
SEC[Security Controls]
MON[Monitoring]
end
subgraph Agent Layer
subgraph Specialized Agents
RA[Research Agent]
AA[Analysis Agent]
VA[Validation Agent]
end
subgraph Agent Controls
AC[Access Control]
AM[Action Monitor]
VE[Verification]
end
end
subgraph Resource Layer
subgraph Tool Management
TM[Tool Registry]
TP[Tool Policies]
end
subgraph Data Sources
DS[Data Access]
DV[Data Validation]
end
end
%% Connections
CL --> ORC
ORC --> RA & AA & VA
RA & AA & VA --> AC
AC --> TM
TM --> DS
%% Control Flow
ORC --> SEC
SEC --> MON
MON --> AM
AM --> VE
VE --> TP
TP --> DV
classDef primary fill:#1e40af,stroke:#1e3a8a,color:#fff
classDef secondary fill:#3b82f6,stroke:#2563eb,color:#fff
classDef control fill:#7c3aed,stroke:#6d28d9,color:#fff
LION provides the essential components you need to build reliable AI workflows:
Each component is designed to be:
Enterprise Operations
AI Integration
Development
LION isn't just another framework - it's your partner in responsible AI adoption. Build enterprise-grade AI systems with:
Join our Discord community to:
@software{Li_LionAGI_2023,
author = {Haiyang Li},
month = {12},
year = {2023},
title = {LionAGI: Intelligent Integration Framework},
url = {https://github.com/lion-agi/lionagi},
}