AI Agent Governance - Policy-Based Sandboxing
Policy-Based Sandboxing: Define what your AI agent can and cannot do using declarative policies - Action Interception: Catch and validate agent action…
- OpenAI
Advanced Agents ·Intermediate
An Agno agentic system that provides expert software architecture analysis and recommendations using a dual-model approach combining DeepSeek R1's Reasoning and Claude. The system provides detailed technical analysis, implementation roadmaps, and architectural decisions for complex software systems.
License Apache-2.0 · content curated and maintained by Doutor AI.
An Agno agentic system that provides expert software architecture analysis and recommendations using a dual-model approach combining DeepSeek R1's Reasoning and Claude. The system provides detailed technical analysis, implementation roadmaps, and architectural decisions for complex software systems.
# Clone the repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/single_agent_apps/ai_system_architect_r1
# Install dependencies
pip install -r requirements.txt
streamlit run ai_system_architect_r1.py
"We need to build a high-frequency trading platform that processes market data streams, executes trades with sub-millisecond latency, maintains audit trails, and handles complex risk calculations. The system needs to be globally distributed, handle 100,000 transactions per second, and have robust disaster recovery capabilities."
"Design a multi-tenant SaaS platform for enterprise resource planning that needs to support customization per tenant, handle different data residency requirements, support offline capabilities, and maintain performance isolation between tenants. The system should scale to 10,000 concurrent users and support custom integrations."
Policy-Based Sandboxing: Define what your AI agent can and cannot do using declarative policies - Action Interception: Catch and validate agent action…
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