Reliable LLM agents in Python — with guardrails
AgentFlow Python is a Python framework concept for building LLM agents that run tools, plan tasks, and automate workflows with human-in-the-loop approvals.
🔗 Live Demo:
https://guru-code-expert.github.io/AgentFlow-Python/
AgentFlow Python focuses on what most agent frameworks miss:
predictability, safety, and operational control.
Instead of ad-hoc agent loops, AgentFlow introduces a structured runtime for planning, tool execution, verification, and approvals.
- 🧠 Planning-first agent execution
- 🛠 Typed, validated tool calls
- 🔁 Retries & rate limits
- 🧾 Memory with explicit budgets
- 🛡 Guardrails & policy enforcement
- 👤 Human-in-the-loop approvals
- 📈 Tracing, eval hooks, and observability
- Support & incident response agents
- Research and analysis agents
- DevOps and infrastructure assistants
- Internal workflow automation
- Deterministic over “vibes”
- Explicit over implicit behavior
- Safe-by-default execution
- Production concerns first, demos second
- Frontend-only interactive demo
- Simulates agent execution timelines and tool calls
- No real LLM or backend integration
This project is a conceptual framework & UI demo.
It illustrates how a serious, production-oriented agent runtime could be designed.
Built by Guru Code Expert
Focused on reliable LLM systems and agent infrastructure.