flowing-os 0.2.0

Interoperability and observability layer for multi-agent AI systems

Flowing: The Debugger for AI Agents Workflow.

Instantly trace, record, and audit every decision in your multi-agent workflow.

Stop guessing why your agents fail. Flowing provides a "Source of Truth" for complex AI interactions.

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⚡ 10-Second Quick Start

Run this in your terminal to launch the full Observability Dashboard and a live Agentic Demo:

python3 -m venv flowing-env && source flowing-env/bin/activate && pip install flowing-os && flowing demo

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🎯 Why this matters

Multi-agent systems are complex:

• Agents plan, reason, call tools, and coordinate asynchronously.
• Silent errors and emergent behavior are common.
• Traditional logs and simple prints don’t provide enough insight. Flowing captures rich execution data structured logs, spans, traces, and interaction graphs to help you see what’s happening and why.

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⚡What you can do with it

With Flowing’s current MVP you can:

• Run multiple independent agents and record execution traces
• Capture structured events for agent actions and tool invocations
• Reconstruct cross-agent workflows
• Generate interactive trace visualizations
• Improve debugging and reproducibility of complex runs

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🧠 What This Repo Includes

• Structured trace capture and logging utilities
• Execution span schema for multi-agent workflows
• Scripts to run demos and visualize behavior
• Base interfaces that emit telemetry

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🚧 Current Status

This project is experimental but functional:

✔ Structured logging and trace capture

✔ Execution spans for agent actions

✔ Interactive trace visualization output

❌ Universal cross-framework interoperability (future work)

❌ Production dashboard or hosted API

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📈 Roadmap

Planned improvements include:

• Enhanced visual dashboards for traces
• Standardized trace schema
• Replay mode for debugging workflows
• Plugins for external observability systems (e.g., OpenTelemetry)
• Enterprise features (enterprise API, alerting, retention)

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🤝 Contributing

This repo is for developers building, debugging, or improving multi-agent AI workflows. If you care about:

• Agent execution visibility
• Reproducible runs
• Structured trace semantics
• Better debugging outcomes

…then this project is for you. Pull requests and feedback welcome.