MeshFlow: run governed multi-agent workflows on any local model — Ollama, LiteLLM, Bedrock — with cost caps and audit trails [Open Source]

Hey, Built a framework that works with any model you're running locally or self-hosted. No vendor lock-in, no required API keys. ```python from meshflow import Agent, Workflow, CostCap # Local Ollama — no API key researcher = Agent(name="researcher", model="llama3.2") analyst = Agent(name="analyst", model="mistral") writer = Agent(name="writer", model="llama3.1:70b") wf = Workflow(cost_cap=CostCap(usd=0.00)) # local = zero cost wf.add(researcher, analyst, writer) result = wf.run("Write a technical analysis of transformer attention mechanisms") ``` Works with: - **Ollama** — `model="llama3.2"`, `model="mistral"`, `model="codellama"`, etc. - **LiteLLM** — `model="groq/llama-3.1-70b"`, any of 100+ models - **AWS Bedrock** — `model="anthropic.claude-v2"` - **Azure OpenAI** — your own endpoint - **Any OpenAI-compatible endpoint** — `OpenAICompatibleProvider(base_url="...")` Full sandbox mode for local testing — full run, full trace, zero model calls: ```python wf = Workflow(mode="sandbox") result = wf.run("test this workflow") # Full audit trace, zero model calls, zero cost ``` The governance layer (audit chain, cost caps, compliance profiles, guardrails) works identically regardless of which model you use. HIPAA compliance enforcement doesn't care if you're running Llama or Claude. ```bash pip install meshflow pip install "meshflow[full]" # adds Bedrock, Gemini, LiteLLM ```