AutoGen
Open source Microsoft framework for building multi agent AI apps with chat tool use function calling human in the loop and orchestration primitives for production workflows.
Pricing Free
Category coding
Difficulty Beginner
Type Web App
Status Active
BentoML
Open source toolkit and managed inference platform for packaging deploying and operating AI models and pipelines with clean Python APIs strong performance and clear operations.
Pricing Free (OSS) / By quote
Category coding
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in AutoGen
agentsframeworkorchestrationtool-calling
Shared
open-source
Only in BentoML
model-servingmlopsinferencekubernetesgpu
Key Features
AutoGen
- • Agent Roles: Define planner executor critic or custom roles
- • Tool Calling: Register Python functions APIs or shell tasks
- • Conversation Loop: Coordinate agent messages tool calls and human handoffs
- • Memory and Logs: Persist conversations and tool results for debugging
- • Deterministic Scripts: Encode repeatable dialogues for reliability
- • Extensible Storage: Plug in vector stores and retrieval sources
BentoML
- • Python SDK for clean typed inference APIs
- • Package services into portable bentos
- • Optimized runners batching and streaming
- • Adapters for torch tf sklearn xgboost llms
- • Managed platform with autoscaling and metrics
- • Self host on Kubernetes or VMs
Use Cases
AutoGen
- → Customer Support Flows: Triage issues call CRM tools summarize tickets
- → Data Processing: Pull files clean columns analyze and report
- → Developer Copilots: Draft tests refactors open PRs with approval gates
- → Research Assistants: Combine retrieval and critique roles with citations
- → Operations Runbooks: Encode dialogues that escalate to humans with logs
- → Marketing Drafts: Connect CMS analytics to propose briefs and drafts
BentoML
- → Serve LLMs and embeddings with streaming endpoints
- → Deploy diffusion and vision models on GPUs
- → Convert notebooks to stable microservices fast
- → Run batch inference jobs alongside online APIs
- → Roll out variants and manage fleets with confidence
- → Add observability to latency errors and throughput
Perfect For
AutoGen
Software engineers, platform teams, and researchers who need a flexible open source base to prototype and run multi agent systems with tool calling logging and human oversight
BentoML
ML engineers platform teams and product developers who want code ownership predictable latency and strong observability for model serving
Capabilities
AutoGen
Roles and Policies Professional
Tool Calls Professional
Memory and Traces Intermediate
Human in the Loop Intermediate
BentoML
Typed Services Intermediate
Runners and Batching Professional
Managed Platform Professional
CLI and GitOps Intermediate
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