Agents and tool use · MLD-1336
Workflow
An organized sequence or graph of processing steps and decisions.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Run extraction, validation, and reporting stages.
Original caveat
A workflow need not use machine learning.
Context and aliases
Level: Intermediate. Stages: Inference · Deployment · Evaluation.
Tags: SLM · LLM · RL · Agents.
Aliases: None recorded.
Related concepts
Concepts linking here
Technology connections
- CrewAI — Framework for role-oriented multi-agent workflows.
- DSPy — Programming and optimization framework for language-model pipelines.
- Haystack — Composable pipelines for search and language-model applications.
- LangChain — Integrations and abstractions for building model-powered applications.
- LangGraph — Stateful graph-based agent orchestration.
- LlamaIndex — Data connectors, indexing and retrieval components for LLM applications.
- Microsoft Agent Framework — Framework for building and coordinating agents with enterprise integrations.
- OpenAI Agents SDK — SDK for model-driven tools, handoffs and tracing.
- PydanticAI — Typed agent framework built around Python and Pydantic.
- Semantic Kernel — SDK for integrating models, functions and orchestration into applications.
- smolagents — Lightweight library for agents using model-selected tools and code.
- Temporal — Durable workflow execution platform.
Original references
- Anthropic: Building effective agents ↗ · Reference link
- Model Context Protocol Python SDK: first steps ↗ · Consulted
- ReAct: Synergizing Reasoning and Acting in Language Models ↗ · Reference link
- Original reference URL ↗