Awesome local LLM
Section: Agent Frameworks · a framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET
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Appears in 4 awesome lists
Microsoft's official framework combining AutoGen's agent abstractions with Semantic Kernel's enterprise features. Supports Python and .NET with graph-based workflows.
Section: Agent Frameworks · a framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET
Section: 4. Agentic AI & Multi-Agent Systems · Microsoft's official framework combining AutoGen's agent abstractions with Semantic Kernel's enterprise features. Supports Python and .NET with graph-based workflows.
Section: Frameworks · Microsoft
Section: LLM and Inference · A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Langchain integrates various providers like Anthropic, AWS, and OpenAI, and offers tools for components such as LLMs, chat models, and data analysis, supporting functionalities from Alpha Vantage to YouTube github | docs
(MIT) provides modules for structured outputs at different levels of abstraction, including output parsers for text completion endpoints, Pydantic programs for mapping prompts to structured outputs using function calling or output parsing, and pre-defined Pydantic programs for specific output types.
February 2026 release making human oversight a native workflow primitive: suspend execution at critical decision points, expose review-and-edit UI mid-flow, and route subsequent execution based on human action (approve/reject/escalate). Demonstrates how HITL transitions from bolt-on approval gates…
Mem0 is an intelligent memory layer for Large Language Models that enhances personalized AI experiences by retaining and utilizing contextual information across various applications. github | website | docs | discord | twitter | github profile | linkedin
Microsoft's multi-agent conversation framework with a complete AgentChat layer covering agent loop, tool integration, termination conditions, and human-in-the-loop. The most comprehensive open-source reference for large-scale multi-agent harness design.
June 2026 harness-first redesign built around the Capability primitive: a single composable unit bundling instructions, tools, lifecycle hooks, and model settings. The split between a small stable core and a fast-moving pydantic-ai-harness lets capabilities graduate as they prove essential, while…
(MIT) is a framework for algorithmically optimizing LM prompts and weights. DSPy introduced typed predictor and signatures to leverage Pydantic for enforcing type constraints on inputs and outputs, improving upon string-based fields.
Flowise simplifies the creation of applications leveraging large language models (LLMs) by providing a drag-and-drop interface for customizing AI workflows, offering easy installation, Docker support, development tools, and documentation for integrating various functionalities such as…