Search Results for "dll custom frameworks"
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Showing 28 open source projects for "dll custom frameworks"
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. “planner,” “searcher,” “coder,” “report generator”)... -
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IntentKit
An open and fair framework for everyone to build AI agents
IntentKit is a natural language understanding (NLU) library focused on intent recognition and entity extraction, enabling developers to build conversational AI applications. -
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Agent Squad
Flexible and powerful framework for managing multiple AI agents
Agent-Squad is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries and maintains context across interactions, offering pre-built components for quick deployment and easy integration of custom agents. -
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Potpie
Create custom engineering agents for your codebase
Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding. -
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TaskWeaver
A code-first agent framework for seamlessly planning analytics tasks
TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks. -
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PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications,... -
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Multi-Agent Orchestrator
Flexible and powerful framework for managing multiple AI agents
Multi-Agent Orchestrator is an AI coordination framework that enables multiple intelligent agents to work together to complete complex, multi-step workflows. -
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OpenManus
Open-source AI agent framework
OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing... -
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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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Agent S
Agent S: an open agentic framework that uses computers like a human
Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines... -
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Atomic Agents
Building AI agents, atomically
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are... -
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Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
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rLLM
Democratizing Reinforcement Learning for LLMs
rLLM is an open-source framework for building and training post-training language agents via reinforcement learning — that is, using reinforcement signals to fine-tune or adapt language models (LLMs) into customizable agents for real-world tasks. With rLLM, developers can define custom “agents” and “environments,” and then train those agents via reinforcement learning workflows, possibly surpassing what vanilla fine-tuning or supervised learning might provide. The project is designed to... -
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Agent Stack
Deploy and share agents with open infrastructure
Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. OpenAI, Anthropic, Mistral, Gemini) and... -
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Universal Commerce Protocol (UCP)
The common language for platforms, agents and businesses.
Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its... -
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Qwen-Agent
Agent framework and applications built upon Qwen>=3.0
Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time.... -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. Agent-Lightning introduces a lightweight training pipeline that observes agents’ execution traces, converts them into structured data, and feeds them into training algorithms, enabling users to improve agent behaviors systematically. ... -
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Phidata
Build multi-modal Agents with memory, knowledge, tools and reasoning
Phidata is an open source platform for building, deploying, and monitoring AI agents. It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to... -
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AutoGroq
Revolutionizes the way users interact with Autogen
AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen™ and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency. AutoGroq was born out of the realization that the traditional approach to building AI agents was backwards. Instead of creating agents in anticipation... -
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Flowly AI
Flowly is 100x faster than OpenClaw
...Projects like this often include a set of components for creating modular AI tasks, connecting data sources, and integrating with APIs so that complex automation can run with minimal boilerplate. Given the broader context of AI workflow tools, FlowlyAI might emphasize extensibility, allowing users to plug in different models or custom logic blocks depending on their specific use cases.
