Search Results for "agent" - Page 3
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Showing 73 open source projects for "agent"
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
...The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The GLM-Z1-32B-0414 line adds deeper mathematical, coding, and logical reasoning via extended reinforcement learning and pairwise ranking feedback, while GLM-Z1-Rumination-32B-0414 introduces a “rumination” mode that performs longer, tool-using deep research for complex, open-ended tasks. A lightweight GLM-Z1-9B-0414 brings many of these techniques to a smaller model, targeting strong reasoning under tight resource budgets. -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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OSS-Fuzz Gen
LLM powered fuzzing via OSS-Fuzz
OSS-Fuzz-Gen is a companion project that helps automatically create or improve fuzz targets for open-source codebases, aiming to increase coverage in OSS-Fuzz with minimal maintainer effort. It analyses a library’s APIs, examples, and tests to propose harnesses that exercise parsers, decoders, or protocol handlers—precisely the code where fuzzing pays off. The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage... -
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MemoryOS
MemoryOS is designed to provide a memory operating system
MemoryOS is an open-source framework designed to provide a structured memory management system for AI agents and large language model applications. The project addresses one of the major limitations of modern language models: their inability to maintain long-term context beyond the limits of their prompt window. MemoryOS introduces a hierarchical memory architecture inspired by operating system memory management principles, allowing agents to store, update, retrieve, and generate information... -
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Claude Code Bridge
Real-time multi-AI collaboration: Claude, Codex & Gemini
Claude Code Bridge is an open-source command-line tool designed to enable real-time collaboration between multiple AI coding assistants within a unified development environment. The system allows developers to coordinate interactions between models such as Claude, Codex, and Gemini so that they can work together on programming tasks. By maintaining persistent shared context between these models, the tool reduces redundant prompts and minimizes token usage while allowing each AI system to... -
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Mirascope
LLM abstractions that aren't obstructions
Mirascope is a powerful, flexible, and user-friendly library that simplifies the process of working with LLMs through a unified interface that works across various supported providers, including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Vertex AI, and Bedrock. Whether you're generating text, extracting structured information, or developing complex AI-driven agent systems, Mirascope provides the tools you need to streamline your development process and create powerful, robust applications. -
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LongWriter
Unleashing 10,000+ Word Generation from Long Context LLMs
...LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer responses. The system uses an agent-based pipeline called AgentWrite that decomposes large writing tasks into smaller subtasks, allowing the model to produce long documents section by section. Researchers also created the LongWriter-6k dataset containing thousands of examples with outputs ranging from a few thousand to tens of thousands of words. -
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OpenPlanter
Language-model investigation agent with a terminal UI
OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. The system is... -
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Youtu-GraphRAG
Vertically Unified Agents for Graph Retrieval-Augmented Reasoning
Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. These structures allow the system to perform multi-hop reasoning by decomposing complex questions into smaller queries that can be executed across different parts of the graph. ... -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
Sage is an open-source AI developer assistant designed to help engineers understand and work with complex codebases more effectively. The tool functions similarly to an intelligent research agent that can analyze a repository and answer questions about how the software works. Instead of focusing solely on code generation, Sage emphasizes code comprehension, system architecture analysis, and integration guidance. Developers can ask natural language questions about a project, and the system responds with explanations supported by references to the relevant code, documentation, or external technical resources. ... -
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ControlFlow
Take control of your AI agents
...The framework provides a structured approach for building AI systems by breaking complex tasks into smaller units called tasks that can be assigned to specialized AI agents. Developers can combine these tasks into flows that define how work is executed, enabling the creation of multi-step reasoning pipelines and collaborative agent systems. ControlFlow focuses on maintaining transparency and control in AI applications by providing explicit workflow structures instead of opaque chains of prompts. The system integrates with common LLM providers and allows developers to create workflows that blend traditional software logic with AI-driven reasoning. Built on top of the Prefect ecosystem, the framework also includes observability and debugging capabilities that allow developers to monitor how tasks are executed. -
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Agentic Context Engine
Make your agents learn from experience
Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and... -
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Cradle framework
The Cradle framework is a first attempt at General Computer Control
...This approach allows agents to interact with any software interface without relying on specialized APIs or predefined automation scripts. The framework integrates reasoning, planning, and memory modules that help the agent understand its environment and execute long sequences of actions. Cradle agents are capable of performing tasks across a wide variety of environments, including computer applications and video games, demonstrating the generality of the approach. The architecture includes modules that allow agents to observe their environment, reflect on past actions, plan future steps, and accumulate useful skills for later tasks. -
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DocETL
A system for agentic LLM-powered data processing and ETL
DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL... -
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Sparrow
Structured data extraction and instruction calling with ML, LLM
Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to... -
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E2B Cookbook
Examples of using E2B
E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code... -
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second-brain-ai-assistant-course
Learn to build your Second Brain AI assistant with LLMs
...The concept of a “second brain” refers to a personal knowledge repository containing notes, research, and documents that can be queried and analyzed using AI. Through a series of modules, the project explains how to design data pipelines, build retrieval-augmented generation systems, and implement agent-based reasoning workflows. The course also introduces practical techniques such as dataset generation, model fine-tuning, and deployment strategies for AI applications. Learners build a full system capable of retrieving information from stored resources and generating responses based on that data. -
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NVIDIA Generative AI Examples
Generative AI reference workflows
...The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. The repository includes examples covering topics such as retrieval-augmented generation pipelines, agent-based workflows, and multimodal AI applications that combine text, vision, and data processing. Many of the examples show how to deploy AI services using containerized environments, GPU acceleration, and microservices that can scale across modern infrastructure. Developers can explore sample chatbot applications, document question-answering systems, and knowledge-base pipelines that illustrate how generative AI can interact with external data sources. -
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Ailice
AIlice is a fully autonomous, general-purpose AI agent
AIlice is an open-source autonomous AI agent framework built to function as a general-purpose assistant that can plan, decompose, and execute complex tasks through a structured multi-agent architecture. The project presents itself as a standalone assistant powered by open-source language models, with an internal design that treats user requests almost like executable programs rather than simple chat prompts. -
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Streamline Analyst
AI agent that streamlines the entire process of data analysis
Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates all the tasks such as data cleaning, preprocessing, and even complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. -
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Functionary
Chat language model that can use tools and interpret the results
Functionary is an open-source large language model specifically designed for interpreting and executing structured functions or external tools within conversational AI systems. The model extends traditional chat-based language models by enabling them to determine when external functions should be called and how to extract the necessary parameters from natural language input. Function definitions are typically provided in JSON schema format, allowing the model to generate structured function... -
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LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
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langchain-prefect
Tools for using Langchain with Prefect
...For this reason, it could be a great fit for observing apps that use LLMs. RecordLLMCalls is a ContextDecorator that can be used to track LLM calls made by Langchain LLMs as Prefect flows. Run several LLM calls via langchain agent as Prefect subflows.
