Search Results for "langchain"
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Showing 54 open source projects for "langchain"
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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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LangChain for Java
LangChain4j is an open-source Java library
LangChain for Java is an open-source Java framework designed to simplify the development of applications powered by large language models. The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. -
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LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
LangChain Rust is an open-source Rust implementation inspired by the LangChain ecosystem for building applications powered by large language models. The library aims to provide Rust developers with a structured framework for orchestrating prompts, chains, agents, and external tools within LLM-driven workflows. By adapting LangChain concepts to the Rust programming language, the project emphasizes performance, safety, and efficient memory management. -
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LangChain MCP
Model Context Protocol tool support for LangChain
langchain-mcp provides Model Context Protocol (MCP) tool support for LangChain, a framework for developing applications powered by language models. It allows developers to create an MCPToolkit with a client. -
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LangChain.js
Building applications with LLMs through composability
...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. This is built to integrate as seamlessly as possible with the LangChain Python package. Specifically, this means all objects (prompts, LLMs, chains, etc) are designed in a way where they can be serialized and shared between languages. -
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LangChain-Chatchat
Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge
LangChain-Chatchat (formerly Langchain-ChatGLM): A local knowledge base question answering application implementation based on large language models such as Langchain and ChatGLM. The knowledge base information of the current project is stored in the database, please initialize the database before running the project officially (we strongly recommend that you back up your knowledge files before performing operations). -
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AI PDF Chatbot LangChain
AI PDF chatbot agent built with LangChain & LangGraph
AI PDF Chatbot LangChain is a full-stack template for building conversational agents that can ingest and answer questions about PDF documents. The project demonstrates how to combine LangChain and LangGraph with a vector database to enable retrieval-augmented question answering over user-provided files. It includes both frontend and backend components, making it suitable as a production starting point rather than just a minimal demo. -
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LangServe
Helps developers deploy LangChain runnables and chains as a REST API
LangServe is an open-source deployment framework designed to expose LangChain applications as production-ready REST APIs. The tool simplifies the process of turning language-model pipelines, chains, and agents into web services that can be accessed by external applications. Instead of manually writing API endpoints, developers can use LangServe to automatically generate a server that exposes LangChain workflows through HTTP interfaces. -
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Langchainrb
Build LLM-powered applications in Ruby
LangchainRB is a Ruby implementation of LangChain, allowing developers to build AI-driven applications using large language models (LLMs) and knowledge graphs. -
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Shell-AI
LangChain powered shell command generator and runner CLI
...Instead of requiring users to remember complex command syntax, the tool lets them describe their intent in plain English and automatically suggests commands that accomplish the task. The system is powered by large language models and integrates with frameworks such as LangChain to interpret user requests and translate them into executable shell instructions. Users interact with the program through an interactive terminal interface where multiple command suggestions are presented for review before execution. This approach improves productivity for developers and system administrators who frequently use terminal environments but may not recall every command variation. ... -
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n8n
Free and source-available fair-code licensed workflow automation tool
n8n is an extendable workflow automation tool. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic and apps. n8n's node-based approach makes it highly versatile, enabling you to connect anything to everything. n8n has 200+ different nodes to automate workflows. -
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Helicone
Open source LLM-Observability Platform for Developers
...One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more. -
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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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ROSA
I Agent designed to interact with ROS1- and ROS2-based robotics system
...The project provides a natural language interface that allows developers and operators to interact with robots by issuing commands or queries in conversational language. Built on top of frameworks such as LangChain and modern large language models, ROSA translates user instructions into actions that can be executed within ROS1 or ROS2 environments. This capability enables users to inspect system status, diagnose issues, and control robot behavior without manually navigating complex command-line tools or configuration files. The system integrates with robotics software stacks and exposes operational tools that allow AI agents to analyze system logs, inspect sensors, or trigger robot tasks. -
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Aix-DB
Based on the LangChain/LangGraph framework
...The system is designed as a ChatBI solution that allows users to query datasets using natural language and receive structured insights, charts, and visualizations automatically. Built on frameworks such as LangChain and LangGraph, Aix-DB integrates retrieval-augmented generation and Text-to-SQL capabilities to convert user questions into executable database queries. The platform supports multiple types of data sources and provides an end-to-end pipeline that includes intent recognition, SQL generation, database execution, and visual presentation of results. ... -
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All Agentic Architectures
Implementation of 17+ agentic architectures
...The project acts as a practical learning resource that bridges the gap between theoretical research on autonomous agents and real software implementations. It contains more than a dozen agent architectures implemented using frameworks such as LangChain and LangGraph. Each architecture is explained through runnable notebooks that illustrate how the agent works internally and how it interacts with tools, data sources, or other agents. The repository organizes the architectures into a structured learning path that progresses from simple reasoning agents to complex multi-agent systems. ... -
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Intel LLM Library for PyTorch
Accelerate local LLM inference and finetuning
...IPEX-LLM supports a wide range of popular models, including architectures such as LLaMA, Mistral, Qwen, and other transformer-based systems. The library can integrate with common AI frameworks and serving tools such as Hugging Face Transformers, LangChain, and vLLM, allowing developers to incorporate optimized inference into existing pipelines. -
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self-llm
Tutorial tailored for Chinese babies on rapid fine-tuning
...It provides step-by-step tutorials covering environment setup, model deployment, inference workflows, and efficient fine-tuning techniques such as LoRA and parameter-efficient training. The project also includes guides for integrating models into real applications, including command-line interfaces, web demos, and frameworks like LangChain. By combining theory, configuration instructions, and runnable examples, self-llm lowers the barrier to entry for students and engineers who want to experiment with open-source models. -
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NVIDIA NeMo Agent Toolkit
Library for efficiently connecting and optimizing teams of AI agents
...It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze token-level performance to identify bottlenecks and improve efficiency. NeMo Agent Toolkit also supports evaluation systems, prompt optimization, and reinforcement learning techniques to enhance agent behavior over time. ... -
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Flock
Flock is a workflow-based low-code platform for building chatbots
...The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on technologies such as LangChain, LangGraph, FastAPI, and Next.js, Flock combines a modern web interface with a flexible backend capable of supporting advanced AI workflows. The platform supports multi-agent collaboration, allowing developers to design workflows where different agents handle specialized tasks within the same system. Flock also includes features such as intent recognition, code execution nodes, and human-in-the-loop approval processes that make it suitable for production AI applications. -
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GenAI Agents
Implementations for various Generative AI Agent techniques
...It spans a spectrum from simple conversational bots and basic question-answering agents to complex multi-agent systems that coordinate on research, education, business workflows, and creative tasks. The implementations leverage modern frameworks such as LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, and more, showing how each can be wired into realistic agent workflows. The repo is structured by categories like beginner agents, framework tutorials, educational agents, business agents, creative agents, analysis agents, news bots, shopping assistants, task management agents, QA bots, and advanced systems such as controllable RAG agents. ... -
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Zep
Zep: A long-term memory store for LLM / Chatbot applications
...Understands chat messages, roles, and user metadata, not just texts and embeddings. Zep Memory and VectorStore implementations are shipped with your favorite frameworks: LangChain, LangChain.js, LlamaIndex, and more. Automatically embed texts and messages using state-of-the-art opeb source models, OpenAI, or bring your own vectors. Zep’s local embedding models and async enrichment ensure a snappy user experience. -
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RAG API
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL
rag_api is an open-source REST API for building Retrieval-Augmented Generation (RAG) systems using LLMs like GPT. It lets users index documents, search semantically, and retrieve relevant content for use in generative AI workflows. Designed for rapid prototyping, it is ideal for chatbot development, document assistants, and knowledge-based LLM apps. -
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Agentic
AI agent stdlib that works with any LLM and TypeScript AI SDK
Agentic is an open source, TypeScript, AI agent standard library that works with any LLM and TS AI SDK. Agentic’s standard library of TypeScript AI tools are optimized for both TS-usage as well as LLM-based usage, which is really important for testing and debugging. -
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Agent Stack
Deploy and share agents with open infrastructure
...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 frameworks like LangChain, CrewAI, etc., enabling them to be hosted, managed and shared through a unified interface. It also offers multi-model, multi-provider support (OpenAI, Anthropic, Gemini, IBM WatsonX, Ollama etc.), letting users compare performance and cost across models. For developers and organizations building AI-agent products or automations, Agent Stack gives a scaffold that handles the “plumbing”, so they can focus on logic and domain.