AI tools for langchain
Related Tools:
LangChain
LangChain is an AI tool that offers a suite of products supporting developers in the LLM application lifecycle. It provides a framework to construct LLM-powered apps easily, visibility into app performance, and a turnkey solution for serving APIs. LangChain enables developers to build context-aware, reasoning applications and future-proof their applications by incorporating vendor optionality. LangSmith, a part of LangChain, helps teams improve accuracy and performance, iterate faster, and ship new AI features efficiently. The tool is designed to drive operational efficiency, increase discovery & personalization, and deliver premium products that generate revenue.
LangChain
LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.
Gista
Gista is an AI-powered conversion agent that helps businesses turn more website visitors into leads. It is equipped with knowledge about your products and services and can offer value props, build an email list, and more. Gista is easy to set up and use, and it integrates with your favorite platforms.
Lyzr AI
Lyzr AI is a full-stack agent framework designed to build GenAI applications faster. It offers a range of AI agents for various tasks such as chatbots, knowledge search, summarization, content generation, and data analysis. The platform provides features like memory management, human-in-loop interaction, toxicity control, reinforcement learning, and custom RAG prompts. Lyzr AI ensures data privacy by running data locally on cloud servers. Enterprises and developers can easily configure, deploy, and manage AI agents using Lyzr's platform.
Teach-O-Matic
Teach-O-Matic is an AI tool that allows users to create how-to videos from text instructions. It is an open source Jupyter notebook powered by Replicate, LangChain, and GPT-4. Users can easily generate videos on various topics without the need for a development environment. The tool utilizes AI technologies such as text-to-video conversion, script writing, music generation, and image creation to streamline the video creation process.
Quivr
Quivr is an open-source chat-powered second brain application that transforms private and enterprise knowledge into a personal AI assistant. It continuously learns and improves at every interaction, offering AI-powered workplace search synced with user data. Quivr allows users to connect with their favorite tools, databases, and applications, and configure their 'second brain' to train on their company's unique context for improved search relevance and knowledge discovery.
NOCODING AI
NOCODING AI is an innovative AI tool that allows users to create advanced applications without the need for coding skills. The platform offers a user-friendly interface with drag-and-drop functionality, making it easy for individuals and businesses to develop custom solutions. With NOCODING AI, users can build chatbots, automate workflows, analyze data, and more, all without writing a single line of code. The tool leverages machine learning algorithms to streamline the development process and empower users to bring their ideas to life quickly and efficiently.
DenserAI
DenserAI is an AI-powered chatbot application designed to be integrated into websites to enhance customer support, lead generation, and conversions. It offers powerful AI features such as intelligent search and chat systems, precise answers with source citations, advanced search functionality, and seamless integration with various platforms. DenserAI aims to provide efficient and scalable solutions for businesses to improve customer satisfaction, save operational costs, generate leads, and boost sales.
Firecrawl
Firecrawl is an advanced web crawling and data conversion tool designed to transform any website into clean, LLM-ready markdown. It automates the collection, cleaning, and formatting of web data, streamlining the preparation process for Large Language Model (LLM) applications. Firecrawl is best suited for business websites, documentation, and help centers, offering features like crawling all accessible subpages, handling dynamic content, converting data into well-formatted markdown, and more. It is built by LLM engineers for LLM engineers, providing clean data the way users want it.
Floom.ai
Floom.ai is an AI Marketplace for apps that allows users to easily add AI functions to their applications in just 5 minutes, without requiring any prior AI knowledge. The platform offers a variety of AI functions developed by the community, such as text translation, classification, summarization, keyword extraction, social media post generation, code explanation, code conversion, code improvement, physical address extraction, and SQL query generation. Floom.ai aims to empower developers and businesses to enhance their applications with AI capabilities through a user-friendly and efficient marketplace.
FutureSmart AI
FutureSmart AI is a platform that provides custom Natural Language Processing (NLP) solutions. The platform focuses on integrating Mem0 with LangChain to enhance AI Assistants with Intelligent Memory. It offers tutorials, guides, and practical tips for building applications with large language models (LLMs) to create sophisticated and interactive systems. FutureSmart AI also features internship journeys and practical guides for mastering RAG with LangChain, catering to developers and enthusiasts in the realm of NLP and AI.
Lunary
Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.
ZeroTrusted.ai
ZeroTrusted.ai is a cybersecurity platform that offers an AI Firewall to protect users from data exposure and exploitation by unethical providers or malicious actors. The platform provides features such as anonymity, security, reliability, integrations, and privacy to safeguard sensitive information. ZeroTrusted.ai empowers organizations with cutting-edge encryption techniques, AI & ML technologies, and decentralized storage capabilities for maximum security and compliance with regulations like PCI, GDPR, and NIST.
FinetuneDB
FinetuneDB is an AI fine-tuning platform that allows users to easily create and manage datasets to fine-tune LLMs, evaluate outputs, and iterate on production data. It integrates with open-source and proprietary foundation models, and provides a collaborative editor for building datasets. FinetuneDB also offers a variety of features for evaluating model performance, including human and AI feedback, automated evaluations, and model metrics tracking.
CatGPT
CatGPT is an AI tool designed to provide expert answers to all your cat-related questions. Created by Arpit Agarwal, this tool is based on a LangChain example by Lance Martin. CatGPT leverages artificial intelligence to offer accurate and insightful information on various topics related to cats, helping cat owners and enthusiasts better understand their feline companions.
BenchLLM
BenchLLM is an AI tool designed for AI engineers to evaluate LLM-powered apps by running and evaluating models with a powerful CLI. It allows users to build test suites, choose evaluation strategies, and generate quality reports. The tool supports OpenAI, Langchain, and other APIs out of the box, offering automation, visualization of reports, and monitoring of model performance.
Unfetch
Unfetch is an online IDE that enables users to generate, deploy, and run AI agents to automate various tasks. It combines coding capabilities with an online deployment platform, making it easy to create AI agents. Unfetch agents are designed specifically for AI tasks and are compatible with tools like Open AI GPT Store and Langchain. Users can build and deploy AI agents to solve a wide range of tasks efficiently.
ConvoStack
ConvoStack is a free and open-source full-stack framework that makes it easy for developers to embed a customizable AI chatbot widget into a website with just a few lines of code. It supports popular frameworks such as Pinecone DB, Express, and React, and allows developers to integrate their own AI models using LangChain. ConvoStack is built on a tech stack that is used and loved by developers, and it is designed to be customizable for any use case.
AI ChatDocs
AI ChatDocs is an AI-powered tool that allows you to chat with your documents using ChatGPT. It is based on langchain, a natural language processing platform. With AI ChatDocs, you can ask questions about your documents, get summaries, translate them into different languages, and more. It is a valuable tool for anyone who works with documents on a regular basis.
eSapiens
eSapiens is an AI last-mile delivery platform dedicated to solving real business problems with AI technology. It offers solutions to boost productivity and elevate products by leveraging AI-driven insights and automation. The platform provides features for customer support, sales management, accounting automation, marketing optimization, investment analysis, and product management. eSapiens enables users to streamline operations, make data-driven decisions, and enhance user experience through AI capabilities. With LangChain technology, eSapiens ensures accurate responses and deeper insights. The platform also offers no-code SQL queries for easy data access and automates message management to free up resources and enhance productivity.
LangChain
LangChain is a C# implementation of the LangChain library, which provides a composable way to build applications with LLMs (Large Language Models). It offers a variety of features, including: - A unified interface for interacting with different LLMs, such as OpenAI's GPT-3 and Microsoft's Azure OpenAI Service - A set of pre-built chains that can be used to perform common tasks, such as question answering, summarization, and translation - A flexible API that allows developers to create their own custom chains - A growing community of developers and users who are contributing to the project LangChain is still under development, but it is already being used to build a variety of applications, including chatbots, search engines, and writing assistants. As the project continues to mature, it is expected to become an increasingly valuable tool for developers who want to build applications with LLMs.
langchain
LangChain is a framework for developing Elixir applications powered by language models. It enables applications to connect language models to other data sources and interact with the environment. The library provides components for working with language models and off-the-shelf chains for specific tasks. It aims to assist in building applications that combine large language models with other sources of computation or knowledge. LangChain is written in Elixir and is not aimed for parity with the JavaScript and Python versions due to differences in programming paradigms and design choices. The library is designed to make it easy to integrate language models into applications and expose features, data, and functionality to the models.
langchain_dart
LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).
serverless-chat-langchainjs
This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.
langchainrb
Langchain.rb is a Ruby library that makes it easy to build LLM-powered applications. It provides a unified interface to a variety of LLMs, vector search databases, and other tools, making it easy to build and deploy RAG (Retrieval Augmented Generation) systems and assistants. Langchain.rb is open source and available under the MIT License.
langchaingo
LangChain Go is a Go language implementation of LangChain, a framework for building applications with LLMs through composability. It provides a simple and easy-to-use API for interacting with LLMs, making it easy to add language-based features to your applications.
langchain-benchmarks
A package to help benchmark various LLM related tasks. The benchmarks are organized by end-to-end use cases, and utilize LangSmith heavily. We have several goals in open sourcing this: * Showing how we collect our benchmark datasets for each task * Showing what the benchmark datasets we use for each task is * Showing how we evaluate each task * Encouraging others to benchmark their solutions on these tasks (we are always looking for better ways of doing things!)
langchain-rust
LangChain Rust is a library for building applications with Large Language Models (LLMs) through composability. It provides a set of tools and components that can be used to create conversational agents, document loaders, and other applications that leverage LLMs. LangChain Rust supports a variety of LLMs, including OpenAI, Azure OpenAI, Ollama, and Anthropic Claude. It also supports a variety of embeddings, vector stores, and document loaders. LangChain Rust is designed to be easy to use and extensible, making it a great choice for developers who want to build applications with LLMs.
Langchain-Chatchat
LangChain-Chatchat is an open-source, offline-deployable retrieval-enhanced generation (RAG) large model knowledge base project based on large language models such as ChatGLM and application frameworks such as Langchain. It aims to establish a knowledge base Q&A solution that is friendly to Chinese scenarios, supports open-source models, and can run offline.
langchain-swift
LangChain for Swift. Optimized for iOS, macOS, watchOS (part) and visionOS.(beta) This is a pure client library, no server required
awesome-langchain
LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.
langserve
LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.
awesome-langchain-zh
The awesome-langchain-zh repository is a collection of resources related to LangChain, a framework for building AI applications using large language models (LLMs). The repository includes sections on the LangChain framework itself, other language ports of LangChain, tools for low-code development, services, agents, templates, platforms, open-source projects related to knowledge management and chatbots, as well as learning resources such as notebooks, videos, and articles. It also covers other LLM frameworks and provides additional resources for exploring and working with LLMs. The repository serves as a comprehensive guide for developers and AI enthusiasts interested in leveraging LangChain and LLMs for various applications.
langchain-extract
LangChain Extract is a simple web server that allows you to extract information from text and files using LLMs. It is built using FastAPI, LangChain, and Postgresql. The backend closely follows the extraction use-case documentation and provides a reference implementation of an app that helps to do extraction over data using LLMs. This repository is meant to be a starting point for building your own extraction application which may have slightly different requirements or use cases.
Langchain-Projects-LLM
Langchain-Projects-LLM is a repository containing various projects utilizing Large Language Models such as GPT and LLAMA from HuggingFace and OpenAI. Users need the OpenAI API to run these models.
Hands-On-LangChain-for-LLM-Applications-Development
Practical LangChain tutorials for developing LLM applications, including prompt templates, output parsing, chatbots memory, chains, evaluating applications, building agents using LangChain & OpenAI API, retrieval augmented generation with LangChain, documents loading, splitting, vector database & text embeddings, information retrieval, answering questions from documents, chat with files, and introduction to Open AI function calling.
langchain-decoded
LangChain Decoded is an open-source framework designed to facilitate the development of applications utilizing large language models (LLMs). It can be applied to tasks such as chatbots, text summarization, data generation, code understanding, question answering, and evaluation. The framework consists of various modules like Models, Embeddings, Prompts, Indexes, Memory, Chains, Agents, and Callbacks, each explored in separate Python notebooks. Users can follow the blog post series to understand and utilize LangChain for their projects.
langchain-examples
This repository contains a collection of apps powered by LangChain, an open-source framework designed to aid the development of applications leveraging large language models (LLMs). It can be used for various tasks such as chatbots, text summarisation, data generation, code understanding, question answering, and evaluation. The repository showcases different applications built using LangChain and other tools like OpenAI, Chroma, Gemini, Helicone, Serper API, Pinecone, and Tavily Search API.
kork
Kork is an experimental Langchain chain that helps build natural language APIs powered by LLMs. It allows assembling a natural language API from python functions, generating a prompt for correct program writing, executing programs safely, and controlling the kind of programs LLMs can generate. The language is limited to variable declarations, function invocations, and arithmetic operations, ensuring predictability and safety in production settings.
langgraph-studio
LangGraph Studio is a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. It offers visual graphs and state editing to better understand agent workflows and iterate faster. Users can collaborate with teammates using LangSmith to debug failure modes. The tool integrates with LangSmith and requires Docker installed. Users can create and edit threads, configure graph runs, add interrupts, and support human-in-the-loop workflows. LangGraph Studio allows interactive modification of project config and graph code, with live sync to the interactive graph for easier iteration on long-running agents.