8 open-source LangChain alternatives
Tags: ai, llm, langchain
Published: 2023-10-05 08:35:55

---
title: 8 open-source LangChain alternatives
published: true
date: 2023-06-13 22:00:00 UTC
tags: ai, llm, langchain
canonical_url: https://blog.apify.com/langchain-alternatives/
---

 **Hey, were** [**Apify**](https://apify.it/data-for-ai) **, and our mission is to make the web more programmable. Part of that is getting better data for AI and LLMs, so we've been using and integrating with LangChain extensively these last few months.** [**Check us out**](https://apify.it/data-for-ai) **.**

## **What is LangChain?**

There have been so many rapid developments in AI since ChatGPT hit the scene that it's tempting to dismiss every new tool as yet another attempt to jump on the bandwagon and strike while the iron is hot. It wouldn't be unreasonable to assume that many hyped-up AI tools will become obsolete before 2023 is done with us. But [LangChain](https://python.langchain.com/en/latest/) is likely to be an exception.

{% embed https://youtu.be/zcfeiVdiGJg %}

For those unfamiliar with it, LangChain is a framework for developing applications powered by language models. Not only can it call a language model via an API, but it can also connect LLMs, like GPT-4, LLaMDA, and LLaMA, to other sources of data, such as Google Drive, Notion, Wikipedia, or even [**Apify Actors**](https://docs.apify.com/platform/actors?ref=blog.apify.com), and allow them to interact with their environment. You can chain commands together so the AI model can know what it needs to do to produce the results or perform the actions you require.

🦜🔗 [**How to get started with LangChain**](https://blog.apify.com/what-is-langchain/#how-to-get-started-with-langchain)

## **Why would you want a LangChain alternative?**

LangChain started in the latter half of 2022 as an open-source project, but its meteoric rise to fame swiftly transformed it into a startup. In the meantime, many tools posing as alternatives have come out of the woodwork. While there is some overlap, the alternatives that have emerged were designed with slightly different purposes in mind. Depending on your project, some of these open-source alternatives might be better suited to your needs or could be used in conjunction with LangChain. But to understand some of the differences between LangChain and its alternatives, you need to know about a couple of LangChain's core features.

🦜🔗 [**How to integrate Apify with LangChain**](https://docs.apify.com/platform/integrations/langchain)

## **LangChain features**

### **Agents**

One of LangChain's distinct features is agents (not to be confused with the sentient eradication programs of _The Matrix_). Agents are a method of using a language model as a reasoning engine to determine how to interact with the outside world based on the user's input. Agents have access to a suite of tools and, depending on the input, an agent can decide which tools to call.

### **Memory**

By default, LLMs process each query independently of other interactions. But LangChain provides memory components to manage and manipulate previous chat messages and incorporate them into chains. LangChain's memory components can be used to _retrieve data from_ memory or _store data in_ memory. This is particularly important for chatbots, for example, which need to remember previous conversations.

🦜🔗 [**How to use LangChain with OpenAI, Pinecone, and Apify**](https://blog.apify.com/how-to-use-langchain/)

## **8 open-source LangChain alternatives**

Now that you have some idea of what LangChain is for let's go through some of the alternatives and their features to see how they compare.

### **1.** [**FlowiseAI**](https://flowiseai.com/)

FlowiseAI is a drag-and-drop UI for building LLM flows and developing LangChain apps. It's an excellent choice for developers who want to construct large language models. At the same time, it's aimed at organizations that want to develop LLM apps but lack the means to employ a developer. You can use Flowise AI to build apps such as chatbots, virtual assistants, and data analysis tools.

> [**_Learn how to integrate Apify with FlowiseAI_**](https://docs.apify.com/platform/integrations/flowise)

### **2.** [**Auto-GPT**](https://autogpt.net/)

Auto-GPT is a software program that allows you to configure and deploy autonomous AI agents and aims to transform GPT-4 into a fully autonomous chatbot. While LangChain is a toolkit that connects various LLMs and utility packages to create customized applications, Auto-GPT is designed to execute codes and commands to deliver specific goal-oriented solutions with an output that's easy to understand. While impressive, at this stage, Auto-GPT has a tendency to get stuck in infinite logic loops and rabbit holes.

> [**_How to get ChatGPT to access the internet_**](https://blog.apify.com/gpt-scraper-chatgpt-access-internet/)

### **3.** [**AgentGPT**](https://agentgpt.reworkd.ai/)

AgentGPT is designed for organizations that wish to deploy autonomous AI agents in their browsers. While Auto-GPT operates independently and generates its own prompts, Agent GPT depends on user inputs and works by interacting with humans to achieve tasks. Though still in the beta stage, AgentGPT currently provides long-term memory and web browsing capabilities.

> [**_Reverse engineering code with ChatGPT_**](https://blog.apify.com/chatgpt-reverse-engineer-code/)

### **4.** [**BabyAGI**](https://github.com/yoheinakajima/babyagi)

BabyAGI is a Python script that acts as an AI-powered task manager. It uses OpenAI, LangChain, and [**vector databases**](https://blog.apify.com/what-is-a-vector-database/), such as Chroma and [**Pinecone**](https://blog.apify.com/what-is-pinecone-why-use-it-with-llms/), to create, prioritize, and execute tasks. It does this by selecting a task from a list and sending the task to an agent, which uses OpenAI to complete the task based on context. The vector database then enriches and stores the result. BabyAGI then goes on to create new tasks and reprioritizes the list according to the result and objective of the previous task.

> [**_How to collect data for LLMs_**](https://blog.apify.com/webscraping-ai-data-for-llms/)

### **5.** [**LangDock**](https://www.langdock.com/)

LangDock was built for developers searching for an all-in-one product suite for creating, testing, deploying, and monitoring their LLM plugins. It lets you add your API documentation manually or import an existing OpenAPI specification.

> [**_AI web scraping tools: do they really work?_**](https://blog.apify.com/ai-web-scraping-tools/)

### **6.** [**GradientJ**](https://gradientj.com/)

GradientJ is a tool for developers looking to build and manage large language model applications. It lets you orchestrate and manage complex applications by chaining prompts and knowledge bases into complex APIs and enhances the accuracy of your models by integrating them with your proprietary data.

> [**_Improve AI with web scraping and data augmentation_**](https://blog.apify.com/improve-ai-models-web-scraping-data-augmentation/)

### **7.** [**TensorFlow**](https://www.tensorflow.org/)

An end-to-end machine learning platform, TensorFlow enables developers to easily build and deploy ML-powered applications. Its Keras API allows for immediate model iteration and easy debugging. You can train and deploy models in the cloud, in a browser, or on a device in any programming language.

> [**_PyTorch vs. TensorFlow for deep learning_**](https://blog.apify.com/pytorch-vs-tensorflow/)

### **8.** [**LlamaIndex**](https://gpt-index.readthedocs.io/en/latest/)

The final alternative on our list is LlamaIndex. While LangChain is primarily for chaining multiple tools together, LlamaIndex is fundamentally a smart storage mechanism. At a high level, LlamaIndex gives you the ability to query your data for any downstream LLM use case, whether its question-answering, summarization, or a component in a chatbot.

> [**_You can load data into LlamaIndex with Apify Actor Loader and use it as a Tool in a LangChain Agent_**](https://llamahub.ai/l/apify-actor)

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**Need data for your AI models? Find out** [**how to collect data for AI and machine learning**](https://apify.com/data-for-generative-ai) **.**