Langchain Reviews & Product Details

The platform is easy to use, even if you only have a basic understanding of AI concepts. I found that navigating the features didn't require advanced technical knowledge, which made the experience straightforward and accessible. Review collected by and hosted on G2.com.

Sometimes, other frameworks appear to be simpler. Review collected by and hosted on G2.com.

Langchain is the best framework for building RAG applications its supports all find of Large Language Models that is both open-source like llama, mistral and closed-source models like OpenAI, and Anthropic using their Access token. It also supports using local LLMs using the Ollama. I build RAG application for our enterprise data using it , its very simple to build and it has many features like a chain of thoughts and memory. They have clean documentation which we can refer to and add more features. We can easily integrate with their other products like Langsmith and Langgraph Review collected by and hosted on G2.com.

I didn't feel any downside while using the Langchain but one thing is they have many version depecdences which will through error if you don't install the correct version. Review collected by and hosted on G2.com.

What I like best about LangChain is its flexibility to integrate models, data sources, and tools seamlessly, which made building and scaling complex LLM-powered workflows much faster in my projects. Review collected by and hosted on G2.com.

What I dislike about LangChain is that its rapid updates sometimes break existing code or change APIs, which can make maintaining long-term projects a bit challenging. Review collected by and hosted on G2.com.

Langchain is used to connect multi-agent system in your application. We used Langgraph which is based on Langchain that helps us orchestrate multiple workflows. It is easy to integrate and supports master-slave architecture. Review collected by and hosted on G2.com.

it tries to do everything in the LLM ecosystem, and that comes with trade-offs. Review collected by and hosted on G2.com.

open source Framework, modular architecture, and easy to integrate LLM models with external data. easy to use and create component like chains, agents etc. Review collected by and hosted on G2.com.

During the debugging the whole workflow, sometime Abstraction layers make it hard to trace issues or optimize performance, particularly with large-scale applications. Also, the rapid pace of updates can lead to deprecated features or breaking changes, which can frustrate developers trying to keep up. Review collected by and hosted on G2.com.

Honestly, what I love most about LangChain is how it takes the fear out of working with large language models. Before I found it, trying to piece everything together — APIs, memory, logic, vector stores — felt like wrestling with a bunch of puzzle pieces that didn’t quite fit. But LangChain gives you a solid toolkit that actually makes sense. It’s super modular and flexible, and once you get the hang of it, things just click. I’ve been able to build full LLM workflows way faster than before, and the best part is, I’m not stuck starting from scratch every time I want to try something new. Review collected by and hosted on G2.com.

While I like to work with LangChain, sometimes it does feel a bit daunting when diving into the documentation or trying to wrap your head around how all the various modules fit together. There is a learning curve, and particularly when you're just starting out. Also, because the ecosystem is moving so quickly, things will break or change unexpectedly, and it's hard to keep up if you're actually deploying it in production. A bit more stability and more examples would be wonderful. Review collected by and hosted on G2.com.

Langchain you can create any agent and app with integrate api key control flow which i feel best and langchain produce high quality agent and app Review collected by and hosted on G2.com.

Langchain work on control flow basically we need to integrate api and than that product will work based on your actions so may be in this case you cannot make best product so you should have knowledge deeply about drag and drop functions Review collected by and hosted on G2.com.

Experiment Tracking via prompt templates,

Integration with Vector Database,

Pipeline Composition allowing mw to separate data ingestion, transformation and inference stages,

Reproducibility- it helps me LLM-powered workflows for CI/CD deployment. Review collected by and hosted on G2.com.

I have been facing complexity in debugging and challenges in scaling.

It has fast-evolving APIs which makes it difficult to track the backward copatibility. Review collected by and hosted on G2.com.

I just say use it and ease your work and this will save your time and efficient your work Review collected by and hosted on G2.com.

Nothing I observed which could I can say useless It was really good tool Review collected by and hosted on G2.com.

It's easy to use and does heavy lifting in the backend also it's open source community is good Review collected by and hosted on G2.com.

I don't dislike anything everything looks good only Review collected by and hosted on G2.com.