What is LangChain?

LangChain became immensely popular when it was launched in 2022, but how can it impact your development and application of AI models, Large Language Models (LLM) in particular. In this video Martin Keen shares an overview of the features and uses of LangChain.

[alexiscao]

After watching a ton of courses on coursera developed by prestigious universities, and tech companies like google, meta, etc., I found IBM' courses are the best: comprehensive, clear and concise! Thank you

[tubero]

Just want to thank the wonderful presenters for this excellent series and IBM for its commitment, innovation, and broad contribution to education in this field.

[supankanlavanathan]

- [00:00] 🛠 LangChain Overview
- LangChain is an open-source framework for developing applications utilizing large language models (LLMs).
- Components of LangChain include abstractions, LLM modules, prompts, and chains, streamlining the programming of LLM applications.

- [01:26] 🔄 Abstractions in LangChain
- Abstractions in LangChain simplify complex NLP tasks by representing common steps and concepts necessary to work with language models.
- These abstractions can be chained together to create applications, minimizing the amount of code required.

- [02:22] 🔗 Components of LangChain
- LangChain comprises LLM modules, prompts, and chains, enabling developers to integrate different models and execute sequential functions to achieve desired tasks.
- Components like prompts formalize the composition of instructions given to LLMs, facilitating the development process.

- [03:47] 📊 Data Handling in LangChain
- LangChain supports various data handling mechanisms, including document loaders and text splitters, enabling access to external data sources and efficient text processing.
- Vector databases and memory utilities enhance data retrieval and management within LangChain applications.

- [06:09] 🤖 LangChain Use Cases
- LangChain facilitates diverse applications such as chatbots, summarization, question answering, data augmentation, and virtual agents.
- Integration with existing workflows and robotic process automation (RPA) enhances the functionality of LangChain.

[unirico]

Great work! The best video to understand LangChane in only a few minutes.Thank you!

[HitteshAhuja]

Probably the only channel that doesnt 'plugin' their app or service ( read Google) to explain a topic !

[ghaith]

I can't put into words how much I loved this video, as a complete novice into langchain I now know more than I expected to, everything is now clear in my mind, thank you from the bottom of my heart <3

[nditahsamweld]

Best description of LangChain I have watched

[muhammadhilal]

This video made it easier for me to understand the LangChain, and also the elements I will be learning during RAG.

[mpicuser]

This video helped me understand better about Langchain.

[softvision]

LangChain exists a long time and its community is huge. Nice to finally get an intro from IBM about that long existing technology and community product.

[seatube]

Great video! I just published a chat bot for home brewers, but it’s a bit basic so a friend of mine recommended using langchain to have it provide better responses and take meaningful actions. This was really helpful for me to get started, thank you!

[josewaihiga]

Thank you for a very instructional video. I loved the format :)

[tyronefrielinghaus]

martin KEEN(nominative determinism at work?) is my all-time fav IBM presenter! THis one no exception Great, clear expo of LangChain..

[vectorautomationsystems]

Pure gold! Thanks a lot for this. Best regards from Nairobi, Kenya

[carlosenriquecastanedaguti]

Excellent explanation, thanks very much. It was very useful

[fluffyunicorn]

I was a little scared that this would be a blockchain thing.

[rahulwale_.]

00:01 LangChain is an orchestration framework for large language model applications.
00:58 LangChain is a fast-growing open-source project with utility in streamlining LLM applications.
02:05 LangChain standardizes llm interface
03:05 LangChain enables sequential chains of functions in applications.
04:06 LangChain's document loaders work with third-party applications for importing data sources.
05:11 LangChain solves the issue of retaining conversation memory
06:14 LangChain offers chatbot integration and text summarization capabilities.
07:15 LangChain enables autonomous actions with language models and RPA.

[antoniopavoni]

Thank you very much for this introduction! I found it really useful and helps me navigate all the information and new programs around AI. Would you be able to provide few examples on what can we built on langchain ?

[mjacfardk]

Thank you, Great tutorial, and easy to understand manner. We would like to ask you to explain about Lang chain concepts like indexes and chains.
thank u again.

[Ramkumar-ujfo]

You're pointing out that while humans, even those in scientific fields, might not prefer to use complex models like graph theory for direct communication, they prioritize these methods when designing machine communication systems. This reflects the focus on efficiency and precision in machine interactions, which differs from how humans naturally communicate.

ChatGPT ❤🎉