Building the Future with LLMs, LangChain, & Pinecone
Join Harrison Chase, the creator of the breakout library LangChain, and James Briggs, developer advocate at Pinecone, as we explore the new age of AI and it's biggest enabler - LangChain.
You’ve seen endless examples of developers and engineers building AI-powered apps in record time using LLMs, LangChain, and Pinecone. We’re in a special moment in history where rule-based processes get replaced by powerful AI systems. At the center of this paradigm shift are Large Language Models (LLMs), vector databa\ses like Pinecone, and the LangChain library. In this online workshop, we’ll explore the tools behind this new wave of technology and how to wield them to build mind-blowing applications.
🔗 Link to slides:
docs.google.com/presentation/...
🔗 Link to notebook:
github.com/pinecone-io/exampl...
You guys are living legends. Bleeding edge shit, and Harrison, your enthusiasm is infectious. Langchain and Pinecone are going to be 2 pillars of the open source AI renaissance that is already starting. Keep up the good work! I am consuming everything you're putting out there and want more.
But the cheapest hosting plan on pinecone is 70 bucks a nonth
@@blackenedblue5401 Weird, I'm doing pay as you go, but also interested in others. Any you recommend? Especially ones that have extra features for multi-modal data
@@blackenedblue5401 that sounds cheap for any business
They will be acquired or AWS will have serverless acorn
sure Amazon is a monster trying to consume all of it's rivals. But in some rare cases when the prey have unique and strong inno-stack, they will survive.@@Chris-se3nc
Amazing content, im loving to work with langchain and pinecone to create usefull tools! Thanks a lot for all this free courses and for your time! Being from a third world country, and having all this access for free its incredible impact. This will change how the world move! Lets go LATAM!
Harrison I recently saw an interesting statement “the fastest growing programming language is English”. Thank you so much for creating Langchain and James thank you for your incredible tutorials and insights. ❤
It is unlikely that programming languages can be efficiently translated into English or any other natural language. Programming languages are designed to be precise and unambiguous, and they rely on a specific syntax and grammar to express their meaning. Natural languages like English, on the other hand, are much more flexible and often rely on context and interpretation to convey meaning. While there may be some efforts to make programming languages more accessible by translating certain keywords and commands into natural language equivalents, such as using "if" instead of "if statement," this approach may introduce additional ambiguity and can make code harder to read and understand for experienced programmers. Ultimately, the most effective way to learn and work with programming languages is to become familiar with their specific syntax and grammar. This allows programmers to write code that is precise, efficient, and easy to read and understand by others who are familiar with the same programming language.
@@eyemazed i think the use case here needs to be clarified. As we can see from openai cataclysm project, GPTforall and lanchain these LLMs employ agents which write perfect utility code on the fly in order to perform a task. The humans speak english to the LLM who then write whatever code is necessary to complete the task. There is abstraction layer in this use case which eliminates the need to translate speech to code. The speech triggers openai actions which writes the code it needs
Really great from Harrison 🎉
Thank you for educating those of us new to the LLM field how to use your applications. I did not get the powerpoint. May get a link to the repo please?
Awesome video and content! Some few tips since this is so good content. I have hearing problems so it would be really awesome if you could use studio microphones and also record in higher quality to give a better video and audio output. Anyhow, thank you for taking your time and provide all these information 🤗
Incredibly informative. Thanks 🙏
Sick! Going to build some stuff on this asap
Hi I have a question. I am using GPT-3 for the task of few-shot text classification, I have tried directly GPT-3 and also via LangChain (using the same few-shot examples for both, the same format of the prompt (the one from LangChain formatter) and the same features of GPT-3). I had better results when I used LangChain. Is there any explanation why LangChain performed better than directly using GPT-3? thanks
This video should inspire a lot of use cases.
Can you link to the Colab example please?
Love this content!
great work , i asked chatgpt what is Langchain, it doesnt give any helpful information as data limit is Sep 2021, your documentation helped me understand this wonderful tool and concept.
Thanks, it is amazing
agents + Pinecone+ Zapier = true ai assistance.
Maybe use semantic drift as a chunking metric/cutoff.
wow thank you
Is LangChain similar to Microsoft's Open Source Semantic Kernel?
Very good, informative #RAG
Does langchain work with weaviate?
Yes. Weaviate YT channel has video on it. Best online resource working with langchain is with pinecone. I saw on LinkedIN about PLOP Python Langchain OpenAI Pinecone stack.
Yes 🎉
I want to contribute on this project
Always start your videos with a cord.
I’m trying to grasp how Azure OpenAI compares to this approach? Is it doing something similar behind the scenes?
Do vector databases also apply to computer code and not just natural language?
and how does it give "meaning" to a chunk of text and is it the job of the embeddings mechanism to do that and then store it to a vectorDB ? can you combine traditional DB's ( mysql and postgres ) with vectorDB's to improve search?
Yes, they do. Determining how you break your files up before embedding seems important; you don’t want to cut functions in the middle, or remove relevant context
@@itsjustmeemman it's the embedding mechanism that does the semantic conditioning. The vector DB just lets you efficiently search/cluster the embedded space. You have to use the same embedding process on your input to the database, since the database is basically just doing distance calculations.
Hey I know u r looking at my comment, u r really awesome 😎
Could you please provide me with this presentation, I need to educate others with this!
interesting
Do the Alpaca too not just the OpenAI since why called it LLMs if there is only OpenAI supported
There are many available
#early :)
Damn… type safety on the output.. what the heck is coding now? What does this even imply what theeee
Streaming AI Paradigm Shift 2023 WoW So Exciting & So Scary I mean we really need to Drop Approximations when it comes to Math, and Get the Exact Solution in Front or you can create a Monster on the Molecular level. Remember This and call me when realize what I am WARNING you about please.
Amomg all the presentations in KZhead this one seems the most likely done by crooks trying to take your money. It's just ridiculously bad quality. F the KZhead algorithm. .
Could you share an example of a better one?
Amomg all the presentations in KZhead this one seems the most likely done by crooks trying to take your money. It's just ridiculously bad quality. F the KZhead algorithm. .