Langsmith LLMOPS Platform By Langchain-Debug ,Monitor And Build Production Grade LLM Application
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- Опубліковано 18 бер 2024
- LangSmith is a platform for building production-grade LLM applications.
It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.
LangSmith is developed by LangChain, the company behind the open source LangChain framework.
github: github.com/krishnaik06/Langsmith
Good Video. Learning a lot from you.
Thank you Krish. A lots of love n respect.
It would be more useful if you could guide us on performing the same for locally saved models too.
Amazing video. Thanks krish waiting for for your future videos
you are so innocent looking while saying " I have updated my OpeniAI API, because the credit balance was less" :) :)
Thanks krish.
Great video
Amazing 🕶❤
Thank you Krish. A lots of love n respect.
Can you do video on evaluations for pdf query code
@krish Naik. Can you please make a video how do we make LLM model from scratch. Not project but LLM model using pytorch or tensorflow. Very less information on that
Thanks so much for your videos🙏 If you will have a chance, could you please help to figure out eval and testing part of LangSmith
@Krish Naik. How to make my LLM model from scratch.
👍🙂👍
I have a very generic question about evaluation of the RAG system. How can we evaluate the responses generated by the RAG system?
RAGAS is a test framework, I started using it in recent times to evaluate RAG
Can we do this with open source model
U r pro bro please explain from scratch
we are providing retrieved information as a context, Will this data get transmitted to Langsmith webspace
, as we are using their url?
Man's dropping W's 🙏🏼🫡🔥
Is it possible to use a different LLM model like a gemini model rather than OpenAI's gpt model while integrating with langsmith?
Hello Sir. I trying to implement the fake news classifier code of your video but i'm getting the error at this line model.add(Embedding(voc_size,embedding_vector_features,input_length=sent_length)) and the error it's showing is Unrecognized keyword arguments passed to Embedding: {'input_length': 20}. If input_length is removed it's giving empty summary table. Can you please help me to resolve this issue.
Are you teaching in inuron.
Thank you sir, Is it support the Arabic language
Are there any alternatives to langsmith?
will this work with local LLM?
Every second day new model new technology 😢
your contents are very generic. Pls do some hard work and demonstrate complex task like "storing log from langsmith into some files or database based on date range"... that kind of videos will be more helpful for experienced techies.