Suggestion : It would be really helpful for viewers and Data Science communities : if next you can make a video on chatbot(maybe chainlit ui) to chat with pdf using langchain any llm(openai/ollama) as a next step, only thing is chatbot should remember chat history(maybe use langchain memories component) so if my first question is : Who is Sachin Tendulkar? and the next follow up question is What is his place of birth? so chatbot should automatically infer that his -> means Sachin Tendulkar. Thanks in Advance.
@thesuriya_35 ай бұрын
i already thought this 💯
@amritsubramanian83845 ай бұрын
hey sks, for that you have this concept called as memory buffer in langchain. You can look to it in LangChain Docs ;)
@shrideeptamboli5 ай бұрын
followed all the 5 videos in less than 24 hrs. Now gotta looks at the documentation for retrieving from multiple documents.
@venkatkrishnan94425 ай бұрын
your videos are too good Krish. If some points are not understood and when I again check back I can get and relate what you are explaining. Thanks for all these very useful videos
@NoDoglapan5 ай бұрын
Your new look reminds me of 70's bollywood villain called 'Shetty' (Rohit Shetty's father) LOL 🤣😛😁 . But in real life you are a hero !!! 🙏
@shashankpandey1966Ай бұрын
I failed an interview today just because i dont know how retrievers works, Thankyou so much for this conceptual learning. Much appreciated. Thanks.
@vos724 ай бұрын
Great hair cut! It suits you! Absolutely love your videos -- they have been very helpful so far! You're an outstanding teacher!
@SantK12085 ай бұрын
You are a gem @krishnaik Sir, i read langchain from multiple platforms but u made it so simple. Now I have more interest on this topic🙂
@zishankhan27635 ай бұрын
If I could I would have liked this series 1000s time, you are awsome person man, I wish you all the very best for the kind work you are doing, Just love you man, big fan
@Rider123743 ай бұрын
you could have liked it 1000 times bcz you are fool.
@abutareqrony45135 ай бұрын
Just an awesome explanation. Love you bro. Make more videos for us.
@AsmaaHANINE-s7j2 ай бұрын
awesome !! so clear. A natural born teacher !
@AvisekSwain-r6v2 ай бұрын
Great videos Krish. You know exactly how to present and make us understand. Are there any specific videos on LangChain Agent ?
@phuloriavivek5 ай бұрын
Hi Krish. Thank you so much for your amazing content. These videos have really been helping me in my GenAI journey. I am stuck in one place though I want to use an output parser -(eg a on the output. But I am not able to do that. Tried a lot of different methods to solve this, but , but not able to debug . If possible, could you please guide how this may be done? Thank you so much in advance.
@techtalksabhishek5 ай бұрын
I am with your look.
@omsundaram43774 ай бұрын
Krish ji , you are looking like Sakal...jokes apart great video and good learning content ..
@andrespineiro76095 ай бұрын
I love this seires. Please dont stop!
@sandeeppvn05035 ай бұрын
Can we use LECL to implement these? It would be helpful if you could show how to use LECL in your future videos also.
@shankarpentyala23903 ай бұрын
The chains seems to be using LCEL
@venkatkrishnan94425 ай бұрын
Will check for different document loaders, mainly the microsoft one :)
@nishantchoudhary32455 ай бұрын
Waiting for next video
@arjunraj39205 ай бұрын
waited for a lifetime to get a response..... my specs are 8gb ram i5 12th will i get some output
@ahmadmponda32945 ай бұрын
Feels like a Shoulin Monk😀 nice
@emiliobravo13855 ай бұрын
You look sharp Mr Naik
@summa75455 ай бұрын
Hi krish, will you create a new episode on usage of various types of retrieval chains? You used retrievalqa in your earlier episode, then bappy did use different retrievar in his episode. Could you provide us a list of scenarios to use specific functions? 😅
@krishnaik065 ай бұрын
Sure
@hamidraza15845 ай бұрын
Looking funny man. Love from Lahore Pakistan
@RahulPrajapati-jg4dg4 ай бұрын
looking Good sir 😃
@SantK12085 ай бұрын
Thanks for the video, could you also please add some topics for RAG -> Qdrant, LLamaindex Parser, Nomic-embeding text
@nandinimatamacedatascince14075 ай бұрын
Very helpful Video , can you make a video on how to load multiple pdf files to create RAG pipeline and connect with azure openai,its will be very useful,currently you are handling with only file.
@iamchiragdahiya19 күн бұрын
can't we use chain like prompt|retriever|llm|output_parser like we did earlier?
@berhanubogale26604 ай бұрын
awesome. You are Good
@omkarjamdar40765 ай бұрын
Please tell the minimum config. of laptop to run this project, and also for 7b model. Are laptops capable of running it if yes recommend future proof ones
@shonrockey61355 ай бұрын
I am not an expert but I think you could buy a laptop which has rtx 3060 graphics card or above it would pretty fast when running 7b model. I am using 2018 acer nitro 5. It has gtx 1050ti graphics and 16 gb ram. I use ollam to run open-source quantized models. It's is slow but it accomplish the task. Either buy a laptop which has graphic rtx 3060 or above. Or buy a mac. Also you could fine tune the models if you have mac or rtx 3060
@meenakshichippa2604 ай бұрын
Krish u look handsome now !!!
@Prashanthsheri-l4x5 ай бұрын
Kindly create an API on RAG with PDF documents rather than just Notebooks
@Prashanthsheri-l4x5 ай бұрын
can you create an API with streamlit UI where user can upload a pdf documents and chat with it .....API and Streamline can do the work..I liked your video
@Danny_DB-xi5lo5 ай бұрын
Hi Krish... Actually I was developing an end-to-end chatbot application for multiple PDF upload from UI with the help of streamlit framework. I used Recursive text splitter and chunking, then huggigface embeddings and chromadb vextorstore. also used Conversational Retrieval Chain. LLM used gpt-3.5-turbo But i am facing issues to get response like repetitive response sometimes, or last query's response if i ask irrelevant questions, sometimes correct response, Can you guide me please
@DoomsdayDatabase5 ай бұрын
Could you provide me your github? I aint Krish but i might know how to help
@prakashmccullum9585 ай бұрын
Hey bro whatsup with your hair style man, it's really cool man, nice
@mukeshvishwakarma62365 ай бұрын
Super cool!
@appikumar-d8l5 ай бұрын
@krish why this is advanced rag concepts, yiu have already explained the retrieverQA concepts right.....i dint get what is tge difference
@malleswararaomaguluri63445 ай бұрын
Hi krish, can you run the same with gpu cuda what are the changes need to apply. Before running llms, how to confirm cuda activated or not. I just checked with tensorflow and pytorch it is detecting xuda version, but this is enough or need to test some more tests. Please reply. Thanks.
@eventsjamaicamobileapp14265 ай бұрын
Great
@ayodeleayodeji44105 ай бұрын
will this video be available to all in your KZbin channel
@sriharshaboini5 ай бұрын
Waiting
@shalabhchaturvedi62905 ай бұрын
Loved it!
@amritsubramanian83845 ай бұрын
Gr8 videoo
@mohsenghafari76525 ай бұрын
tanks krish !
@anshulesh5 ай бұрын
Please make videos of RAFT also.
@khalidkifayat5 ай бұрын
Hi, where to find these RAG Q&A Chatbot With Chain And Retrievers JOBS ONLINE ?? does it require prior building experience ??
@iamchiragdahiya24 күн бұрын
Hello Sir, Ollama Embedding execute karte hue following error is coming, how to resolve? ValueError: Error raised by inference endpoint: HTTPConnectionPool(host='localhost', port=11434): Max retries exceeded with url: /api/embeddings (Caused by NewConnectionError(': Failed to establish a new connection: [WinError 10061] No connection could be made because the target machine actively refused it'))
@thinktrovert5 ай бұрын
When I run: response=retrieval_chain.invoke({"input":"Scaled Dot-Product Attention"}) I am getting this error: TypeError: can only concatenate str (not "ChatPromptValue") to str What to do???
@SujeetKumar-tl3lq5 ай бұрын
Thanks for video, I had question, retrieval_chain.invoke() in this function you are passing only query, where is context, is that optional ?
@shankarpentyala23903 ай бұрын
The retrieval_chain is taking care of getting the context. response = retrieval_chain.invoke({"input": "what is attention"}) response when executed above code, the response is: {'input': 'what is attention', 'context': [Document(page_content='3.2 Attention An attention function can be described as mapping a query and a set of key-value pairs to an output, where the query, keys, values, and output are all vectors. The output is computed as a weighted sum 3', metadata={'source': 'attention.pdf', 'page': 2})], 'answer': 'Based on the provided context from the paper "Attention Is All You Need" by Ashish Vaswani et al., I can answer your question. According to the text, an attention function can be described as mapping a query and a set of key-value pairs to an output, where the query, keys, values, and output are all vectors. The output is computed as a weighted sum. In simpler terms, attention refers to a mechanism that allows a model to focus on specific parts of an input sequence (or key-value pairs) based on their relevance or importance. This process involves comparing the input sequence with the query vector and computing weights for each position in the input sequence. The output is then computed by taking a weighted sum of the values, where the weights are learned during training. Attention has been used successfully in various tasks such as reading comprehension, abstractive summarization, textual entailment, and learning task-independent sentence representations. Please let me know if you find this answer helpful!'} It has your input,context and answer fields
@nehapradhan4984 ай бұрын
Hi, when I run : retrieval_chain = create_retrieval_chain(retriever,document_chain), I keep on getting this error: AttributeError: 'function' object has no attribute 'with_config' Does anyone know how to fix it?
@commoncats54375 ай бұрын
reddy garo😝🔥🔥
@saliltrehan42555 ай бұрын
It is true! Hehe
@nishantchoudhary32455 ай бұрын
❤
@twinklepardeshi31135 ай бұрын
First comment ❤
@rishiraj25485 ай бұрын
🙏
@Rider123743 ай бұрын
You just tell how to use tools but not why to use . It's a very bad approach whether you like it or not, but that's the truth and try to improve it.
@twinklepardeshi31135 ай бұрын
First like
@yusufansari32035 ай бұрын
Krish Sir I am getting this error: ValueError: Error raised by inference endpoint: HTTPConnectionPool(host='localhost', port=11434): Max retries exceeded with url: /api/embeddings (Caused by NewConnectionError(': Failed to establish a new connection: [WinError 10061] No connection could be made because the target machine actively refused it')) Please help me out!
@jayaprakash73485 ай бұрын
I am also getting same error from "retrieval_chain.invoke" method. Please help us with the solution @Krish Ji
@keerthipriya34164 ай бұрын
@@jayaprakash7348 I also got the same error, downloading ollama and running llama2 model locally will fix this!
@keerthipriya34164 ай бұрын
@@jayaprakash7348 I also got the same error. downloading ollama and running llama model locally would fix this.