please i need the souce code zip file

I would like to know how to HOST this CUSTOM model in cloud... please? anyone?

hi pradip , your vedios are very useful, can we inegrate like if give any slot value in Amazon lex bot and it will hit API via Lambda and get the response back to the Lex.If yes then please show us how we can achieve

Is it possible to interface with Sybase DB?

Very useful information in the video. Thanks.!

Here how did you get the code that you have been using in the lambda function

very helpful. thank you!

Hi, it can be observed in the "table_details.py" file written in VS code, that there is no mention of Message placeholder to save the chat history while defining the prompt for selected tables. That may cause the chain() module to train on the entire list of tables in the database when the input is "List the names." Will it not? If someone may kindly advise me on this issue. Thank you so much for such an informative session. Cheers!!

Easy Interpretation!! Kudos

learnt about the helpful langsmith, and also your thought of generating sql query. but when dealing with database column recognizing it's not so precise with this method...looking for knowledge graph based ways. but thanks a lot any way! :)

very useful video

Nice project. How do I obtain the T-SQL query that was generated in this chatbot coding?

Can you make a video on vllm and kubernetes to be used with lang graph

Thank you for the useful video! Can Textract extract text from Bulgarian and return it in Bulgarian language or only English text?

Thank you for this great Video. Wating for next video!!!!!!

Hi Pradip, Thanks for the video. I am getting this exception , Could you please help me to fix? "langchain_core.exceptions.OutputParserException: This output parser can only be used with a chat generation." Instead of OpenAI, I am using Google Palm LLM and Huggingface Embeddings

Hello Pradip, thanks for your great session. I am learner in AI, I am using sqlcoder 7b-2 model along with langchain and huggingface, here I am stuck with create_extraction_chain_pydantic function, not getting what we can use in place of this function, if u can guide me it will be great help. Thanks in advance.

Best life best view

It's a nice tutorial brother.

if I want to use mic then what should I do?

how to do in node.js?

Thanks for the video, I can understand easily from your explanation.

I don't know why but I have already added all rights and to the right base. Still , when I access it says Invalid authorisation

I tried a model, and api said max 10 candidates

Will it be able to generate charts like if we ask to draw bar chart or line chart?

This video is just awesome. Thank you. Is there a way I can plot the graph epoch vs accuracy?

It's a great video. Could you please give me the link for the notebook? I want to get the csv file

Thanks for amazing video! followed your code bas and all looks good.only problem is create_extraction_chain_pyndantic is not able to extract table name

I am facing the issue deploy on AWS ec2 can u explain 😊

can i give my own aspect and train model accordingly

This is a really nice tutorial and a set of code. Especially the implementation of memory to make it super efficient. I am trying to make some minor changes. I am making use of Snowflake Databases. In this case, the url for connection with sqlalchemy has the database name and schema name as compulsory. This doesn't allow me to access data across multiple schemas for the Chatbot. If I go for multiple db objects, each for one schema, Is it possible to combine them in a single chain for creating the generate_query object??

i need to implement this function calling in vocode, for live calling (voice AI assistant), How can i ?

Great guide..One doubt..is this a better approach in 2024, given this tutorial was made in 2022 ? Do you recommend the same method now or using the latest LLMs ?

hi there im actually quite new with aws i would like to know in this tutorial how to get the menu at 14:03 to send the json request

Hi , Thanks for the video, I am trying to query a multi-tenant db and I want only admin to access all the data while others to see only their relevant data, how can I establish this feature on the top of the base model

is this method possible when using AWS Bedrock to create my chatbot, rather than Amazon lex?

need a separete video tutorial for how to login in kommunicate. im trying for weeks but unable to get that so..please cover a video on that

Unable to login.. Its accessing permissions only for business emails is there any alternate option??

Can we do this via Azure Open AI?

Sir is it required to have open ai key or call openai library as i want q&a using the provided document only?

Hi I wanted work on the establishing an SQL agent with chatgpt, but I wanted make a project in such a way where if I ask question related to database then I get response based on data I have in DB, and if I prompt something generic it shud give a generic answer... Is that possible?

So, the model will just try to find the best match category according to the meaning of the class?

Thank you, crisp and clear explanation,

Can you use any other opensource model rather than using chatgpt

How can we make a chatbot retrieving the data through custom website

Great video .!

have a use case with a haven't seen anywhere: I create a private GPT that has documents as contexts. This documents has criteria for a specific subject I give it system instructions so its function is to evaluate a user document that it's attached as a part of the prompt, to see if the document complies with the criteria in the context documents, and give detail response on the result of evaluation and the justification that includes, the content of the user document and the criteria in the context documents. I want to do that in LangChain but I don't know hot to add a user document as a part of the prompt for the RAG.. It would be great if you can you explain how to approach this implementation. Thanks you for the content!! Keep the good work.

It's humble request to don't say again and again "You know"

Oh good. I’m sure no one would ever use this to filter out negative opinions on certain controversial topics. Definitely not a thing any major corporation that owns media platforms would do.

That's amazing, congratulations and thank you very much for making your time available to share you knowledge.