At 1:01:36 I got an error: "PydanticUserError: If you use `@root_validator` with pre=False (the default) you MUST specify `skip_on_failure=True`. Note that `@root_validator` is deprecated and should be replaced with `@model_validator`." Please resolve this...😣
nice. quick question/ some are using anaconda, some jupiter and some using local . but would we complete and how to share the application to users, is through Azure Open AI service or any other UI? and also is it integrated with Azure DevOps code chnages? and how to move the code from dev to uat to PRD. these are the main things in the projects and if this is covered it will be apprecicated
Finally after so much of trail and error, got the response for the model. Vector database invocation has changed a lot. Guys please take that into notice. Thanks for the session Bappy.
1:29:53 AttributeError: init is no longer a top-level attribute of the pinecone package., This error can not be solved, If any solution any expert write , it will bw grateful to completion of this project.
try using this from pinecone import Pinecone as PineconeClient from langchain_community.vectorstores import Pinecone as PineconeLang pc = PineconeClient(api_key=PINECONE_API_KEY) docsearch = PineconeLang.from_texts([t.page_content for t in text_chunks],embedding=embeddings, index_name = INDEX_NAME)
Pinecone has no attribute 'from_texts' errors is occuring when using Langchain due to a namespace collision. The Python classes for both Langchain and Pinecone have objects named Pinecone. With the pinecone-client v3 there have been some modifications. Instead of using "from langchain.vectorstores import Pinecone" you need to use "from langchain_pinecone import PineconeVectorStore". Make sure that the pinecone-client you install is v3.x. For no errors make sure to set PINECONE_API_KEY as an environment variable. os.environ['PINECONE_API_KEY'] = '....' then you can use index_name = 'your_index_name' docsearch = PineconeVectorStore.from_documents( text_chunks, embeddings, index_name = index_name )
from langchain_pinecone import PineconeVectorStore pc = pinecone.Pinecone(api_key= os.environ['PINECONE_API_KEY'] , environment= PINECONE_API_ENV) index_name = "medical-chatbot" index = pc.Index(index_name) docs_chunks =[t.page_content for t in text_chunks] docsearch = PineconeVectorStore.from_texts(docs_chunks ,embeddings, index_name=index_name) this might work @@sayed5603
any solution for this error ?? qa=RetrievalQA.from_chain_type( llm=llm, chain_type="stuff", retriever=docsearch.as_retriever(search_kwargs={'k': 2}), return_source_documents=True, chain_type_kwargs=chain_type_kwargs) ValidationError: 1 validation error for RetrievalQA retriever Can't instantiate abstract class BaseRetriever without an implementation for abstract methods '_aget_relevant_documents', '_get_relevant_documents' (type=type_error)
i am getting error in this code qa=RetrievalQA.from_chain_type( llm=llm, chain_type="stuff", retriever=index.as_retriever(search_kwargs={'k': 2}), return_source_documents=True, chain_type_kwargs=chain_type_kwargs) if anyone knows , how to resolve ,please help
Great thanks!! If I can know If I follow the video and apply the practical step by step with you, will I get a complete project in the end or are there some things that are not explained in the video , because I find it difficult to create projects and to develop this skill I decided to start by imitating some of the projects explained at the beginning so that I can later create the projects myself
I am asking this question because I was trying to implement projects from other channels, but in the end I was surprised that there were parts of the project that were not explained or that the project was incomplete and only some of its parts were implemented. I hope you answer thank you
Just check the langchain pinecone documentation and just copy paste the code. Also create a .env file in your project root directory with the PINECONE_API_KEY storing the api key string. And don't forget to restart the kernel after creating the .env file
Hey, You can make projects by following videos. But you will need to study up and read the documentation to actually understand what is going on and what the code does
@@yahyaahmed8875 This video explains the stuff very well, its good for beginners. But I do recommend learning more about langchain and vector databases a bit before doing this project. There is this course on Udemy for Langchain by Eden Marco. I really recommend to do that .
Pinecone has no attribute 'from_texts' errors is occuring when using Langchain due to a namespace collision. The Python classes for both Langchain and Pinecone have objects named Pinecone. With the pinecone-client v3 there have been some modifications. Instead of using "from langchain.vectorstores import Pinecone" you need to use "from langchain_pinecone import PineconeVectorStore". Make sure that the pinecone-client you install is v3.x. For no errors make sure to set PINECONE_API_KEY as an environment variable. os.environ['PINECONE_API_KEY'] = '....' then you can use index_name = 'your_index_name' docsearch = PineconeVectorStore.from_documents( text_chunks, embeddings, index_name = index_name )
@@funnybonner2113 aur mene 4 pdfs se vector database banaya h to merko 120 mins lage databse bana ne mei to most prob utna time lagega agar ek pdf use krni hai to baaki pdfs hata lena
@@dipendrapratap6495 very very thanks brother for your comment....I need your help in that...... Kya transformer pre trained used kar Rahe hai hugging face sa ya hud apna train kia hai .....??
does anyone experience this error? need help on it qa=RetrievalQA.from_chain_type( llm=llm, chain_type="stuff", retriever=docsearch.as_retriever(search_kwargs={'k': 2}), return_source_documents=True, chain_type_kwargs=chain_type_kwargs) ValidationError: 1 validation error for RetrievalQA retriever Can't instantiate abstract class BaseRetriever without an implementation for abstract methods '_aget_relevant_documents', '_get_relevant_documents' (type=type_error)
docsearch=Pinecone.from_texts([t.page_content for t in text_chunks], embeddings, index_name=index_name) i am getting here error as pinecone is not defined
from langchain_pinecone import PineconeVectorStore pc = pinecone.Pinecone(api_key= os.environ['PINECONE_API_KEY'] , environment= PINECONE_API_ENV) index_name = "medical-chatbot" index = pc.Index(index_name) docs_chunks =[t.page_content for t in text_chunks] docsearch = PineconeVectorStore.from_texts(docs_chunks ,embeddings, index_name=index_name) this might work
@@shrutibisht2977 thanks, still there is issue while importing: from langchain_pinecone.vectorstores import PineconeVectorStore, if possible please help
![ผัวเถื่อน - ยูริ โตเกียวมิวสิค [ OFFICIAL MUSIC VIDEO ]](http://i.ytimg.com/vi/P08ORRVDGl8/mqdefault.jpg)
Checkout our Free Generative AI Course - ineuron.ai/course/generative-ai-community-edition
It seems genAI projects are quite simpler then core machine learning projects
Not at all. Building is one part and getting desired output is whole another story. It gets really complicated at that point.
not getting pinecone index enviorment option
ans- they stop providing it free
Good morning sir, I'm sidhanta
how can we connect to pinecone serverless for this project
At 1:01:36 I got an error: "PydanticUserError: If you use `@root_validator` with pre=False (the default) you MUST specify `skip_on_failure=True`. Note that `@root_validator` is deprecated and should be replaced with `@model_validator`." Please resolve this...😣
install this pydantic version:
pip install pydantic==1.10.9
Hi i am also getting the same error, did you got any solution please help
nice. quick question/ some are using anaconda, some jupiter and some using local . but would we complete and how to share the application to users, is through Azure Open AI service or any other UI? and also is it integrated with Azure DevOps code chnages? and how to move the code from dev to uat to PRD. these are the main things in the projects and if this is covered it will be apprecicated
sir how can i make chatbot for dynamic website which gets data from third party api
Can anyone give me the project summary for Resume
Finally after so much of trail and error, got the response for the model. Vector database invocation has changed a lot. Guys please take that into notice.
Thanks for the session Bappy.
HI! can you please suggest some steps i can follow to make it work, i am facing similar issues.
can you share the working code? it will be really helpful.
A great project by bappy sir
i m facing problem while connecting to pinecone . in pinecone , i found different while comparing to yours.
yes ..please tell me how u solved it
Where is the source code
can anyone help me in running this project according to the updated version
wdym?
1:29:53 AttributeError: init is no longer a top-level attribute of the pinecone package., This error can not be solved, If any solution any expert write , it will bw grateful to completion of this project.
i am facing the same error did you got any solution to it?
@@bhavyashah7904Bro are you available. i facing with from_texts.. error.
Did you got any solution
What if my data is in database tables, how do i train the model using that?
Sir, can we implement this in VS code without using ineuron.
Sir can we implement this on windows, Because there is no availability of terminal on windows.
Window ko kholo fir andar aa payega na...😂
AttributeError: init is no longer a top-level attribute of the pinecone package.
...
region='us-west-2'
)
)
replyy anyone
try using this
from pinecone import Pinecone as PineconeClient
from langchain_community.vectorstores import Pinecone as PineconeLang
pc = PineconeClient(api_key=PINECONE_API_KEY)
docsearch = PineconeLang.from_texts([t.page_content for t in text_chunks],embedding=embeddings, index_name = INDEX_NAME)
Pinecone has no attribute 'from_texts' errors is occuring when using Langchain due to a namespace collision. The Python classes for both Langchain and Pinecone have objects named Pinecone.
With the pinecone-client v3 there have been some modifications. Instead of using "from langchain.vectorstores import Pinecone" you need to use "from langchain_pinecone import PineconeVectorStore". Make sure that the pinecone-client you install is v3.x.
For no errors make sure to set PINECONE_API_KEY as an environment variable. os.environ['PINECONE_API_KEY'] = '....'
then you can use
index_name = 'your_index_name'
docsearch = PineconeVectorStore.from_documents(
text_chunks,
embeddings,
index_name = index_name
)
i also got the same error have you resoleved it
@@sayed5603
from langchain_pinecone import PineconeVectorStore
pc = pinecone.Pinecone(api_key= os.environ['PINECONE_API_KEY'] , environment= PINECONE_API_ENV)
index_name = "medical-chatbot"
index = pc.Index(index_name)
docs_chunks =[t.page_content for t in text_chunks]
docsearch = PineconeVectorStore.from_texts(docs_chunks ,embeddings, index_name=index_name)
this might work @@sayed5603
any solution for this error ??
qa=RetrievalQA.from_chain_type(
llm=llm,
chain_type="stuff",
retriever=docsearch.as_retriever(search_kwargs={'k': 2}),
return_source_documents=True,
chain_type_kwargs=chain_type_kwargs)
ValidationError: 1 validation error for RetrievalQA
retriever
Can't instantiate abstract class BaseRetriever without an implementation for abstract methods '_aget_relevant_documents', '_get_relevant_documents' (type=type_error)
Same error. @iNeuron Intelligence, please help
please share the solution
i am getting error in this code
qa=RetrievalQA.from_chain_type(
llm=llm,
chain_type="stuff",
retriever=index.as_retriever(search_kwargs={'k': 2}),
return_source_documents=True,
chain_type_kwargs=chain_type_kwargs)
if anyone knows , how to resolve ,please help
anyone able to get the solution ?
please share the solution
what r the pre-requisites for this vedio.....should i refer any other video before starting this one
Great thanks!! If I can know If I follow the video and apply the practical step by step with you, will I get a complete project in the end or are there some things that are not explained in the video , because I find it difficult to create projects and to develop this skill I decided to start by imitating some of the projects explained at the beginning so that I can later create the projects myself
I am asking this question because I was trying to implement projects from other channels, but in the end I was surprised that there were parts of the project that were not explained or that the project was incomplete and only some of its parts were implemented. I hope you answer thank you
@@NetF-yz5el want to know too
Data set...??
facing issue while initializing pinecone, error is init is no more available or removed from latest update, please help me with latest update 1:36:46
have you found any solutiion
%pip install -U langchain-pinecone do this it will work
@@prateeksharma2354 not working
Just check the langchain pinecone documentation and just copy paste the code. Also create a .env file in your project root directory with the PINECONE_API_KEY storing the api key string. And don't forget to restart the kernel after creating the .env file
@@shobhitsharma8337 can u please share the code
from where he took dimension
??? anyone please help
Thank you so much😊
Is it possible for me to build this project with 0 knowledge in all the technologies used in the video...i mean can learn in the process?
Hey, You can make projects by following videos. But you will need to study up and read the documentation to actually understand what is going on and what the code does
@@mihirkapile6925 can you give us the prerequisites for this project?!
@@yahyaahmed8875 This video explains the stuff very well, its good for beginners. But I do recommend learning more about langchain and vector databases a bit before doing this project.
There is this course on Udemy for Langchain by Eden Marco. I really recommend to do that .
does anyone have the full project, if so please contact me!
Hi can anbody help? I am getting ModuleNotFound Error for langchain
I encountered the same issue, so I used Jupyter Notebook instead of VSCode Notebook.
create the environment correctly , it'll work .i too faced the same issue
from_texts is no longer available. any solution?
You can use some other vector database
Pinecone has no attribute 'from_texts' errors is occuring when using Langchain due to a namespace collision. The Python classes for both Langchain and Pinecone have objects named Pinecone.
With the pinecone-client v3 there have been some modifications. Instead of using "from langchain.vectorstores import Pinecone" you need to use "from langchain_pinecone import PineconeVectorStore". Make sure that the pinecone-client you install is v3.x.
For no errors make sure to set PINECONE_API_KEY as an environment variable. os.environ['PINECONE_API_KEY'] = '....'
then you can use
index_name = 'your_index_name'
docsearch = PineconeVectorStore.from_documents(
text_chunks,
embeddings,
index_name = index_name
)
thanks for the help@@nemilpanchamia1758
thanks for the help @@nemilpanchamia1758
@@nemilpanchamia1758 Thank You for your response. Wasted a lot of time searching on the web. It really worked!!!
i want written notes for this plz
This is so good, thanks so much
After creating indexes environment doesn't showsup
yes same thing i faced and then i come to know that they are stop providing it free
@@mohammadriyaz5586 how did you procced further without environment
only serverless pinecone is available how do i use that?
ha bhai
tumne kya kiya plz batao cv me dalna hai ye project or we shall work together
@@funnybonner2113 aur mene 4 pdfs se vector database banaya h to merko 120 mins lage databse bana ne mei to most prob utna time lagega agar ek pdf use krni hai to baaki pdfs hata lena
So how did u guys move ahead?
@@arpanthakur6200 used different tools for the same tasks
Is you used open api key in this ?? 13:46
@@dipendrapratap6495 very very thanks brother for your comment....I need your help in that......
Kya transformer pre trained used kar Rahe hai hugging face sa ya hud apna train kia hai .....??
@@acsport5728 pretrained
very nice.
does anyone experience this error? need help on it
qa=RetrievalQA.from_chain_type(
llm=llm,
chain_type="stuff",
retriever=docsearch.as_retriever(search_kwargs={'k': 2}),
return_source_documents=True,
chain_type_kwargs=chain_type_kwargs)
ValidationError: 1 validation error for RetrievalQA
retriever
Can't instantiate abstract class BaseRetriever without an implementation for abstract methods '_aget_relevant_documents', '_get_relevant_documents' (type=type_error)
I am facing the same error. Found no fixes so far even after spending a lot of time 🥲
I am also facing the same, no solution as of now
did anyone got any solution ?
Anyone got solution ?
im also facing same problem have you got the solution
Where can we find the code for it?
docsearch=Pinecone.from_texts([t.page_content for t in text_chunks], embeddings, index_name=index_name) i am getting here error as pinecone is not defined
from langchain_pinecone import PineconeVectorStore
pc = pinecone.Pinecone(api_key= os.environ['PINECONE_API_KEY'] , environment= PINECONE_API_ENV)
index_name = "medical-chatbot"
index = pc.Index(index_name)
docs_chunks =[t.page_content for t in text_chunks]
docsearch = PineconeVectorStore.from_texts(docs_chunks ,embeddings, index_name=index_name)
this might work
@@shrutibisht2977 hey by doing this your code runs?
@@shrutibisht2977 thanks, still there is issue while importing: from langchain_pinecone.vectorstores import PineconeVectorStore, if possible please help
doesnt work
I have the same issue@@akshatgandhi7958