Building a Document-based Question Answering System with LangChain, Pinecone, and LLMs like GPT-4.

Learn how to build a powerful document-based question-answering system using LangChain, Pinecone, and advanced LLMs like GPT-4 and ChatGPT. Unlock the potential of semantic search and AI-driven insights to create precise and context-aware AI applications. Watch now and elevate your projects with cutting-edge techniques!

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🚀 Top Rated Plus Data Science Freelancer with 8+ years of experience, specializing in NLP and Back-End Development. Founder of FutureSmart AI, helping clients build custom AI NLP applications using cutting-edge models and techniques. Former Lead Data Scientist at Oracle, primarily working on NLP and MLOps.

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#LangChain #Pinecone #GPT4 #ChatGPT #SemanticSearch #DocumentQnA"

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[entertainmentbuzz]

Very useful information in the video.
Thanks.!

[LaveshNK]

Just an update, unstructured 0.6.1 does not support local-inference. For the import statements you have to add *!pip install as well to load your documents.

Thanks for the content!

[FindMultiBagger]

Crisp and up to the point !!! Great work
need more tutorials on LLM

[kevon]

This was a very illuminating demo. Appreciate it!

[SaiKiranAdusumilli]

Fastest research on complete langchain and you provided the best notes ❤🎉

[extrememike]

Good explanations. The flow diagrams really helps with he big picture. Thanks!

[port]

It was a very helpful presentation. Thanks and greetings from Poland.

[rotormeeeeeeee]

This is first-class information.
Thank you.
I just subscribed!

[Yogic-ignition]

for everyone getting error on:
embeddings =
text= "Hello world"
query_result = embeddings.embed_query(text)
len(query_result)

can go ahead and use:
response = openai.Embedding.create(
input="Hello world",

)
embeddings =
len(embeddings)

[rishikapandit]

Sir in the code it is giving an error saying that pinecone does not have an attribute named ‘init’ how do we resolve this ?

[thomasguillemard]

Clear explanations and great code! Thanks!

[mohsinaliriad]

Looking for something similar and found the best one. Thanks @Pradip

[quengelbeard]

Hey Pradip, great video!
Do you know if it's possible to automatically create a pinecone db index from code?
So that you don't have to create them manually

[snehitvaddi]

Hello! I’m working on creating an idiom dataset to fine-tune LLaMa2 for suggesting idioms based on different scenarios. I have a PDF full of idioms and I’m wondering if there’s a way to extract all the idioms using GPT or any other Large Language Model. Is there a cost-effective or free method to generate this dataset? Also, could you advise on how the data should be structured for fine-tuning the LLM? Should it be similar to a QnA format or something else?

[ShadowDC]

wouldve been helpful to have the docs included with the colab files to run some tests straight away

[ujjwalsrivastava]

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

[axysharma]

How to show the document path alongwith get_answer(query) call without using print similar_docs?

[saadkhattak]

Hi Pradip, Hope you are doing well :)
I installed all the dependencies and was running the following cell,

directory = '/content/data'

def load_docs(directory):
loader = DirectoryLoader(directory)
documents = loader.load()
return documents

documents = load_docs(directory)
len(documents)



I got this error: ImportError: cannot import name 'is_directory' from 'PIL._util'

Any idea how to resolve this? I have faced this error before as well.

[patrickhilpold]

Has someone turned this into a streamlit app and would share the github? Would really appreciate that!