Realtime Powerful RAG Pipeline using Neo4j(Knowledge Graph Db) and Langchain #rag

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Want a super-powered AI app? This video shows how to build one using Neo4j for data connections, keyword searches, and even special "vector searches" for super-accurate results. All with Langchain to make it easy!

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#llm #embedding #ai #rag #futureai #generativeai #genai #textgeneration #ragapp #langchain #programminglogic #python #chatbot #openai #gpt #langchain #neo4j #graphdatabase #rag

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Thanks Sunny this will definitely helpful for my Bioinformatics related project

mohammedsaif
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Start AIops projects using kubernetes CICD terraform monitoring Airflow kubeflow.

kashifsadiq
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In this you have implemented the graph search and vector search only, right? As mentioned in the beginning of video there are 3 types of searches including keyword search which is not implemented in code?

arjuns
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Thank you so much for this incredible tutorial! At the end, how would we automate the chat history pipeline without having to hard code it in? Is there a tutorial or documentation for that also?

ItzJustJohn
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Thanks sir, Super amazing content. Will share this to my colleague and friends 😮❤❤...

Just one thing, i need to ask, OpenAI doesn't give free credit now, so how do we access these things?

aryan.
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Very good video
Few Requests: Could you please use any PDFs store in neo4j as chunks. From that chunks can you make RAG

Srb
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good content...
How embedding is getting generated in this? please explain more about this.
I am not able to generate it following your steps.

sarmaamras
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hi, is that work for db schemas to get related schema based on user query ?

sairam
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How you get updated with the technologies thats coming and what do you refer for code of all new things coming in LLM

shailendralowanshi
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Your GitHub code is missing can you please share your colab notebook

taraniroshni
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Thanks. Why did you select [0:3] from documents? because I have a problem importing my whole pdf. please guide me through this.

minayazdani
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Once try this with cohere and evalution part also ... I was stucked in Evaluation .. I checked documenations also.. but i didn't find good evaluation for cohere rag model

msumanth
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this is awsome, but my grapg are getting generated and not adding to graph.the thing is what should be the data format?

rakeshkumarrout
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How we will make sure that every entity formed is correct and have correct relationships?

sandeepsasikumar
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Hello, sorry but i have an error: ClientError: {code: {message: Failed to invoke procedure Caused by: There is no such fulltext schema index: entity} . I don't understand how you solved this on video.

Nic-ku
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can I provide my custom web scrapping data to the graph instead of the wikipedia?

naqeebahmed
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I am getting error in this code piece
from langchain_openai import OpenAIEmbeddings

vector_index =
OpenAIEmbeddings(),
# embedding=OpenAIEmbeddings(),
search_type="hybrid",
node_label="Document",
text_node_properties=["text"],

)

Error :
ValueError: Index with name vector already exists.The provided embedding function and vector index dimensions do not match.
Embedding function dimension: 1536
Vector index dimension: 384

Anonymous-buch
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Can we use open source llm models I tried using llama2 it’s not working throwing an error

manyams
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Hi sunny, can you suggest any Open Source Graph database for the same?

vivekshindeVivekShinde
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What if we have CSV files, instead of taking from Wikipedia??

vinskumar