It would be lovely to see a speech recognition and generation model added to this workflow, and entities and relationships extracted from the conversations between the users and the digital agents, and these entities and relationships merged into a graph representation. If users could select parts of the conversations that they want to merge into a shared graph representation for public discussion, and knowledge and sentiment extracted from millions of simultaneous conversations with people around the world could be merged, we could create a collective human and digital intelligence.
thanks for your suggestion, I'll try.. Thanks for your support. Pleases consider sharing it in your communities who might benefit. Your support is greatly appreciated :)
have a question, i would like advice to learn the right way because everyday in AI releases a new thing and i feel like im stuck, because im not so good to implement papers or x project(dont know web or work with vs only colab) but im aware that is a problem to be creative building your own projects, i ve binged a lot of tutorials and then when you get in the loop of failing a lot of times , you dont learn at the implementation side to upload to eg GitHub...so its complicated,i wanted to ask you some advice or if you could teach me better because its years around and im stuck ,thanks 🙏@@SridharKumarKannam
First of all, Thanks for the wonderful explanation. But I have a doubt, The LLMGraphTransformer converts text documents into structured graph documents using LLM . (llm_transformer.convert_to_graph_documents(documents)). Similarly Is there any predefined methods to create graph schema for csv data so that we don't need to write the cypher query for it.
as far as I know, there isn't any. Creating entities and relationships from text is conceptually easy, but for a tabular data, you have to define what are entities, their properties and relationships, through cypher...
Is there any way through which we can summarize the graph from our neo4j as we are unable to query it. As it is not working by changing the query ,asking for summarization
One way to summarise a graph is, first extract all the node/relations data from graph in a table or json format and then provide that info as context llm for summarisation...
Hi, Great video thanks !! Do you think the graph.refresh_schema() (13:22 in your video) works still if the Neo4J DB hasn't been created by the same code ? thanks again for really rich informations here
If you found this content useful, pleases consider sharing it with others who might benefit. Your support is greatly appreciated :)
It would be lovely to see a speech recognition and generation model added to this workflow, and entities and relationships extracted from the conversations between the users and the digital agents, and these entities and relationships merged into a graph representation.
If users could select parts of the conversations that they want to merge into a shared graph representation for public discussion, and knowledge and sentiment extracted from millions of simultaneous conversations with people around the world could be merged, we could create a collective human and digital intelligence.
thats a great idea and also require a team effort. I'll see what I can do. Thanks a lot for your comment and support.
@@SridharKumarKannamAgreed, it requires a team effort. A demonstration of the concept might be a tool to help build a team.
Thanks for all the hard work and take your time to explain all the details. It helps us to understand 😊
Thank you very much for your support :)
Sridhar, very crisp and clear explanation. Thanks a lot !!
Thank you very much :)
A video on Product recommendation system where there are user and products data in Neo4j and where user can get related products while querying
thanks for your suggestion, I'll try..
Thanks for your support. Pleases consider sharing it in your communities who might benefit. Your support is greatly appreciated :)
Amazing work, thank you so much!
Thanks for your support. Pleases consider sharing it in your communities who might benefit. Your support is greatly appreciated :)
Love your videos!!!! Thanks for the knowledge sharing!
Thanks for your support :)
Just in time, I'm waiting for more updates about graph and llm based technologies related videos. Thank you.
thank you, sure, I'll do more videos as I get time...
Great explanation. Thanks!
Thanks for your support :)
wow this is something really interesting finally what i wanted!!! thank you very much 🙏
Thanks for your support :)
have a question, i would like advice to learn the right way because everyday in AI releases a new thing and i feel like im stuck, because im not so good to implement papers or x project(dont know web or work with vs only colab) but im aware that is a problem to be creative building your own projects, i ve binged a lot of tutorials and then when you get in the loop of failing a lot of times , you dont learn at the implementation side to upload to eg GitHub...so its complicated,i wanted to ask you some advice or if you could teach me better because its years around and im stuck ,thanks 🙏@@SridharKumarKannam
awesome tutorial please make a tutorial on not only keywords as nodes but also a summary of the text of the node/topics.
thank you, sure, I'll try
First of all, Thanks for the wonderful explanation. But I have a doubt,
The LLMGraphTransformer converts text documents into structured graph documents using LLM . (llm_transformer.convert_to_graph_documents(documents)).
Similarly Is there any predefined methods to create graph schema for csv data so that we don't need to write the cypher query for it.
as far as I know, there isn't any. Creating entities and relationships from text is conceptually easy, but for a tabular data, you have to define what are entities, their properties and relationships, through cypher...
Is there any way through which we can summarize the graph from our neo4j as we are unable to query it. As it is not working by changing the query ,asking for summarization
One way to summarise a graph is, first extract all the node/relations data from graph in a table or json format and then provide that info as context llm for summarisation...
Hi, Great video thanks !! Do you think the graph.refresh_schema() (13:22 in your video) works still if the Neo4J DB hasn't been created by the same code ? thanks again for really rich informations here
Thanks for your support. I think it should work fine. Pls let me know if it doesn't...
I tried this code... but my connection with neo4j refused..auth error.. while usename and password are correct..? Any solution
Are you still facing the issue? The DB must be in Active mode. Open Neo4j Desktop and click on the "start" button of the DB
Hi sir, can you please tell how we can use this with llama 2 as the llm model?
Use Ollama to run llama2 locally and then use langchain to connect... python.langchain.com/v0.1/docs/integrations/llms/ollama/
hey , make a video on 1 , 2 bit quantization
Sure, I'll try...
Touch on open devin
sure, I'll try...