Closed theainerd closed 2 years ago
You can!
The nearText function does a semantic search without the Q&A module.
For example:
{
Get {
Paragraph(
nearText: {
concepts: ["Italian food"]
}
limit: 50
) {
content
order
title
inArticle {
... on Article {
title
}
}
}
}
}
If you like, you can join our Slack to further discuss this.
Hello how exactly to use it using the python client, also i am trying to run on a cpu.
Hi @theainerd –
how exactly to use it using the python client
You can connect the client to a Weaviate instance as outlined here in the docs. The above query will look something like:
import weaviate
client = weaviate.Client("http://localhost:8080")
nearText = {
"concepts": ["Italian food"]
}
client.query.get("Paragraph", ["content", "order", "title", "_additional {certainty} "]).with_near_text(nearText).limit(50).do()
also i am trying to run on a CPU
This will work but slower and without the Q&A module, the docker file is here
Strange but all i get is this error when i try to run.
ConnectionResetError: [Errno 104] Connection reset by peer
Hi @theainerd – just to make sure, if you go to your browser and load: http://localhost:8080/v1/meta
you can see the instance?
I am running it on my gcp instance. I am trying to acess it : http://<ip-of-the-machine>/v1/meta
I am unable to access the instance. I am not sure what i am doing wrong.
Is there any further details i can share for further understanding of the problem.
I think it's because of the port number. Would you mind moving this conversation to our Slack? If you are on it just go to the channel #datasets
Hello i want to use this semantic search engine. I just want to retrive all documents rather performing question answering on it. How to get the data of information retrival part using python client ?