-
Can you point me to the right documentation for how I can spin this up or access the service? Is there a docker image I can pull?
-
The vector database should be created with sample navigation specific data.
-
## Why RAG
Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of LLMs by incorporating a retrieval mechanism into the generative process. This approach allows the model…
-
### Documentation Issue Description
This markdown table in `Multi Modal Vector Stores` section isn't rendered properly:
### Documentation Link
https://docs.llamaindex.ai/en/latest/module_guid…
-
### The Feature
Litellm currently supports only Redis for semantic caching. It would be advantageous if it also supported semantic caching with other popular vector databases such as Qdrant.
### Mot…
-
When running private GPT using Ollama profile and set up for QDrant cloud, it cannot resolve the cloud REST address.
settings.yaml
vectorstore:
database: qdrant
nodestore:
database: pos…
-
### System Name
Qdrant
### Type
Materialize
### Details
https://qdrant.tech/
-
### Is there an existing issue for this?
- [X] I have searched the existing issues
### Is your feature request related to a problem? Please describe.
I have the following setup:
Milvus 2.3.7, pym…
-
it will considerably speed up future work to be able to make and export phonetic n-gram indices that can be later used for querying, in the same way that you can do `makeblastdb` and then later query …
-
### Describe the issue
**Issue Overview:**
In [this GitHub issue](https://github.com/microsoft/autogen/issues/253), the proposal for implementing QdrantRetrieveUserProxyAgent has been successfully…