Open Halpph opened 7 months ago
We are currently understaffed on the RAG front. Would you be willing to submit a PR to fix this issue?
We've come up with a complete pull request for this issue using any general embedding function that returns a list of embeddings. We'll post our pull request in the next few hours.
We've come up with a complete pull request for this issue using any general embedding function that returns a list of embeddings. We'll post our pull request in the next few hours.
Is this implemented?
We'll submit the draft pull request for review.
I have also just tried to use ada-embedding by performing the vectorization of chunks outside of Autogen, using LlamaIndex. And then trying to query the populated QDrant database using the notebook example at https://github.com/microsoft/autogen/blob/main/notebook/agentchat_qdrant_RetrieveChat.ipynb
using "embedding_model": "default"
, and docs_path: None
.
However, the error message is that embedding_model
must be one of the 12 options at https://qdrant.github.io/fastembed/examples/Supported_Models/, and ada is not in it.
Describe the issue
Issue Overview: In this GitHub issue, the proposal for implementing QdrantRetrieveUserProxyAgent has been successfully executed. However, upon attempting to use the feature, it was discovered that the current implementation relies on the qdrant_client, which in turn depends on fastembedding. Consequently, only a specific set of models listed in SUPPORTED_EMBEDDING_MODELS are supported.
SUPPORTED_EMBEDDING_MODELS: Dict[str, Tuple[int, models.Distance]] = { "BAAI/bge-base-en": (768, models.Distance.COSINE), "sentence-transformers/all-MiniLM-L6-v2": (384, models.Distance.COSINE), "BAAI/bge-small-en": (384, models.Distance.COSINE), "BAAI/bge-small-en-v1.5": (384, models.Distance.COSINE), "BAAI/bge-base-en-v1.5": (768, models.Distance.COSINE), "intfloat/multilingual-e5-large": (1024, models.Distance.COSINE), }
.Enhancement Proposal: It is suggested that the support for additional models be extended beyond the current list. A reference implementation, inspired by the approach taken in Issue 253, is provided below:
This adds dependencies on litellm but I think your contribution to this enhancement would greatly benefit the community by expanding the scope of supported models and enhancing the overall utility of QdrantRetrieveUserProxyAgent.
Steps to reproduce
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Screenshots and logs
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Additional Information
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