Closed AtmehEsraa closed 3 months ago
To link ChromaDB to the vector store and ensure it works correctly, follow these steps:
Configuration Settings: Ensure that the configuration settings for ChromaDB are correctly set. This includes the collection name, persist directory, and any server settings if applicable.
ChromaComponent Setup:
Verify that the ChromaComponent
is properly configured. Here is an example configuration:
from langchain_community.vectorstores.chroma import Chroma
from langflow.interface.custom.custom_component import CustomComponent
class ChromaComponent(CustomComponent):
display_name: str = "Chroma"
description: str = "Implementation of Vector Store using Chroma"
def build_config(self):
return {
"collection_name": {"display_name": "Collection Name", "value": "UAE_Schools"},
"index_directory": {"display_name": "Persist Directory", "value": "test"},
"embedding": {"display_name": "Embedding"},
"chroma_server_host": {"display_name": "Server Host", "advanced": True},
"chroma_server_port": {"display_name": "Server Port", "advanced": True},
"chroma_server_ssl_enabled": {"display_name": "Server SSL Enabled", "advanced": True},
}
def build(self, collection_name, embedding, index_directory, chroma_server_host=None, chroma_server_port=None, chroma_server_ssl_enabled=False):
chroma_settings = None
if chroma_server_host:
chroma_settings = chromadb.config.Settings(
chroma_server_host=chroma_server_host,
chroma_server_port=chroma_server_port,
chroma_server_ssl_enabled=chroma_server_ssl_enabled,
)
return Chroma(
collection_name=collection_name,
persist_directory=index_directory,
embedding=embedding,
client_settings=chroma_settings,
)
VectorStore Retriever Configuration:
Ensure that the VectorStore Retriever
is correctly set up to use the Chroma vector store. Here is an example:
from langchain_core.vectorstores import VectorStoreRetriever
class VectorStoreRetrieverComponent(CustomComponent):
display_name = "VectorStore Retriever"
description = "A vector store retriever"
def build_config(self):
return {
"vectorstore": {"display_name": "Vector Store", "type": VectorStore},
}
def build(self, vectorstore):
return vectorstore.as_retriever()
Check Connections:
Verify that all components are correctly interconnected in your workflow. Ensure that the VectorStore Retriever
is linked to the ChromaComponent
and that the RetrieverTool
is correctly configured to use the retriever.
Troubleshooting:
By following these steps and ensuring all configurations are correctly set, you should be able to link ChromaDB to the vector store successfully [1][2].
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@hakeemsyd the VectorStore Retriever is outdated, thanks for sharing this. I'll let the team know about this and make an update soon.
@AtmehEsraa I believe there's a misunderstanding about the retriever. One of the outputs is the retriever itself, and the other is the search result. Therefore, you don't need a separate vectorStore Retriever, as the retriever is already included as one of the outputs.
I try to link chroma DB, to the vector store and it doesnt work, could you help me in that