[Question]: How to add new SQLTableSchema to an existing ChromaDB embedding?

[Chakradhar448]

[Question]: How to add new SQLTableSchema to an existing ChromaDB embedding?

[dosubot]

To add a new SQLTableSchema to an existing ChromaDB embedding, you can use the add method of the ChromaVectorStore class. Here is an example based on your provided code:

from llama_index.core.objects import SQLTableSchema
from llama_index.vector_stores.chroma import ChromaVectorStore

# Assuming you have an existing ChromaVectorStore instance
vector_store = ChromaVectorStore(chroma_collection=chroma_collection)

# Define your new SQLTableSchema
new_sql_table_schema = SQLTableSchema(
    table_name="new_table",
    columns=[
        {"name": "column1", "type": "TEXT"},
        {"name": "column2", "type": "INTEGER"},
    ],
    primary_key="column1"
)

# Add the new SQLTableSchema to the existing ChromaDB embedding
vector_store.add([new_sql_table_schema])

This code snippet demonstrates how to create a new SQLTableSchema and add it to an existing ChromaDB embedding using the add method of the ChromaVectorStore class ^[1].

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[dosubot]

To update the existing embedding if there is a change in just the column of an existing SQLTableSchema, you would need to regenerate the TextNode for the updated schema and then update the embedding in the ChromaVectorStore. Here is how you can do it:

1. Regenerate the TextNode for the updated schema:

   from llama_index.core.objects import SQLTableNodeMapping, SQLTableSchema
   
   # Assuming you have an instance of SQLTableNodeMapping and an updated SQLTableSchema
   sql_table_node_mapping = SQLTableNodeMapping(sql_database)
   updated_schema = SQLTableSchema(table_name="your_table_name", context_str="new_context")
   
   # Generate the updated TextNode
   updated_node = sql_table_node_mapping.to_node(updated_schema)

2. Update the embedding in the ChromaVectorStore:

   from llama_index.vector_stores.chroma import ChromaVectorStore
   
   # Assuming you have an existing ChromaVectorStore instance
   vector_store = ChromaVectorStore(chroma_collection=chroma_collection)
   
   # Step 1: Delete the existing node
   vector_store.delete(ref_doc_id=updated_node.node_id)
   
   # Step 2: Add the updated node
   vector_store.add(nodes=[updated_node])

This approach ensures that the old embedding is removed and the new embedding is added to the collection, reflecting the updated schema changes ^[1][2].

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[Chakradhar448]

Hi thanks for the response.

But could you please help me, on what if there was change in just the column. How to update the existing embedding for that tableschema, Please