Indexing Engine

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We use Pinecone to index and search for text. The following example demonstrates how to store text as an index and then retrieve the most related match:

expr = Expression()
expr.add(Symbol('Hello World!').zip())
expr.add(Symbol('I like cookies!').zip())
res = expr.get(Symbol('hello').embedding, index_name='default_index').ast()
res['matches'][0]['metadata']['text'][0]

Here, the zip method creates a pair of strings and embedding vectors, which are then added to the index. The line with get retrieves the original source based on the vector value of hello and uses ast to cast the value to a dictionary.

You can set several optional arguments for the indexing engine. For more details, see the symai/backend/engine_pinecone.py file.