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Updated 11 months ago

hello, is there an example, where the

hello, is there an example, where the LLM can be integrated to generate the filtering on metadata values? The only example i see is where the user pass the values to the filter eg:

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from llama_index.vector_stores.types import ExactMatchFilter, MetadataFilters

filters = MetadataFilters(
    filters=[ExactMatchFilter(key="type", value="fruit")]
)

15 comments

LLogan M

What you describe is an auto retriever

LLogan M

Two ways of doing it
https://docs.llamaindex.ai/en/stable/examples/agent/openai_agent_query_cookbook.html#autoretrieval-from-a-vector-database

https://docs.llamaindex.ai/en/stable/examples/vector_stores/elasticsearch_auto_retriever.html#define-vectorindexautoretriever

SSMN

thanks! i'll give a try

SSMN

@Logan M is there a way also to support node splitting in case the text is long?

LLogan M

In case which text is long?

SSMN

the content of a TextNode that i'm idexing

SSMN

(I'm using a single TextNode for a single blog post)

SSMN

also when using the filtering technique illustrated in your first link i have some issues:

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Got output: Error: Error code: 400 - {'error': {'message': 'max_tokens is too large: 8192. This model supports at most 4096 completion tokens, whereas you provided 8192.', 'type': 'invalid_request_error', 'param': 'max_tokens', 'code': None}}

LLogan M

Should probably be chunking your data before indexing it?

SSMN

but then will be possible to re-obtain the original article?

LLogan M

If you need the full article, you can attach some link to it in the metadata (i.e. a file path, or a URL)

LLogan M

Or you can chunk the data after retrieving

SSMN

i'm looking on how to use BaseToolSpec, probably this is the best solution

SSMN

by defining under the hood an API that filter first the articles

SSMN

based on some keywrods

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