Where to write the custom query ? for prefiltering

[shanumas]

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Example Code

# Generate a prompt and parse output
prompt = get_query_constructor_prompt(document_content_description, metadata_field_info)
output_parser = StructuredQueryOutputParser.from_components()
query_constructor = prompt | llm | output_parser

# Invoke the query constructor with a sample query
query_constructor.invoke({
 "query": "Songs by Taylor Swift or Katy Perry about teenage romance under 3 minutes long in the dance pop genre"
})

Description

My self query extractor is working fine. But I just want llm to extract the metadata. I want to write my custom query. I want to decide whether it should the metadata coparison should be "gte" or "lte" . How can I do it here ?

System Info

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Hey @shanumas! 👋 I'm here to help you with any questions or issues you have. I'm a bot that can assist with bug fixes, answering questions, and getting you ready to contribute. Let me know how I can assist you!

You should write the custom query for prefiltering in the similarity_search method call. Here is an example of how to include a filter in your query:

# Perform a similarity search with a filter
query = "What did the president say about Ketanji Brown Jackson"
filter = {"field_name": {"$gte": value}}  # Replace with your actual filter criteria
docs = vectorstore.similarity_search(query, filter=filter)

print(docs[0].page_content)

This code snippet shows how to add a filter to the similarity_search method to prefilter the documents based on your criteria. The filter parameter supports various operators such as $eq, $ne, $lt, $lte, $gt, $gte, $in, $nin, $between, $like, $ilike, $and, and $or for more complex filtering logic ^[1][2].

To integrate custom metadata extraction and comparison logic into the invoke method of the query constructor, you can modify the visit_comparison method in the QdrantTranslator class. This method is responsible for handling comparisons and can be customized to include your specific metadata extraction and comparison logic.

Here is an example of how you can modify the visit_comparison method to include custom metadata extraction and comparison logic:

from qdrant_client.http import models as rest

class QdrantTranslator(Visitor):
    def __init__(self, metadata_key: str):
        self.metadata_key = metadata_key

    def visit_comparison(self, comparison: Comparison) -> rest.FieldCondition:
        self._validate_func(comparison.comparator)
        attribute = self.metadata_key + "." + comparison.attribute

        # Custom metadata extraction logic
        if isinstance(comparison.value, dict) and 'custom_metadata' in comparison.value:
            custom_metadata = comparison.value['custom_metadata']
            # Apply custom logic to extract metadata
            comparison.value = self.extract_custom_metadata(custom_metadata)

        if comparison.comparator == Comparator.EQ:
            return rest.FieldCondition(
                key=attribute, match=rest.MatchValue(value=comparison.value)
            )
        if comparison.comparator == Comparator.LIKE:
            return rest.FieldCondition(
                key=attribute, match=rest.MatchText(text=comparison.value)
            )
        kwargs = {comparison.comparator.value: comparison.value}
        return rest.FieldCondition(key=attribute, range=rest.Range(**kwargs))

    def extract_custom_metadata(self, custom_metadata: dict) -> Any:
        # Implement your custom metadata extraction logic here
        # For example, you can extract specific fields or transform the metadata
        return custom_metadata.get('specific_field', 'default_value')

Additionally, you can refer to the ElasticsearchTranslator class in the elasticsearch.py file from the LangChain repository for more advanced examples of how to handle different comparison scenarios and integrate custom logic ^[3][4][5][6].

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