Open teis-e opened 8 months ago
🤖
Hey @teis-e! Great to see you back. Diving into another challenge, I see? Let's get to the bottom of this.
Based on the context provided, it seems like the issue you're experiencing with LlamaIndex v0.9.44 returning an empty response when using multiple MetadataFilters with a condition set in a VectorStoreIndex query on Qdrant could be due to the way the filters are being processed in the _build_query_filter
method.
In the current implementation, the _build_query_filter
method is responsible for building the filter conditions for the query. It iterates over the filters provided in the query.filters.filters
and adds a FieldCondition
for each filter to the must_conditions
list. However, it does not handle the case where multiple conditions are set for the same field. If multiple conditions are set for the same field, only the last condition will be used, and the previous conditions will be overwritten. This could result in an empty response if the overwritten conditions were necessary to return the desired results.
Here is the relevant code:
if query.filters is None:
return Filter(must=must_conditions)
for subfilter in query.filters.filters:
# only for exact match
if not subfilter.operator or subfilter.operator == "==":
if isinstance(subfilter.value, float):
must_conditions.append(
FieldCondition(
key=subfilter.key,
range=Range(
gte=subfilter.value,
lte=subfilter.value,
),
)
)
else:
must_conditions.append(
FieldCondition(
key=subfilter.key,
match=MatchValue(value=subfilter.value),
)
)
# ... other conditions ...
return Filter(must=must_conditions)
To fix this issue, you would need to modify the _build_query_filter
method to handle multiple conditions for the same field. This could involve grouping the conditions by field and then combining the conditions for each field into a single FieldCondition
. However, the exact solution would depend on the specific requirements of your application and the capabilities of the Qdrant API.
You can find the relevant code in the llama_index/vector_stores/qdrant.py file.
As for the MetadataFilters
class, it is used to handle a collection of filters for metadata. It takes a list of filter objects (which can be of type MetadataFilter
or ExactMatchFilter
) as input and provides a method legacy_filters()
to convert these filters into a legacy format. You can find more details about this in the tests/vector_stores/test_metadata_filters.py file.
I hope this helps! If you have any more questions or need further clarification, feel free to ask.
@dosu-bot what do you mean with 'it does not handle the case where multiple conditions are set for the same field'. if i am not mistaking I'm trying to filter on 2 different fields 'color' and 'alpha'
🤖
Based on the provided context, it seems that the MetadataFilters
class in LlamaIndex handles multiple filters by accepting a list of filter objects in its constructor. These filters are then used in the legacy_filters
method, which converts the list of filters into a legacy format. However, if any of the filters have an operator other than the default (None
), a ValueError
is raised. This suggests that the legacy format does not support operators.
Regarding the FilterCondition
parameter, the context does not provide direct information about how MetadataFilters
handles it. However, it does show how filters are handled in the query
method of the DocArrayVectorStore
class. If query.filters
is not empty, the method creates a filter_query
dictionary where each key is a concatenation of "metadata__" and the filter key, and each value is a dictionary with "$eq" as the key and the filter value as the value. This dictionary is then used in the .filter(filter_query=filter_query)
method to filter the results of the query.
In your case, you're using FilterCondition.OR
with two different fields 'color' and 'alpha'. It's possible that the issue lies in how the FilterCondition.OR
is being processed. Without more information about the MetadataFilters
class and the legacy_filters
method, it's hard to provide a more detailed explanation.
As for the comment about 'it does not handle the case where multiple conditions are set for the same field', it seems to refer to a situation where you would have multiple filters for the same field, like this:
filters=[
MetadataFilter(
key="color",
value="red",
),
MetadataFilter(
key="color",
value="blue",
),
],
In this case, it's unclear how the MetadataFilters
class would handle this situation, as the provided context does not cover this scenario.
I hope this helps clarify the situation. If you have more information or if there's something else you'd like to know, please let me know. You can also check the source code for the MetadataFilters
class and the legacy_filters
method for more details:
For more detailed help, you might want to consider upgrading to the latest version of LlamaIndex (v0.9.46) if possible, as there may have been fixes or improvements related to this issue.
@dosu-bot
Is there another way to get nodes and do the a query on it. Like to match these keys separately and merge those nodes
🤖
Based on the context provided, it seems like you're trying to use multiple MetadataFilters
with a FilterCondition.OR
condition. This should return nodes that match any of the filters, not all of them. However, you mentioned that you're getting an empty response.
The code you've provided seems correct, but I suspect the issue might be with the data you're querying. If there are no nodes that match either the "color" filter or the "alpha" filter, the query would indeed return an empty response.
Here's a modified version of your code that should work as expected:
from llama_index.vector_stores.types import (
FilterOperator,
FilterCondition,
)
filters = MetadataFilters(
filters=[
MetadataFilter(key="color", value="red"),
MetadataFilter(key="alpha", value="1"),
],
condition=FilterCondition.OR, # Change AND to OR
)
query_engine = index.as_query_engine(filters=filters)
In this code, the FilterCondition.OR
condition is used, meaning that the query will return nodes that match either the "color" filter or the "alpha" filter, not necessarily both.
If you're still getting an empty response, I would recommend checking the data you're querying to ensure there are nodes that match either of the filters. You can do this by running separate queries for each filter and checking if they return any results.
For more information on how to use MetadataFilters
with multiple filters and a FilterCondition.OR
condition, you can refer to the Qdrant metadata filter example in the LlamaIndex documentation.
If you're still having issues after trying these steps, please provide more information about the data you're querying and I'll be happy to help further.
Is this fixed in the latest 0.10.1 ?
having the same issue
i am having a similar issue where i can add multiple value for the same key.
@dosubot I get a similar issue and I try to follow in website. it is not still filters anything.
Ref: https://docs.llamaindex.ai/en/stable/examples/vector_stores/RedisIndexDemo/?h=exactmatchfilter https://docs.llamaindex.ai/en/stable/examples/vector_stores/postgres/?h=metadatafilter
encountered same issue :)
facing same issue
This really depends on the vector store being used, it will be different for each one
same issue
any update from the team? seeing the same issue both with llama-index syntax and with the vector_store_kwargs
native qdrant client syntax
Somehow got it working after upgrading the qdrant image (v1.11.0) and llama-index (v0.11.1)
docker pull qdrant/qdrant:v1.11.0
pip install llama-index-core>0.11.1 llama-index-vector-stores-qdrant>0.3.0 --upgrade
Example usage:
# Define your filter:
doc_list=['doc1','doc2','doc3']
from llama_index.core.vector_stores import (
MetadataFilter,
MetadataFilters,
FilterOperator,
)
# Define your filter(s)
from llama_index.core.vector_stores import FilterOperator, FilterCondition
filters = MetadataFilters(
filters=[
MetadataFilter(key="metadata_key_name", value=doc, operator=FilterOperator.EQ) for doc in doc_list
],
condition=FilterCondition.OR,
)
retriever_filtered = index.as_retriever(filters=filters, similarity_top_k=5)
# Test your retriever with filter
result=retriever_filtered.retrieve("Testing Filter")
set([res.metadata['metadata_key_name'] for res in result])
Bug Description
Only when i use either of the filters it gives a index. When i do buth it returns:
Empty response
Version
0.9.44
Steps to Reproduce
Make a vectore store index and query it
Im using Qdrant.
Relevant Logs/Tracbacks
No response