WIP on threadpool impl of query_namespaces

pinecone/core/openapi/shared/api_client.py

@@ -8,6 +8,24 @@
 import typing
 from urllib.parse import quote
 from urllib3.fields import RequestField
+import time
+import random
+
+def retry_api_call(
+    func, args=(), kwargs={}, retries=3, backoff=1, jitter=0.5
+):
+    attempts = 0
+    while attempts < retries:
+        try:
+            return func(*args, **kwargs)  # Attempt to call __call_api
+        except Exception as e:
+            attempts += 1
+            if attempts >= retries:
+                print(f"API call failed after {attempts} attempts: {e}")
+                raise  # Re-raise exception if retries are exhausted
+            sleep_time = backoff * (2 ** (attempts - 1)) + random.uniform(0, jitter)
+            # print(f"Retrying ({attempts}/{retries}) in {sleep_time:.2f} seconds after error: {e}")
+            time.sleep(sleep_time)
 
 
 from pinecone.core.openapi.shared import rest
@@ -397,25 +415,32 @@ def call_api(
             )
 
         return self.pool.apply_async(
-            self.__call_api,
-            (
-                resource_path,
-                method,
-                path_params,
-                query_params,
-                header_params,
-                body,
-                post_params,
-                files,
-                response_type,
-                auth_settings,
-                _return_http_data_only,
-                collection_formats,
-                _preload_content,
-                _request_timeout,
-                _host,
-                _check_type,
-            ),
+            retry_api_call,
+            args=(
+                self.__call_api,  # Pass the API call function as the first argument
+                (
+                    resource_path,
+                    method,
+                    path_params,
+                    query_params,
+                    header_params,
+                    body,
+                    post_params,
+                    files,
+                    response_type,
+                    auth_settings,
+                    _return_http_data_only,
+                    collection_formats,
+                    _preload_content,
+                    _request_timeout,
+                    _host,
+                    _check_type,
+                ),
+                {},  # empty kwargs dictionary
+                3,    # retries
+                1,    # backoff time
+                0.5   # jitter
+            )
         )
 
     def request(

pinecone/data/index.py

@@ -27,6 +27,8 @@
 from pinecone.core.openapi.data.api.data_plane_api import DataPlaneApi
 from ..utils import setup_openapi_client, parse_non_empty_args
 from .vector_factory import VectorFactory
+from .query_results_aggregator import QueryResultsAggregator, QueryNamespacesResults
+from multiprocessing.pool import ApplyResult
 
 __all__ = [
     "Index",
@@ -361,7 +363,7 @@ def query(
             Union[SparseValues, Dict[str, Union[List[float], List[int]]]]
         ] = None,
         **kwargs,
-    ) -> QueryResponse:
+    ) -> Union[QueryResponse, ApplyResult]:
         """
         The Query operation searches a namespace, using a query vector.
         It retrieves the ids of the most similar items in a namespace, along with their similarity scores.
@@ -403,6 +405,39 @@ def query(
                  and namespace name.
         """
 
+        response = self._query(
+            *args,
+            top_k=top_k,
+            vector=vector,
+            id=id,
+            namespace=namespace,
+            filter=filter,
+            include_values=include_values,
+            include_metadata=include_metadata,
+            sparse_vector=sparse_vector,
+            **kwargs,
+        )
+
+        if kwargs.get("async_req", False):
+            return response
+        else:
+            return parse_query_response(response)
+
+    def _query(
+        self,
+        *args,
+        top_k: int,
+        vector: Optional[List[float]] = None,
+        id: Optional[str] = None,
+        namespace: Optional[str] = None,
+        filter: Optional[Dict[str, Union[str, float, int, bool, List, dict]]] = None,
+        include_values: Optional[bool] = None,
+        include_metadata: Optional[bool] = None,
+        sparse_vector: Optional[
+            Union[SparseValues, Dict[str, Union[List[float], List[int]]]]
+        ] = None,
+        **kwargs,
+    ) -> QueryResponse:
         if len(args) > 0:
             raise ValueError(
                 "The argument order for `query()` has changed; please use keyword arguments instead of positional arguments. Example: index.query(vector=[0.1, 0.2, 0.3], top_k=10, namespace='my_namespace')"
@@ -435,7 +470,58 @@ def query(
             ),
             **{k: v for k, v in kwargs.items() if k in _OPENAPI_ENDPOINT_PARAMS},
         )
-        return parse_query_response(response)
+        return response
+
+    @validate_and_convert_errors
+    def query_namespaces(
+        self,
+        vector: List[float],
+        namespaces: List[str],
+        top_k: Optional[int] = None,
+        filter: Optional[Dict[str, Union[str, float, int, bool, List, dict]]] = None,
+        include_values: Optional[bool] = None,
+        include_metadata: Optional[bool] = None,
+        sparse_vector: Optional[
+            Union[SparseValues, Dict[str, Union[List[float], List[int]]]]
+        ] = None,
+        **kwargs,
+    ) -> QueryNamespacesResults:
+        if len(namespaces) == 0:
+            raise ValueError("At least one namespace must be specified")
+        if len(vector) == 0:
+            raise ValueError("Query vector must not be empty")
+
+        # The caller may only want the top_k=1 result across all queries,
+        # but we need to get at least 2 results from each query in order to
+        # aggregate them correctly. So we'll temporarily set topK to 2 for the
+        # subqueries, and then we'll take the topK=1 results from the aggregated
+        # results.
+        overall_topk = top_k if top_k is not None else 10
+        aggregator = QueryResultsAggregator(top_k=overall_topk)
+        subquery_topk = overall_topk if overall_topk > 2 else 2
+
+        target_namespaces = set(namespaces)  # dedup namespaces
+        async_results = [
+            self.query(
+                vector=vector,
+                namespace=ns,
+                top_k=subquery_topk,
+                filter=filter,
+                include_values=include_values,
+                include_metadata=include_metadata,
+                sparse_vector=sparse_vector,
+                async_req=True,
+                **kwargs,
+            )
+            for ns in target_namespaces
+        ]
+
+        for result in async_results:
+            response = result.get()
+            aggregator.add_results(response)
+
+        final_results = aggregator.get_results()
+        return final_results
 
     @validate_and_convert_errors
     def update(

pinecone/grpc/index_grpc_asyncio.py

@@ -42,7 +42,7 @@
     parse_sparse_values_arg,
 )
 from .vector_factory_grpc import VectorFactoryGRPC
-from .query_results_aggregator import QueryResultsAggregator, QueryNamespacesResults
+from ..data.query_results_aggregator import QueryResultsAggregator, QueryNamespacesResults
 
 
 class GRPCIndexAsyncio(GRPCIndexBase):

tests/unit_grpc/test_query_results_aggregator.py → tests/unit/test_query_results_aggregator.py

@@ -1,4 +1,4 @@
-from pinecone.grpc.query_results_aggregator import (
+from pinecone.data.query_results_aggregator import (
     QueryResultsAggregator,
     QueryResultsAggregatorInvalidTopKError,
     QueryResultsAggregregatorNotEnoughResultsError,