diff --git a/poetry.lock b/poetry.lock
index 4d2fe0477a52cd48d6308a469a86999a7e18ee15..db50db68f40569e06cf4b6ffcc9c295e483741b9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1059,6 +1059,140 @@ smb = ["smbprotocol"]
ssh = ["paramiko"]
tqdm = ["tqdm"]
+[[package]]
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+ {file = "grpcio_tools-1.62.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2152308e5321cb90fb45aaa84d03d6dedb19735a8779aaf36c624f97b831842d"},
+ {file = "grpcio_tools-1.62.1-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:ed1f27dc2b2262c8b8d9036276619c1bb18791311c16ccbf1f31b660f2aad7cf"},
+ {file = "grpcio_tools-1.62.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:2744947b6c5e907af21133431809ccca535a037356864e32c122efed8cb9de1f"},
+ {file = "grpcio_tools-1.62.1-cp38-cp38-win32.whl", hash = "sha256:13b20e269d14ad629ff9a2c9a2450f3dbb119d5948de63b27ffe624fa7aea85a"},
+ {file = "grpcio_tools-1.62.1-cp38-cp38-win_amd64.whl", hash = "sha256:999823758e9eacd0095863d06cd6d388be769f80c9abb65cdb11c4f2cfce3fea"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-linux_armv7l.whl", hash = "sha256:941f8a5c31986053e75fa466bcfa743c2bf1b513b7978cf1f4ab4e96a8219d27"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-macosx_10_10_universal2.whl", hash = "sha256:b9c02c88c77ef6057c6cbeea8922d7c2424aabf46bfc40ddf42a32765ba91061"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:6abd4eb3ccb444383a40156139acc3aaa73745d395139cb6bc8e2a3429e1e627"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:449503213d142f8470b331a1c2f346f8457f16c7fe20f531bc2500e271f7c14c"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a11bcf609d00cfc9baed77ab308223cabc1f0b22a05774a26dd4c94c0c80f1f"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:5d7bdea33354b55acf40bb4dd3ba7324d6f1ef6b4a1a4da0807591f8c7e87b9a"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d03b645852d605f43003020e78fe6d573cae6ee6b944193e36b8b317e7549a20"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-win32.whl", hash = "sha256:52b185dfc3bf32e70929310367dbc66185afba60492a6a75a9b1141d407e160c"},
+ {file = "grpcio_tools-1.62.1-cp39-cp39-win_amd64.whl", hash = "sha256:63a273b70896d3640b7a883eb4a080c3c263d91662d870a2e9c84b7bbd978e7b"},
+]
+
+[package.dependencies]
+grpcio = ">=1.62.1"
+protobuf = ">=4.21.6,<5.0dev"
+setuptools = "*"
+
[[package]]
name = "h11"
version = "0.14.0"
@@ -1070,6 +1204,32 @@ files = [
{file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
]
+[[package]]
+name = "h2"
+version = "4.1.0"
+description = "HTTP/2 State-Machine based protocol implementation"
+optional = true
+python-versions = ">=3.6.1"
+files = [
+ {file = "h2-4.1.0-py3-none-any.whl", hash = "sha256:03a46bcf682256c95b5fd9e9a99c1323584c3eec6440d379b9903d709476bc6d"},
+ {file = "h2-4.1.0.tar.gz", hash = "sha256:a83aca08fbe7aacb79fec788c9c0bac936343560ed9ec18b82a13a12c28d2abb"},
+]
+
+[package.dependencies]
+hpack = ">=4.0,<5"
+hyperframe = ">=6.0,<7"
+
+[[package]]
+name = "hpack"
+version = "4.0.0"
+description = "Pure-Python HPACK header compression"
+optional = true
+python-versions = ">=3.6.1"
+files = [
+ {file = "hpack-4.0.0-py3-none-any.whl", hash = "sha256:84a076fad3dc9a9f8063ccb8041ef100867b1878b25ef0ee63847a5d53818a6c"},
+ {file = "hpack-4.0.0.tar.gz", hash = "sha256:fc41de0c63e687ebffde81187a948221294896f6bdc0ae2312708df339430095"},
+]
+
[[package]]
name = "httpcore"
version = "1.0.4"
@@ -1105,6 +1265,7 @@ files = [
[package.dependencies]
anyio = "*"
certifi = "*"
+h2 = {version = ">=3,<5", optional = true, markers = "extra == \"http2\""}
httpcore = "==1.*"
idna = "*"
sniffio = "*"
@@ -1161,6 +1322,17 @@ files = [
[package.dependencies]
pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_version >= \"3.8\""}
+[[package]]
+name = "hyperframe"
+version = "6.0.1"
+description = "HTTP/2 framing layer for Python"
+optional = true
+python-versions = ">=3.6.1"
+files = [
+ {file = "hyperframe-6.0.1-py3-none-any.whl", hash = "sha256:0ec6bafd80d8ad2195c4f03aacba3a8265e57bc4cff261e802bf39970ed02a15"},
+ {file = "hyperframe-6.0.1.tar.gz", hash = "sha256:ae510046231dc8e9ecb1a6586f63d2347bf4c8905914aa84ba585ae85f28a914"},
+]
+
[[package]]
name = "idna"
version = "3.6"
@@ -2522,6 +2694,25 @@ files = [
dev = ["pre-commit", "tox"]
testing = ["pytest", "pytest-benchmark"]
+[[package]]
+name = "portalocker"
+version = "2.8.2"
+description = "Wraps the portalocker recipe for easy usage"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "portalocker-2.8.2-py3-none-any.whl", hash = "sha256:cfb86acc09b9aa7c3b43594e19be1345b9d16af3feb08bf92f23d4dce513a28e"},
+ {file = "portalocker-2.8.2.tar.gz", hash = "sha256:2b035aa7828e46c58e9b31390ee1f169b98e1066ab10b9a6a861fe7e25ee4f33"},
+]
+
+[package.dependencies]
+pywin32 = {version = ">=226", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+docs = ["sphinx (>=1.7.1)"]
+redis = ["redis"]
+tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)", "types-redis"]
+
[[package]]
name = "prompt-toolkit"
version = "3.0.43"
@@ -3049,6 +3240,32 @@ files = [
[package.dependencies]
cffi = {version = "*", markers = "implementation_name == \"pypy\""}
+[[package]]
+name = "qdrant-client"
+version = "1.8.0"
+description = "Client library for the Qdrant vector search engine"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "qdrant_client-1.8.0-py3-none-any.whl", hash = "sha256:fa28d3eb64c0c57ec029c7c85c71f6c72c197f92502022655741f3632c518e29"},
+ {file = "qdrant_client-1.8.0.tar.gz", hash = "sha256:2a1a3f2cbacc7adba85644cf6cfdee20401cf25764b32da479c81fb63e178d15"},
+]
+
+[package.dependencies]
+grpcio = ">=1.41.0"
+grpcio-tools = ">=1.41.0"
+httpx = {version = ">=0.14.0", extras = ["http2"]}
+numpy = [
+ {version = ">=1.21", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
+ {version = ">=1.26", markers = "python_version >= \"3.12\""},
+]
+portalocker = ">=2.7.0,<3.0.0"
+pydantic = ">=1.10.8"
+urllib3 = ">=1.26.14,<3"
+
+[package.extras]
+fastembed = ["fastembed (==0.2.2)"]
+
[[package]]
name = "regex"
version = "2023.12.25"
@@ -3330,6 +3547,22 @@ tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
testing = ["h5py (>=3.7.0)", "huggingface_hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools_rust (>=1.5.2)"]
torch = ["safetensors[numpy]", "torch (>=1.10)"]
+[[package]]
+name = "setuptools"
+version = "69.2.0"
+description = "Easily download, build, install, upgrade, and uninstall Python packages"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "setuptools-69.2.0-py3-none-any.whl", hash = "sha256:c21c49fb1042386df081cb5d86759792ab89efca84cf114889191cd09aacc80c"},
+ {file = "setuptools-69.2.0.tar.gz", hash = "sha256:0ff4183f8f42cd8fa3acea16c45205521a4ef28f73c6391d8a25e92893134f2e"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+
[[package]]
name = "six"
version = "1.16.0"
@@ -4034,9 +4267,10 @@ local = ["llama-cpp-python", "torch", "transformers"]
mistralai = ["mistralai"]
pinecone = ["pinecone-client"]
processing = ["matplotlib"]
+qdrant = ["qdrant-client"]
vision = ["pillow", "torch", "torchvision", "transformers"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.9,<3.13"
-content-hash = "b02bb06cd8c09237dafe711992b1cbe9e190a63ad8510e6478b94d052a141901"
+content-hash = "424cd1692d7d98c5e4be9774689edb8cf8cebc187fc35f0e80d6013e3b70a9c9"
diff --git a/pyproject.toml b/pyproject.toml
index bc43ed818baabcf5a41f3328661ae27844b9fd6f..94db45e6c2a9e8134748d4328134637bcb2af4f5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,6 +36,7 @@ torchvision = { version = "^0.17.0", optional = true}
pillow = { version= "^10.2.0", optional = true}
tiktoken = "^0.6.0"
matplotlib = { version="^3.8.3", optional = true}
+qdrant-client = {version="^1.8.0", optional = true}
[tool.poetry.extras]
hybrid = ["pinecone-text"]
@@ -45,6 +46,7 @@ pinecone = ["pinecone-client"]
vision = ["torch", "torchvision", "transformers", "pillow"]
processing = ["matplotlib"]
mistralai = ["mistralai"]
+qdrant = ["qdrant-client"]
[tool.poetry.group.dev.dependencies]
ipykernel = "^6.25.0"
diff --git a/semantic_router/index/__init__.py b/semantic_router/index/__init__.py
index 1ad70df4228e35b6212d2b749e5c1b123f539c25..9a01b996985414a5b60bd1c4f1280a4488999275 100644
--- a/semantic_router/index/__init__.py
+++ b/semantic_router/index/__init__.py
@@ -1,9 +1,11 @@
from semantic_router.index.base import BaseIndex
from semantic_router.index.local import LocalIndex
from semantic_router.index.pinecone import PineconeIndex
+from semantic_router.index.qdrant import QdrantIndex
__all__ = [
"BaseIndex",
"LocalIndex",
+ "QdrantIndex",
"PineconeIndex",
]
diff --git a/semantic_router/index/qdrant.py b/semantic_router/index/qdrant.py
new file mode 100644
index 0000000000000000000000000000000000000000..e1339afc033aae4bf9701675583a03aaa4acf225
--- /dev/null
+++ b/semantic_router/index/qdrant.py
@@ -0,0 +1,247 @@
+from typing import Any, Dict, List, Optional, Tuple, Union
+
+import numpy as np
+from pydantic.v1 import Field
+
+from semantic_router.index.base import BaseIndex
+from semantic_router.schema import Metric
+
+DEFAULT_COLLECTION_NAME = "semantic-router-index"
+DEFAULT_UPLOAD_BATCH_SIZE = 100
+SCROLL_SIZE = 1000
+SR_UTTERANCE_PAYLOAD_KEY = "sr_utterance"
+SR_ROUTE_PAYLOAD_KEY = "sr_route"
+
+
+class QdrantIndex(BaseIndex):
+ "The name of the collection to use"
+
+ index_name: str = Field(
+ default=DEFAULT_COLLECTION_NAME,
+ description="Name of the Qdrant collection."
+ f"Default: '{DEFAULT_COLLECTION_NAME}'",
+ )
+ location: Optional[str] = Field(
+ default=":memory:",
+ description="If ':memory:' - use an in-memory Qdrant instance."
+ "Used as 'url' value otherwise",
+ )
+ url: Optional[str] = Field(
+ default=None,
+ description="Qualified URL of the Qdrant instance."
+ "Optional[scheme], host, Optional[port], Optional[prefix]",
+ )
+ port: Optional[int] = Field(
+ default=6333,
+ description="Port of the REST API interface.",
+ )
+ grpc_port: int = Field(
+ default=6334,
+ description="Port of the gRPC interface.",
+ )
+ prefer_grpc: bool = Field(
+ default=None,
+ description="Whether to use gPRC interface whenever possible in methods",
+ )
+ https: Optional[bool] = Field(
+ default=None,
+ description="Whether to use HTTPS(SSL) protocol.",
+ )
+ api_key: Optional[str] = Field(
+ default=None,
+ description="API key for authentication in Qdrant Cloud.",
+ )
+ prefix: Optional[str] = Field(
+ default=None,
+ description="Prefix to the REST URL path. Example: `http://localhost:6333/some/prefix/{qdrant-endpoint}`.",
+ )
+ timeout: Optional[int] = Field(
+ default=None,
+ description="Timeout for REST and gRPC API requests.",
+ )
+ host: Optional[str] = Field(
+ default=None,
+ description="Host name of Qdrant service."
+ "If url and host are None, set to 'localhost'.",
+ )
+ path: Optional[str] = Field(
+ default=None,
+ description="Persistence path for Qdrant local",
+ )
+ grpc_options: Optional[Dict[str, Any]] = Field(
+ default=None,
+ description="Options to be passed to the low-level GRPC client, if used.",
+ )
+ dimensions: Union[int, None] = Field(
+ default=None,
+ description="Embedding dimensions."
+ "Defaults to the embedding length of the configured encoder.",
+ )
+ metric: Metric = Field(
+ default=Metric.COSINE,
+ description="Distance metric to use for similarity search.",
+ )
+ config: Optional[Dict[str, Any]] = Field(
+ default={},
+ description="Collection options passed to `QdrantClient#create_collection`.",
+ )
+ client: Any = Field(default=None, exclude=True)
+
+ def __init__(self, **kwargs):
+ super().__init__(**kwargs)
+ self.type = "qdrant"
+ self.client = self._initialize_client()
+
+ def _initialize_client(self):
+ try:
+ from qdrant_client import QdrantClient
+
+ return QdrantClient(
+ location=self.location,
+ url=self.url,
+ port=self.port,
+ grpc_port=self.grpc_port,
+ prefer_grpc=self.prefer_grpc,
+ https=self.https,
+ api_key=self.api_key,
+ prefix=self.prefix,
+ timeout=self.timeout,
+ host=self.host,
+ path=self.path,
+ grpc_options=self.grpc_options,
+ )
+
+ except ImportError as e:
+ raise ImportError(
+ "Please install 'qdrant-client' to use QdrantIndex."
+ "You can install it with: "
+ "`pip install 'semantic-router[qdrant]'`"
+ ) from e
+
+ def _init_collection(self) -> None:
+ from qdrant_client import QdrantClient, models
+
+ self.client: QdrantClient
+ if not self.client.collection_exists(self.index_name):
+ if not self.dimensions:
+ raise ValueError(
+ "Cannot create a collection without specifying the dimensions."
+ )
+
+ self.client.create_collection(
+ collection_name=self.index_name,
+ vectors_config=models.VectorParams(
+ size=self.dimensions, distance=self.convert_metric(self.metric)
+ ),
+ **self.config,
+ )
+
+ def add(
+ self,
+ embeddings: List[List[float]],
+ routes: List[str],
+ utterances: List[str],
+ batch_size: int = DEFAULT_UPLOAD_BATCH_SIZE,
+ ):
+ self.dimensions = self.dimensions or len(embeddings[0])
+ self._init_collection()
+
+ payloads = [
+ {SR_ROUTE_PAYLOAD_KEY: route, SR_UTTERANCE_PAYLOAD_KEY: utterance}
+ for route, utterance in zip(routes, utterances)
+ ]
+
+ # UUIDs are autogenerated by qdrant-client if not provided explicitly
+ self.client.upload_collection(
+ self.index_name,
+ vectors=embeddings,
+ payload=payloads,
+ batch_size=batch_size,
+ )
+
+ def get_routes(self) -> List[Tuple]:
+ """
+ Gets a list of route and utterance objects currently stored in the index.
+
+ Returns:
+ List[Tuple]: A list of (route_name, utterance) objects.
+ """
+
+ import grpc
+
+ results = []
+ next_offset = None
+ stop_scrolling = False
+ while not stop_scrolling:
+ records, next_offset = self.client.scroll(
+ self.index_name,
+ limit=SCROLL_SIZE,
+ offset=next_offset,
+ with_payload=True,
+ )
+ stop_scrolling = next_offset is None or (
+ isinstance(next_offset, grpc.PointId)
+ and next_offset.num == 0
+ and next_offset.uuid == ""
+ )
+
+ results.extend(records)
+
+ route_tuples = [
+ (x.payload[SR_ROUTE_PAYLOAD_KEY], x.payload[SR_UTTERANCE_PAYLOAD_KEY])
+ for x in results
+ ]
+ return route_tuples
+
+ def delete(self, route_name: str):
+ from qdrant_client import models
+
+ self.client.delete(
+ self.index_name,
+ points_selector=models.Filter(
+ must=[
+ models.FieldCondition(
+ key=SR_ROUTE_PAYLOAD_KEY,
+ match=models.MatchText(text=route_name),
+ )
+ ]
+ ),
+ )
+
+ def describe(self) -> dict:
+ collection_info = self.client.get_collection(self.index_name)
+
+ return {
+ "type": self.type,
+ "dimensions": collection_info.config.params.vectors.size,
+ "vectors": collection_info.points_count,
+ }
+
+ def query(self, vector: np.ndarray, top_k: int = 5) -> Tuple[np.ndarray, List[str]]:
+ results = self.client.search(
+ self.index_name, query_vector=vector, limit=top_k, with_payload=True
+ )
+ scores = [result.score for result in results]
+ route_names = [result.payload[SR_ROUTE_PAYLOAD_KEY] for result in results]
+ return np.array(scores), route_names
+
+ def delete_index(self):
+ self.client.delete_collection(self.index_name)
+
+ def convert_metric(self, metric: Metric):
+ from qdrant_client.models import Distance
+
+ mapping = {
+ Metric.COSINE: Distance.COSINE,
+ Metric.EUCLIDEAN: Distance.EUCLID,
+ Metric.DOTPRODUCT: Distance.DOT,
+ Metric.MANHATTAN: Distance.MANHATTAN,
+ }
+
+ if metric not in mapping:
+ raise ValueError(f"Unsupported Qdrant similarity metric: {metric}")
+
+ return mapping[metric]
+
+ def __len__(self):
+ return self.client.get_collection(self.index_name).points_count
diff --git a/semantic_router/layer.py b/semantic_router/layer.py
index 221de2bef3f02e5992750fd98d63fd1e02e94659..851fc1b6d8438d9b7526a8827773f9755890752e 100644
--- a/semantic_router/layer.py
+++ b/semantic_router/layer.py
@@ -318,9 +318,9 @@ class RouteLayer:
return cls(encoder=encoder, routes=config.routes)
@classmethod
- def from_config(cls, config: LayerConfig):
+ def from_config(cls, config: LayerConfig, index: Optional[BaseIndex] = None):
encoder = Encoder(type=config.encoder_type, name=config.encoder_name).model
- return cls(encoder=encoder, routes=config.routes)
+ return cls(encoder=encoder, routes=config.routes, index=index)
def add(self, route: Route):
logger.info(f"Adding `{route.name}` route")
diff --git a/semantic_router/schema.py b/semantic_router/schema.py
index 3e0cd5e5b4a3979d4566386ceec43f22f7f65ed8..85d428ef0494a882cd84b8c9ea8caf7c914de517 100644
--- a/semantic_router/schema.py
+++ b/semantic_router/schema.py
@@ -85,3 +85,10 @@ class DocumentSplit(BaseModel):
@property
def content(self) -> str:
return " ".join(self.docs)
+
+
+class Metric(Enum):
+ COSINE = "cosine"
+ DOTPRODUCT = "dotproduct"
+ EUCLIDEAN = "euclidean"
+ MANHATTAN = "manhattan"
diff --git a/tests/unit/test_layer.py b/tests/unit/test_layer.py
index 4a55777b66658a4635add189c7402a12fa947932..1f5bce5a776ef58a0cc70800a78c7c57d473f942 100644
--- a/tests/unit/test_layer.py
+++ b/tests/unit/test_layer.py
@@ -1,3 +1,4 @@
+import importlib
import os
import tempfile
from unittest.mock import mock_open, patch
@@ -5,6 +6,8 @@ from unittest.mock import mock_open, patch
import pytest
from semantic_router.encoders import BaseEncoder, CohereEncoder, OpenAIEncoder
+from semantic_router.index.local import LocalIndex
+from semantic_router.index.qdrant import QdrantIndex
from semantic_router.layer import LayerConfig, RouteLayer
from semantic_router.llms.base import BaseLLM
from semantic_router.route import Route
@@ -19,7 +22,7 @@ def mock_encoder_call(utterances):
"Bye": [1.0, 1.1, 1.2],
"Au revoir": [1.3, 1.4, 1.5],
}
- return [mock_responses.get(u, [0, 0, 0]) for u in utterances]
+ return [mock_responses.get(u, [0.0, 0.0, 0.0]) for u in utterances]
def layer_json():
@@ -118,9 +121,21 @@ def test_data():
]
+def get_test_indexes():
+ indexes = [LocalIndex]
+
+ if importlib.util.find_spec("qdrant_client") is not None:
+ indexes.append(QdrantIndex)
+
+ return indexes
+
+
+@pytest.mark.parametrize("index_cls", get_test_indexes())
class TestRouteLayer:
- def test_initialization(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes, top_k=10)
+ def test_initialization(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, top_k=10, index=index_cls()
+ )
assert openai_encoder.score_threshold == 0.82
assert route_layer.score_threshold == 0.82
assert route_layer.top_k == 10
@@ -131,29 +146,35 @@ class TestRouteLayer:
else 0 == 2
)
- def test_initialization_different_encoders(self, cohere_encoder, openai_encoder):
- route_layer_cohere = RouteLayer(encoder=cohere_encoder)
+ def test_initialization_different_encoders(
+ self, cohere_encoder, openai_encoder, index_cls
+ ):
+ route_layer_cohere = RouteLayer(encoder=cohere_encoder, index=index_cls())
assert cohere_encoder.score_threshold == 0.3
assert route_layer_cohere.score_threshold == 0.3
- route_layer_openai = RouteLayer(encoder=openai_encoder)
+ route_layer_openai = RouteLayer(encoder=openai_encoder, index=index_cls())
assert route_layer_openai.score_threshold == 0.82
- def test_initialization_no_encoder(self, openai_encoder):
+ def test_initialization_no_encoder(self, openai_encoder, index_cls):
os.environ["OPENAI_API_KEY"] = "test_api_key"
route_layer_none = RouteLayer(encoder=None)
assert route_layer_none.score_threshold == openai_encoder.score_threshold
def test_initialization_dynamic_route(
- self, cohere_encoder, openai_encoder, dynamic_routes
+ self, cohere_encoder, openai_encoder, dynamic_routes, index_cls
):
- route_layer_cohere = RouteLayer(encoder=cohere_encoder, routes=dynamic_routes)
+ route_layer_cohere = RouteLayer(
+ encoder=cohere_encoder, routes=dynamic_routes, index=index_cls()
+ )
assert route_layer_cohere.score_threshold == 0.3
- route_layer_openai = RouteLayer(encoder=openai_encoder, routes=dynamic_routes)
+ route_layer_openai = RouteLayer(
+ encoder=openai_encoder, routes=dynamic_routes, index=index_cls()
+ )
assert openai_encoder.score_threshold == 0.82
assert route_layer_openai.score_threshold == 0.82
- def test_add_route(self, openai_encoder):
- route_layer = RouteLayer(encoder=openai_encoder)
+ def test_add_route(self, openai_encoder, index_cls):
+ route_layer = RouteLayer(encoder=openai_encoder, index=index_cls())
route1 = Route(name="Route 1", utterances=["Yes", "No"])
route2 = Route(name="Route 2", utterances=["Maybe", "Sure"])
@@ -172,15 +193,19 @@ class TestRouteLayer:
assert route_layer.routes == [route1, route2]
assert route_layer.index.describe()["vectors"] == 4
- def test_list_route_names(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_list_route_names(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
route_names = route_layer.list_route_names()
assert set(route_names) == {
route.name for route in routes
}, "The list of route names should match the names of the routes added."
- def test_delete_route(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_delete_route(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
# Delete a route by name
route_to_delete = routes[0].name
route_layer.delete(route_to_delete)
@@ -194,8 +219,10 @@ class TestRouteLayer:
utterance not in route_layer.index
), "The route's utterances should be deleted from the index."
- def test_remove_route_not_found(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_remove_route_not_found(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
# Attempt to remove a route that does not exist
non_existent_route = "non-existent-route"
with pytest.raises(ValueError) as excinfo:
@@ -204,35 +231,43 @@ class TestRouteLayer:
str(excinfo.value) == f"Route `{non_existent_route}` not found"
), "Attempting to remove a non-existent route should raise a ValueError."
- def test_add_multiple_routes(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder)
+ def test_add_multiple_routes(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(encoder=openai_encoder, index=index_cls())
route_layer._add_routes(routes=routes)
assert route_layer.index is not None
assert route_layer.index.describe()["vectors"] == 5
- def test_query_and_classification(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_query_and_classification(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
query_result = route_layer(text="Hello").name
assert query_result in ["Route 1", "Route 2"]
- def test_query_with_no_index(self, openai_encoder):
- route_layer = RouteLayer(encoder=openai_encoder)
+ def test_query_with_no_index(self, openai_encoder, index_cls):
+ route_layer = RouteLayer(encoder=openai_encoder, index=index_cls())
with pytest.raises(ValueError):
assert route_layer(text="Anything").name is None
- def test_query_with_vector(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_query_with_vector(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
vector = [0.1, 0.2, 0.3]
query_result = route_layer(vector=vector).name
assert query_result in ["Route 1", "Route 2"]
- def test_query_with_no_text_or_vector(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_query_with_no_text_or_vector(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
with pytest.raises(ValueError):
route_layer()
- def test_semantic_classify(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_semantic_classify(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
classification, score = route_layer._semantic_classify(
[
{"route": "Route 1", "score": 0.9},
@@ -242,8 +277,10 @@ class TestRouteLayer:
assert classification == "Route 1"
assert score == [0.9]
- def test_semantic_classify_multiple_routes(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_semantic_classify_multiple_routes(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
classification, score = route_layer._semantic_classify(
[
{"route": "Route 1", "score": 0.9},
@@ -254,28 +291,34 @@ class TestRouteLayer:
assert classification == "Route 1"
assert score == [0.9, 0.8]
- def test_query_no_text_dynamic_route(self, openai_encoder, dynamic_routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=dynamic_routes)
+ def test_query_no_text_dynamic_route(
+ self, openai_encoder, dynamic_routes, index_cls
+ ):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=dynamic_routes, index=index_cls()
+ )
vector = [0.1, 0.2, 0.3]
with pytest.raises(ValueError):
route_layer(vector=vector)
- def test_pass_threshold(self, openai_encoder):
- route_layer = RouteLayer(encoder=openai_encoder)
+ def test_pass_threshold(self, openai_encoder, index_cls):
+ route_layer = RouteLayer(encoder=openai_encoder, index=index_cls())
assert not route_layer._pass_threshold([], 0.5)
assert route_layer._pass_threshold([0.6, 0.7], 0.5)
- def test_failover_score_threshold(self, base_encoder):
- route_layer = RouteLayer(encoder=base_encoder)
+ def test_failover_score_threshold(self, base_encoder, index_cls):
+ route_layer = RouteLayer(encoder=base_encoder, index=index_cls())
assert route_layer.score_threshold == 0.5
- def test_json(self, openai_encoder, routes):
+ def test_json(self, openai_encoder, routes, index_cls):
temp = tempfile.NamedTemporaryFile(suffix=".yaml", delete=False)
try:
temp_path = temp.name # Save the temporary file's path
temp.close() # Close the file to ensure it can be opened again on Windows
os.environ["OPENAI_API_KEY"] = "test_api_key"
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
route_layer.to_json(temp_path)
assert os.path.exists(temp_path)
route_layer_from_file = RouteLayer.from_json(temp_path)
@@ -286,13 +329,15 @@ class TestRouteLayer:
finally:
os.remove(temp_path) # Ensure the file is deleted even if the test fails
- def test_yaml(self, openai_encoder, routes):
+ def test_yaml(self, openai_encoder, routes, index_cls):
temp = tempfile.NamedTemporaryFile(suffix=".yaml", delete=False)
try:
temp_path = temp.name # Save the temporary file's path
temp.close() # Close the file to ensure it can be opened again on Windows
os.environ["OPENAI_API_KEY"] = "test_api_key"
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
route_layer.to_yaml(temp_path)
assert os.path.exists(temp_path)
route_layer_from_file = RouteLayer.from_yaml(temp_path)
@@ -303,7 +348,7 @@ class TestRouteLayer:
finally:
os.remove(temp_path) # Ensure the file is deleted even if the test fails
- def test_from_file_json(openai_encoder, tmp_path):
+ def test_from_file_json(openai_encoder, tmp_path, index_cls):
# Create a temporary JSON file with layer configuration
config_path = tmp_path / "config.json"
config_path.write_text(
@@ -319,7 +364,7 @@ class TestRouteLayer:
assert len(layer_config.routes) == 2
assert layer_config.routes[0].name == "politics"
- def test_from_file_yaml(openai_encoder, tmp_path):
+ def test_from_file_yaml(openai_encoder, tmp_path, index_cls):
# Create a temporary YAML file with layer configuration
config_path = tmp_path / "config.yaml"
config_path.write_text(
@@ -335,14 +380,14 @@ class TestRouteLayer:
assert len(layer_config.routes) == 2
assert layer_config.routes[0].name == "politics"
- def test_from_file_invalid_path(self):
+ def test_from_file_invalid_path(self, index_cls):
with pytest.raises(FileNotFoundError) as excinfo:
LayerConfig.from_file("nonexistent_path.json")
assert "[Errno 2] No such file or directory: 'nonexistent_path.json'" in str(
excinfo.value
)
- def test_from_file_unsupported_type(self, tmp_path):
+ def test_from_file_unsupported_type(self, tmp_path, index_cls):
# Create a temporary unsupported file
config_path = tmp_path / "config.unsupported"
config_path.write_text(layer_json())
@@ -351,7 +396,7 @@ class TestRouteLayer:
LayerConfig.from_file(str(config_path))
assert "Unsupported file type" in str(excinfo.value)
- def test_from_file_invalid_config(self, tmp_path):
+ def test_from_file_invalid_config(self, tmp_path, index_cls):
# Define an invalid configuration JSON
invalid_config_json = """
{
@@ -375,7 +420,7 @@ class TestRouteLayer:
excinfo.value
), "Loading an invalid configuration should raise an exception."
- def test_from_file_with_llm(self, tmp_path):
+ def test_from_file_with_llm(self, tmp_path, index_cls):
llm_config_json = """
{
"encoder_type": "cohere",
@@ -409,22 +454,25 @@ class TestRouteLayer:
layer_config.routes[0].llm.name == "fake-model-v1"
), "LLM instance should have the 'name' attribute set correctly"
- def test_config(self, openai_encoder, routes):
+ def test_config(self, openai_encoder, routes, index_cls):
os.environ["OPENAI_API_KEY"] = "test_api_key"
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
# confirm route creation functions as expected
layer_config = route_layer.to_config()
assert layer_config.routes == routes
# now load from config and confirm it's the same
- route_layer_from_config = RouteLayer.from_config(layer_config)
- assert (route_layer_from_config.index.index == route_layer.index.index).all()
+ route_layer_from_config = RouteLayer.from_config(layer_config, index_cls())
assert (
route_layer_from_config._get_route_names() == route_layer._get_route_names()
)
assert route_layer_from_config.score_threshold == route_layer.score_threshold
- def test_get_thresholds(self, openai_encoder, routes):
- route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
+ def test_get_thresholds(self, openai_encoder, routes, index_cls):
+ route_layer = RouteLayer(
+ encoder=openai_encoder, routes=routes, index=index_cls()
+ )
assert route_layer.get_thresholds() == {"Route 1": 0.82, "Route 2": 0.82}