diff --git a/poetry.lock b/poetry.lock
index 360f2988bf165befd1edf211f79c4a629589e17d..ed489810cb3640a3a64b6f447002dd62377937fd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,87 +2,87 @@
[[package]]
name = "aiohttp"
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+version = "3.9.3"
description = "Async http client/server framework (asyncio)"
optional = false
python-versions = ">=3.8"
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description = "Disable App Nap on macOS >= 10.9"
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optional = true
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gs = ["gcsfs"]
gui = ["panel"]
hdfs = ["pyarrow (>=1)"]
-http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
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oci = ["ocifs"]
s3 = ["s3fs"]
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ptyprocess = ">=0.5"
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@@ -2714,28 +2725,28 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
[[package]]
name = "ruff"
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+version = "0.1.15"
description = "An extremely fast Python linter and code formatter, written in Rust."
optional = false
python-versions = ">=3.7"
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- {file = "triton-2.1.0-0-pp38-pypy38_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:82fc5aeeedf6e36be4e4530cbdcba81a09d65c18e02f52dc298696d45721f3bd"},
- {file = "triton-2.1.0-0-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:81a96d110a738ff63339fc892ded095b31bd0d205e3aace262af8400d40b6fa8"},
+ {file = "triton-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2294514340cfe4e8f4f9e5c66c702744c4a117d25e618bd08469d0bfed1e2e5"},
+ {file = "triton-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da58a152bddb62cafa9a857dd2bc1f886dbf9f9c90a2b5da82157cd2b34392b0"},
+ {file = "triton-2.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0af58716e721460a61886668b205963dc4d1e4ac20508cc3f623aef0d70283d5"},
+ {file = "triton-2.2.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8fe46d3ab94a8103e291bd44c741cc294b91d1d81c1a2888254cbf7ff846dab"},
+ {file = "triton-2.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b8ce26093e539d727e7cf6f6f0d932b1ab0574dc02567e684377630d86723ace"},
+ {file = "triton-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:227cc6f357c5efcb357f3867ac2a8e7ecea2298cd4606a8ba1e931d1d5a947df"},
]
[package.dependencies]
filelock = "*"
[package.extras]
-build = ["cmake (>=3.18)", "lit"]
-tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
-tutorials = ["matplotlib", "pandas", "tabulate"]
+build = ["cmake (>=3.20)", "lit"]
+tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"]
+tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
[[package]]
name = "types-pyyaml"
@@ -3277,13 +3291,13 @@ files = [
[[package]]
name = "types-requests"
-version = "2.31.0.20240106"
+version = "2.31.0.20240125"
description = "Typing stubs for requests"
-optional = true
+optional = false
python-versions = ">=3.8"
files = [
- {file = "types-requests-2.31.0.20240106.tar.gz", hash = "sha256:0e1c731c17f33618ec58e022b614a1a2ecc25f7dc86800b36ef341380402c612"},
- {file = "types_requests-2.31.0.20240106-py3-none-any.whl", hash = "sha256:da997b3b6a72cc08d09f4dba9802fdbabc89104b35fe24ee588e674037689354"},
+ {file = "types-requests-2.31.0.20240125.tar.gz", hash = "sha256:03a28ce1d7cd54199148e043b2079cdded22d6795d19a2c2a6791a4b2b5e2eb5"},
+ {file = "types_requests-2.31.0.20240125-py3-none-any.whl", hash = "sha256:9592a9a4cb92d6d75d9b491a41477272b710e021011a2a3061157e2fb1f1a5d1"},
]
[package.dependencies]
@@ -3302,17 +3316,18 @@ files = [
[[package]]
name = "urllib3"
-version = "2.1.0"
+version = "2.2.0"
description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
python-versions = ">=3.8"
files = [
- {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
- {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
+ {file = "urllib3-2.2.0-py3-none-any.whl", hash = "sha256:ce3711610ddce217e6d113a2732fafad960a03fd0318c91faa79481e35c11224"},
+ {file = "urllib3-2.2.0.tar.gz", hash = "sha256:051d961ad0c62a94e50ecf1af379c3aba230c66c710493493560c0c223c49f20"},
]
[package.extras]
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
@@ -3459,8 +3474,9 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
fastembed = ["fastembed"]
hybrid = ["pinecone-text"]
local = ["llama-cpp-python", "torch", "transformers"]
+pinecone = ["pinecone-client"]
[metadata]
lock-version = "2.0"
-python-versions = "^3.9"
-content-hash = "9bce8a548105a7226534f2f2e7b1a4d9ec22cab06ada5e4b16ef12156a0983c3"
+python-versions = ">=3.9,<3.13"
+content-hash = "23b8995b7eee4df19bb2242d6a81de8557a855053b4346a532efa63be2ea303f"
diff --git a/pyproject.toml b/pyproject.toml
index c997d0075ca209bb1b2104cda227050fc2a9d0dc..1889ef6eb3d92245da2b96373c16749ebe2ed87e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,7 @@ readme = "README.md"
packages = [{include = "semantic_router"}]
[tool.poetry.dependencies]
-python = "^3.9"
+python = ">=3.9,<3.13"
pydantic = "^2.5.3"
openai = "^1.10.0"
cohere = "^4.32"
@@ -30,11 +30,12 @@ transformers = {version = "^4.36.2", optional = true}
llama-cpp-python = {version = "^0.2.28", optional = true}
black = "^23.12.1"
colorama = "^0.4.6"
-
+pinecone-client = {version="^3.0.0", optional = true}
[tool.poetry.extras]
hybrid = ["pinecone-text"]
fastembed = ["fastembed"]
local = ["torch", "transformers", "llama-cpp-python"]
+pinecone = ["pinecone-client"]
[tool.poetry.group.dev.dependencies]
ipykernel = "^6.25.0"
@@ -45,6 +46,7 @@ pytest-cov = "^4.1.0"
pytest-xdist = "^3.5.0"
mypy = "^1.7.1"
types-pyyaml = "^6.0.12.12"
+types-requests = "^2.31.0"
[build-system]
requires = ["poetry-core"]
diff --git a/semantic_router/index/__init__.py b/semantic_router/index/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ad70df4228e35b6212d2b749e5c1b123f539c25
--- /dev/null
+++ b/semantic_router/index/__init__.py
@@ -0,0 +1,9 @@
+from semantic_router.index.base import BaseIndex
+from semantic_router.index.local import LocalIndex
+from semantic_router.index.pinecone import PineconeIndex
+
+__all__ = [
+ "BaseIndex",
+ "LocalIndex",
+ "PineconeIndex",
+]
diff --git a/semantic_router/index/base.py b/semantic_router/index/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..77053ef08100a5d7dd5f06048ce9360b0987f091
--- /dev/null
+++ b/semantic_router/index/base.py
@@ -0,0 +1,59 @@
+from pydantic.v1 import BaseModel
+from typing import Any, List, Tuple, Optional, Union
+import numpy as np
+
+
+class BaseIndex(BaseModel):
+ """
+ Base class for indices using Pydantic's BaseModel.
+ This class outlines the expected interface for index classes.
+ Actual method implementations should be provided in subclasses.
+ """
+
+ # You can define common attributes here if there are any.
+ # For example, a placeholder for the index attribute:
+ index: Optional[Any] = None
+ routes: Optional[np.ndarray] = None
+ utterances: Optional[np.ndarray] = None
+ dimensions: Union[int, None] = None
+ type: str = "base"
+
+ def add(
+ self, embeddings: List[List[float]], routes: List[str], utterances: List[str]
+ ):
+ """
+ Add embeddings to the index.
+ This method should be implemented by subclasses.
+ """
+ raise NotImplementedError("This method should be implemented by subclasses.")
+
+ def delete(self, route_name: str):
+ """
+ Deletes route by route name.
+ This method should be implemented by subclasses.
+ """
+ raise NotImplementedError("This method should be implemented by subclasses.")
+
+ def describe(self) -> dict:
+ """
+ Returns a dictionary with index details such as type, dimensions, and total vector count.
+ This method should be implemented by subclasses.
+ """
+ raise NotImplementedError("This method should be implemented by subclasses.")
+
+ def query(self, vector: np.ndarray, top_k: int = 5) -> Tuple[np.ndarray, List[str]]:
+ """
+ Search the index for the query_vector and return top_k results.
+ This method should be implemented by subclasses.
+ """
+ raise NotImplementedError("This method should be implemented by subclasses.")
+
+ def delete_index(self):
+ """
+ Deletes or resets the index.
+ This method should be implemented by subclasses.
+ """
+ raise NotImplementedError("This method should be implemented by subclasses.")
+
+ class Config:
+ arbitrary_types_allowed = True
diff --git a/semantic_router/index/local.py b/semantic_router/index/local.py
new file mode 100644
index 0000000000000000000000000000000000000000..058ee2bc08e562a56327c61850471b14409dfa6a
--- /dev/null
+++ b/semantic_router/index/local.py
@@ -0,0 +1,101 @@
+import numpy as np
+from typing import List, Tuple, Optional
+from semantic_router.linear import similarity_matrix, top_scores
+from semantic_router.index.base import BaseIndex
+
+
+class LocalIndex(BaseIndex):
+ def __init__(
+ self,
+ index: Optional[np.ndarray] = None,
+ routes: Optional[np.ndarray] = None,
+ utterances: Optional[np.ndarray] = None,
+ ):
+ super().__init__(index=index, routes=routes, utterances=utterances)
+ self.type = "local"
+
+ class Config: # Stop pydantic from complaining about Optional[np.ndarray] type hints.
+ arbitrary_types_allowed = True
+
+ def add(
+ self, embeddings: List[List[float]], routes: List[str], utterances: List[str]
+ ):
+ embeds = np.array(embeddings) # type: ignore
+ routes_arr = np.array(routes)
+ utterances_arr = np.array(utterances)
+ if self.index is None:
+ self.index = embeds # type: ignore
+ self.routes = routes_arr
+ self.utterances = utterances_arr
+ else:
+ self.index = np.concatenate([self.index, embeds])
+ self.routes = np.concatenate([self.routes, routes_arr])
+ self.utterances = np.concatenate([self.utterances, utterances_arr])
+
+ 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.
+ """
+ if self.routes is None or self.utterances is None:
+ raise ValueError("No routes have been added to the index.")
+ return list(zip(self.routes, self.utterances))
+
+ def describe(self) -> dict:
+ return {
+ "type": self.type,
+ "dimensions": self.index.shape[1] if self.index is not None else 0,
+ "vectors": self.index.shape[0] if self.index is not None else 0,
+ }
+
+ def query(self, vector: np.ndarray, top_k: int = 5) -> Tuple[np.ndarray, List[str]]:
+ """
+ Search the index for the query and return top_k results.
+ """
+ if self.index is None or self.routes is None:
+ raise ValueError("Index or routes are not populated.")
+ sim = similarity_matrix(vector, self.index)
+ # extract the index values of top scoring vectors
+ scores, idx = top_scores(sim, top_k)
+ # get routes from index values
+ route_names = self.routes[idx].copy()
+ return scores, route_names
+
+ def delete(self, route_name: str):
+ """
+ Delete all records of a specific route from the index.
+ """
+ if (
+ self.index is not None
+ and self.routes is not None
+ and self.utterances is not None
+ ):
+ delete_idx = self._get_indices_for_route(route_name=route_name)
+ self.index = np.delete(self.index, delete_idx, axis=0)
+ self.routes = np.delete(self.routes, delete_idx, axis=0)
+ self.utterances = np.delete(self.utterances, delete_idx, axis=0)
+ else:
+ raise ValueError(
+ "Attempted to delete route records but either index, routes or utterances is None."
+ )
+
+ def delete_index(self):
+ """
+ Deletes the index, effectively clearing it and setting it to None.
+ """
+ self.index = None
+
+ def _get_indices_for_route(self, route_name: str):
+ """Gets an array of indices for a specific route."""
+ if self.routes is None:
+ raise ValueError("Routes are not populated.")
+ idx = [i for i, route in enumerate(self.routes) if route == route_name]
+ return idx
+
+ def __len__(self):
+ if self.index is not None:
+ return self.index.shape[0]
+ else:
+ return 0
diff --git a/semantic_router/index/pinecone.py b/semantic_router/index/pinecone.py
new file mode 100644
index 0000000000000000000000000000000000000000..a6492226a46ebd2550f9c467fa64aa44af36d0a3
--- /dev/null
+++ b/semantic_router/index/pinecone.py
@@ -0,0 +1,228 @@
+from pydantic.v1 import BaseModel, Field
+import requests
+import time
+import hashlib
+import os
+from typing import Any, Dict, List, Tuple, Optional, Union
+from semantic_router.index.base import BaseIndex
+from semantic_router.utils.logger import logger
+import numpy as np
+
+
+def clean_route_name(route_name: str) -> str:
+ return route_name.strip().replace(" ", "-")
+
+
+class PineconeRecord(BaseModel):
+ id: str = ""
+ values: List[float]
+ route: str
+ utterance: str
+
+ def __init__(self, **data):
+ super().__init__(**data)
+ # generate ID based on route name and utterances to prevent duplicates
+ clean_route = clean_route_name(self.route)
+ utterance_id = hashlib.md5(self.utterance.encode()).hexdigest()
+ self.id = f"{clean_route}#{utterance_id}"
+
+ def to_dict(self):
+ return {
+ "id": self.id,
+ "values": self.values,
+ "metadata": {"sr_route": self.route, "sr_utterance": self.utterance},
+ }
+
+
+class PineconeIndex(BaseIndex):
+ index_prefix: str = "semantic-router--"
+ index_name: str = "index"
+ dimensions: Union[int, None] = None
+ metric: str = "cosine"
+ cloud: str = "aws"
+ region: str = "us-west-2"
+ host: str = ""
+ client: Any = Field(default=None, exclude=True)
+ index: Optional[Any] = Field(default=None, exclude=True)
+ ServerlessSpec: Any = Field(default=None, exclude=True)
+
+ def __init__(self, **data):
+ super().__init__(**data)
+ self._initialize_client()
+
+ self.type = "pinecone"
+ self.client = self._initialize_client()
+ if not self.index_name.startswith(self.index_prefix):
+ self.index_name = f"{self.index_prefix}{self.index_name}"
+ # Create or connect to an existing Pinecone index
+ self.index = self._init_index()
+
+ def _initialize_client(self, api_key: Optional[str] = None):
+ try:
+ from pinecone import Pinecone, ServerlessSpec
+
+ self.ServerlessSpec = ServerlessSpec
+ except ImportError:
+ raise ImportError(
+ "Please install pinecone-client to use PineconeIndex. "
+ "You can install it with: "
+ "`pip install 'semantic-router[pinecone]'`"
+ )
+ api_key = api_key or os.getenv("PINECONE_API_KEY")
+ if api_key is None:
+ raise ValueError("Pinecone API key is required.")
+ return Pinecone(api_key=api_key)
+
+ def _init_index(self, force_create: bool = False) -> Union[Any, None]:
+ index_exists = self.index_name in self.client.list_indexes().names()
+ dimensions_given = self.dimensions is not None
+ if dimensions_given and not index_exists:
+ # if the index doesn't exist and we have dimension value
+ # we create the index
+ self.client.create_index(
+ name=self.index_name,
+ dimension=self.dimensions,
+ metric=self.metric,
+ spec=self.ServerlessSpec(cloud=self.cloud, region=self.region),
+ )
+ # wait for index to be created
+ while not self.client.describe_index(self.index_name).status["ready"]:
+ time.sleep(1)
+ index = self.client.Index(self.index_name)
+ time.sleep(0.5)
+ elif index_exists:
+ # if the index exists we just return it
+ index = self.client.Index(self.index_name)
+ # grab the dimensions from the index
+ self.dimensions = index.describe_index_stats()["dimension"]
+ elif force_create and not dimensions_given:
+ raise ValueError(
+ "Cannot create an index without specifying the dimensions."
+ )
+ else:
+ # if the index doesn't exist and we don't have the dimensions
+ # we return None
+ logger.warning("Index could not be initialized.")
+ index = None
+ if index is not None:
+ self.host = self.client.describe_index(self.index_name)["host"]
+ return index
+
+ def add(
+ self, embeddings: List[List[float]], routes: List[str], utterances: List[str]
+ ):
+ if self.index is None:
+ self.dimensions = self.dimensions or len(embeddings[0])
+ # we set force_create to True as we MUST have an index to add data
+ self.index = self._init_index(force_create=True)
+ vectors_to_upsert = []
+ for vector, route, utterance in zip(embeddings, routes, utterances):
+ record = PineconeRecord(values=vector, route=route, utterance=utterance)
+ vectors_to_upsert.append(record.to_dict())
+ if self.index is not None:
+ self.index.upsert(vectors=vectors_to_upsert)
+ else:
+ raise ValueError("Index is None could not upsert.")
+
+ def _get_route_ids(self, route_name: str):
+ clean_route = clean_route_name(route_name)
+ ids, _ = self._get_all(prefix=f"{clean_route}#")
+ return ids
+
+ def _get_all(self, prefix: Optional[str] = None, include_metadata: bool = False):
+ """
+ Retrieves all vector IDs from the Pinecone index using pagination.
+ """
+ if self.index is None:
+ raise ValueError("Index is None, could not retrieve vector IDs.")
+ all_vector_ids = []
+ next_page_token = None
+
+ if prefix:
+ prefix_str = f"?prefix={prefix}"
+ else:
+ prefix_str = ""
+
+ # Construct the request URL for listing vectors. Adjust parameters as needed.
+ list_url = f"https://{self.host}/vectors/list{prefix_str}"
+ params: Dict = {}
+ headers = {"Api-Key": os.environ["PINECONE_API_KEY"]}
+ metadata = []
+
+ while True:
+ if next_page_token:
+ params["paginationToken"] = next_page_token
+
+ # Make the request to list vectors. Adjust headers and parameters as needed.
+ response = requests.get(list_url, params=params, headers=headers)
+ response_data = response.json()
+ print(response_data)
+
+ # Extract vector IDs from the response and add them to the list
+ vector_ids = [vec["id"] for vec in response_data.get("vectors", [])]
+ all_vector_ids.extend(vector_ids)
+
+ # if we need metadata, we fetch it
+ if include_metadata:
+ res_meta = self.index.fetch(ids=vector_ids)
+ # extract metadata only
+ metadata.extend([x["metadata"] for x in res_meta["vectors"].values()])
+
+ # Check if there's a next page token; if not, break the loop
+ next_page_token = response_data.get("pagination", {}).get("next")
+ if not next_page_token:
+ break
+
+ return all_vector_ids, metadata
+
+ 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.
+ """
+ # Get all records
+ _, metadata = self._get_all(include_metadata=True)
+ route_tuples = [(x["sr_route"], x["sr_utterance"]) for x in metadata]
+ return route_tuples
+
+ def delete(self, route_name: str):
+ route_vec_ids = self._get_route_ids(route_name=route_name)
+ if self.index is not None:
+ self.index.delete(ids=route_vec_ids)
+ else:
+ raise ValueError("Index is None, could not delete.")
+
+ def delete_all(self):
+ self.index.delete(delete_all=True)
+
+ def describe(self) -> dict:
+ if self.index is not None:
+ stats = self.index.describe_index_stats()
+ return {
+ "type": self.type,
+ "dimensions": stats["dimension"],
+ "vectors": stats["total_vector_count"],
+ }
+ else:
+ raise ValueError("Index is None, cannot describe index stats.")
+
+ def query(self, vector: np.ndarray, top_k: int = 5) -> Tuple[np.ndarray, List[str]]:
+ if self.index is None:
+ raise ValueError("Index is not populated.")
+ query_vector_list = vector.tolist()
+ results = self.index.query(
+ vector=[query_vector_list],
+ top_k=top_k,
+ include_metadata=True,
+ )
+ scores = [result["score"] for result in results["matches"]]
+ route_names = [result["metadata"]["sr_route"] for result in results["matches"]]
+ return np.array(scores), route_names
+
+ def delete_index(self):
+ self.client.delete_index(self.index_name)
+
+ def __len__(self):
+ return self.index.describe_index_stats()["total_vector_count"]
diff --git a/semantic_router/layer.py b/semantic_router/layer.py
index 08afccfab19b590a1fc975e9325c69d6cb961d0b..5d56aefb96f86881838b960c9c80f02b28f40f29 100644
--- a/semantic_router/layer.py
+++ b/semantic_router/layer.py
@@ -8,11 +8,12 @@ import yaml
from tqdm.auto import tqdm
from semantic_router.encoders import BaseEncoder, OpenAIEncoder
-from semantic_router.linear import similarity_matrix, top_scores
from semantic_router.llms import BaseLLM, OpenAILLM
from semantic_router.route import Route
from semantic_router.schema import Encoder, EncoderType, RouteChoice
from semantic_router.utils.logger import logger
+from semantic_router.index.base import BaseIndex
+from semantic_router.index.local import LocalIndex
def is_valid(layer_config: str) -> bool:
@@ -151,20 +152,19 @@ class LayerConfig:
class RouteLayer:
- index: Optional[np.ndarray] = None
- categories: Optional[np.ndarray] = None
score_threshold: float
encoder: BaseEncoder
+ index: BaseIndex
def __init__(
self,
encoder: Optional[BaseEncoder] = None,
llm: Optional[BaseLLM] = None,
routes: Optional[List[Route]] = None,
+ index: Optional[BaseIndex] = None, # type: ignore
):
- logger.info("Initializing RouteLayer")
- self.index = None
- self.categories = None
+ logger.info("local")
+ self.index: BaseIndex = index if index is not None else LocalIndex()
if encoder is None:
logger.warning(
"No encoder provided. Using default OpenAIEncoder. Ensure "
@@ -206,7 +206,7 @@ class RouteLayer:
vector_arr = self._encode(text=text)
else:
vector_arr = np.array(vector)
- # get relevant utterances
+ # get relevant results (scores and routes)
results = self._retrieve(xq=vector_arr)
# decide most relevant routes
top_class, top_class_scores = self._semantic_classify(results)
@@ -274,64 +274,64 @@ class RouteLayer:
if route.score_threshold is None:
route.score_threshold = self.score_threshold
- # create route array
- if self.categories is None:
- self.categories = np.array([route.name] * len(embeds))
- else:
- str_arr = np.array([route.name] * len(embeds))
- self.categories = np.concatenate([self.categories, str_arr])
- # create utterance array (the index)
- if self.index is None:
- self.index = np.array(embeds)
- else:
- embed_arr = np.array(embeds)
- self.index = np.concatenate([self.index, embed_arr])
- # add route to routes list
+ # add routes to the index
+ self.index.add(
+ embeddings=embeds,
+ routes=[route.name] * len(route.utterances),
+ utterances=route.utterances,
+ )
self.routes.append(route)
def list_route_names(self) -> List[str]:
return [route.name for route in self.routes]
- def remove(self, name: str):
- if name not in [route.name for route in self.routes]:
- err_msg = f"Route `{name}` not found"
+ def update(self, route_name: str, utterances: List[str]):
+ raise NotImplementedError("This method has not yet been implemented.")
+
+ def delete(self, route_name: str):
+ """Deletes a route given a specific route name.
+
+ :param route_name: the name of the route to be deleted
+ :type str:
+ """
+ if route_name not in [route.name for route in self.routes]:
+ err_msg = f"Route `{route_name}` not found"
logger.error(err_msg)
raise ValueError(err_msg)
else:
- self.routes = [route for route in self.routes if route.name != name]
- logger.info(f"Removed route `{name}`")
- # Also remove from index and categories
- if self.categories is not None and self.index is not None:
- indices_to_remove = [
- i
- for i, route_name in enumerate(self.categories)
- if route_name == name
- ]
- self.index = np.delete(self.index, indices_to_remove, axis=0)
- self.categories = np.delete(self.categories, indices_to_remove, axis=0)
+ self.routes = [route for route in self.routes if route.name != route_name]
+ self.index.delete(route_name=route_name)
+
+ def _refresh_routes(self):
+ """Pulls out the latest routes from the index."""
+ raise NotImplementedError("This method has not yet been implemented.")
+ route_mapping = {route.name: route for route in self.routes}
+ index_routes = self.index.get_routes()
+ new_routes_names = []
+ new_routes = []
+ for route_name, utterance in index_routes:
+ if route_name in route_mapping:
+ if route_name not in new_routes_names:
+ existing_route = route_mapping[route_name]
+ new_routes.append(existing_route)
+
+ new_routes.append(Route(name=route_name, utterances=[utterance]))
+ route = route_mapping[route_name]
+ self.routes.append(route)
def _add_routes(self, routes: List[Route]):
# create embeddings for all routes
all_utterances = [
utterance for route in routes for utterance in route.utterances
]
- embedded_utterance = self.encoder(all_utterances)
-
+ embedded_utterances = self.encoder(all_utterances)
# create route array
route_names = [route.name for route in routes for _ in route.utterances]
- route_array = np.array(route_names)
- self.categories = (
- np.concatenate([self.categories, route_array])
- if self.categories is not None
- else route_array
- )
-
- # create utterance array (the index)
- embed_utterance_arr = np.array(embedded_utterance)
- self.index = (
- np.concatenate([self.index, embed_utterance_arr])
- if self.index is not None
- else embed_utterance_arr
+ # add everything to the index
+ self.index.add(
+ embeddings=embedded_utterances,
+ routes=route_names,
+ utterances=all_utterances,
)
def _encode(self, text: str) -> Any:
@@ -343,16 +343,9 @@ class RouteLayer:
def _retrieve(self, xq: Any, top_k: int = 5) -> List[dict]:
"""Given a query vector, retrieve the top_k most similar records."""
- if self.index is not None:
- # calculate similarity matrix
- sim = similarity_matrix(xq, self.index)
- scores, idx = top_scores(sim, top_k)
- # get the utterance categories (route names)
- routes = self.categories[idx] if self.categories is not None else []
- return [{"route": d, "score": s.item()} for d, s in zip(routes, scores)]
- else:
- logger.warning("No index found for route layer.")
- return []
+ # get scores and routes
+ scores, routes = self.index.query(vector=xq, top_k=top_k)
+ return [{"route": d, "score": s.item()} for d, s in zip(routes, scores)]
def _semantic_classify(self, query_results: List[dict]) -> Tuple[str, List[float]]:
scores_by_class: Dict[str, List[float]] = {}
@@ -464,6 +457,9 @@ class RouteLayer:
accuracy = correct / len(Xq)
return accuracy
+ def _get_route_names(self) -> List[str]:
+ return [route.name for route in self.routes]
+
def threshold_random_search(
route_layer: RouteLayer,
diff --git a/tests/unit/test_layer.py b/tests/unit/test_layer.py
index 9669d594a0e560bea125c75d8cc5cd46caaac7df..03c0c1eaba540ec6f0f9ae0dc93ab38e41a3265d 100644
--- a/tests/unit/test_layer.py
+++ b/tests/unit/test_layer.py
@@ -124,8 +124,8 @@ class TestRouteLayer:
assert route_layer.score_threshold == 0.82
assert len(route_layer.index) if route_layer.index is not None else 0 == 5
assert (
- len(set(route_layer.categories))
- if route_layer.categories is not None
+ len(set(route_layer._get_route_names()))
+ if route_layer._get_route_names() is not None
else 0 == 2
)
@@ -155,17 +155,20 @@ class TestRouteLayer:
route1 = Route(name="Route 1", utterances=["Yes", "No"])
route2 = Route(name="Route 2", utterances=["Maybe", "Sure"])
+ # Initially, the routes list should be empty
+ assert route_layer.routes == []
+
+ # Add route1 and check
route_layer.add(route=route1)
- assert route_layer.index is not None and route_layer.categories is not None
- assert route_layer.index.shape[0] == 2
- assert len(set(route_layer.categories)) == 1
- assert set(route_layer.categories) == {"Route 1"}
+ assert route_layer.routes == [route1]
+ assert route_layer.index is not None
+ # Use the describe method to get the number of vectors
+ assert route_layer.index.describe()["vectors"] == 2
+ # Add route2 and check
route_layer.add(route=route2)
- assert route_layer.index.shape[0] == 4
- assert len(set(route_layer.categories)) == 2
- assert set(route_layer.categories) == {"Route 1", "Route 2"}
- del route_layer
+ 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)
@@ -174,31 +177,27 @@ class TestRouteLayer:
route.name for route in routes
}, "The list of route names should match the names of the routes added."
- def test_remove_route(self, openai_encoder, routes):
+ def test_delete_route(self, openai_encoder, routes):
route_layer = RouteLayer(encoder=openai_encoder, routes=routes)
- # Remove a route by name
- route_to_remove = routes[0].name
- route_layer.remove(route_to_remove)
+ # Delete a route by name
+ route_to_delete = routes[0].name
+ route_layer.delete(route_to_delete)
# Ensure the route is no longer in the route layer
assert (
- route_to_remove not in route_layer.list_route_names()
- ), "The route should be removed from the route layer."
- # Ensure the route is no longer in the index or categories
- assert (
- route_to_remove not in route_layer.categories
- ), "The route should be removed from the categories."
+ route_to_delete not in route_layer.list_route_names()
+ ), "The route should be deleted from the route layer."
# Ensure the route's utterances are no longer in the index
for utterance in routes[0].utterances:
assert (
utterance not in route_layer.index
- ), "The route's utterances should be removed from the 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)
# Attempt to remove a route that does not exist
non_existent_route = "non-existent-route"
with pytest.raises(ValueError) as excinfo:
- route_layer.remove(non_existent_route)
+ route_layer.delete(non_existent_route)
assert (
str(excinfo.value) == f"Route `{non_existent_route}` not found"
), "Attempting to remove a non-existent route should raise a ValueError."
@@ -206,9 +205,8 @@ class TestRouteLayer:
def test_add_multiple_routes(self, openai_encoder, routes):
route_layer = RouteLayer(encoder=openai_encoder)
route_layer._add_routes(routes=routes)
- assert route_layer.index is not None and route_layer.categories is not None
- assert route_layer.index.shape[0] == 5
- assert len(set(route_layer.categories)) == 2
+ 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)
@@ -217,7 +215,8 @@ class TestRouteLayer:
def test_query_with_no_index(self, openai_encoder):
route_layer = RouteLayer(encoder=openai_encoder)
- assert route_layer(text="Anything").name is None
+ 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)
@@ -277,7 +276,7 @@ class TestRouteLayer:
route_layer_from_file = RouteLayer.from_json(temp.name)
assert (
route_layer_from_file.index is not None
- and route_layer_from_file.categories is not None
+ and route_layer_from_file._get_route_names() is not None
)
os.remove(temp.name)
@@ -290,7 +289,7 @@ class TestRouteLayer:
route_layer_from_file = RouteLayer.from_yaml(temp.name)
assert (
route_layer_from_file.index is not None
- and route_layer_from_file.categories is not None
+ and route_layer_from_file._get_route_names() is not None
)
os.remove(temp.name)
@@ -302,8 +301,10 @@ class TestRouteLayer:
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 == route_layer.index).all()
- assert (route_layer_from_config.categories == route_layer.categories).all()
+ assert (route_layer_from_config.index.index == route_layer.index.index).all()
+ 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):