diff --git a/examples/openai_search.py b/examples/openai_search.py new file mode 100644 index 00000000..f42f7696 --- /dev/null +++ b/examples/openai_search.py @@ -0,0 +1,50 @@ +from neo4j import GraphDatabase +from neo4j_genai import VectorRetriever + +from random import random +from neo4j_genai.indexes import create_vector_index + +from langchain_openai import OpenAIEmbeddings + +URI = "neo4j://localhost:7687" +AUTH = ("neo4j", "password") + +INDEX_NAME = "embedding-name-large" +DIMENSION = 3072 + +# Connect to Neo4j database +driver = GraphDatabase.driver(URI, auth=AUTH) + + +# Create Embedder object +embedder = OpenAIEmbeddings(model="text-embedding-3-large") + +# Initialize the retriever +retriever = VectorRetriever(driver, INDEX_NAME, embedder) + +# Creating the index +create_vector_index( + driver, + INDEX_NAME, + label="Document", + property="propertyKey", + dimensions=DIMENSION, + similarity_fn="cosine", +) + +# Upsert the query +vector = [random() for _ in range(DIMENSION)] +insert_query = ( + "MERGE (n:Document)" + "WITH n " + "CALL db.create.setNodeVectorProperty(n, 'propertyKey', $vector)" + "RETURN n" +) +parameters = { + "vector": vector, +} +driver.execute_query(insert_query, parameters) + +# Perform the similarity search for a text query +query_text = "hello world" +print(retriever.search(query_text=query_text, top_k=5)) diff --git a/examples/similarity_search_for_text.py b/examples/similarity_search_for_text.py index 40c09492..3104bbc6 100644 --- a/examples/similarity_search_for_text.py +++ b/examples/similarity_search_for_text.py @@ -1,9 +1,10 @@ from typing import List from neo4j import GraphDatabase -from neo4j_genai.client import GenAIClient +from neo4j_genai import VectorRetriever from random import random from neo4j_genai.embedder import Embedder +from neo4j_genai.indexes import create_vector_index URI = "neo4j://localhost:7687" AUTH = ("neo4j", "password") @@ -23,11 +24,9 @@ def embed_query(self, text: str) -> List[float]: embedder = CustomEmbedder() -# Initialize the client -client = GenAIClient(driver, embedder) - # Creating the index -client.create_index( +create_vector_index( + driver, INDEX_NAME, label="Document", property="propertyKey", @@ -35,6 +34,9 @@ def embed_query(self, text: str) -> List[float]: similarity_fn="euclidean", ) +# Initialize the retriever +retriever = VectorRetriever(driver, INDEX_NAME, embedder) + # Upsert the query vector = [random() for _ in range(DIMENSION)] insert_query = ( @@ -50,4 +52,4 @@ def embed_query(self, text: str) -> List[float]: # Perform the similarity search for a text query query_text = "hello world" -print(client.similarity_search(INDEX_NAME, query_text=query_text, top_k=5)) +print(retriever.search(query_text=query_text, top_k=5)) diff --git a/examples/similarity_search_for_vector.py b/examples/similarity_search_for_vector.py index 6c4c9c3a..31045676 100644 --- a/examples/similarity_search_for_vector.py +++ b/examples/similarity_search_for_vector.py @@ -1,8 +1,10 @@ from neo4j import GraphDatabase -from neo4j_genai.client import GenAIClient +from neo4j_genai import VectorRetriever from random import random +from neo4j_genai.indexes import create_vector_index + URI = "neo4j://localhost:7687" AUTH = ("neo4j", "password") @@ -12,11 +14,9 @@ # Connect to Neo4j database driver = GraphDatabase.driver(URI, auth=AUTH) -# Initialize the client -client = GenAIClient(driver) - # Creating the index -client.create_index( +create_vector_index( + driver, INDEX_NAME, label="Document", property="propertyKey", @@ -24,6 +24,9 @@ similarity_fn="euclidean", ) +# Initialize the retriever +retriever = VectorRetriever(driver, INDEX_NAME) + # Upsert the vector vector = [random() for _ in range(DIMENSION)] insert_query = ( @@ -40,4 +43,4 @@ # Perform the similarity search for a vector query query_vector = [random() for _ in range(DIMENSION)] -print(client.similarity_search(INDEX_NAME, query_vector=query_vector, top_k=5)) +print(retriever.search(query_vector=query_vector, top_k=5)) diff --git a/poetry.lock b/poetry.lock index 813c5c70..d9811a01 100644 --- a/poetry.lock +++ b/poetry.lock @@ -14,6 +14,28 @@ files = [ [package.dependencies] typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""} +[[package]] +name = "anyio" +version = "4.3.0" +description = "High level compatibility layer for multiple asynchronous event loop implementations" +optional = false +python-versions = ">=3.8" +files = [ + {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"}, + {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"}, +] + +[package.dependencies] +exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} +idna = ">=2.8" +sniffio = ">=1.1" +typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} + +[package.extras] +doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] +trio = ["trio (>=0.23)"] + [[package]] name = "astroid" version = "3.1.0" @@ -28,6 +50,17 @@ files = [ [package.dependencies] typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} +[[package]] +name = "certifi" +version = "2024.2.2" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.6" +files = [ + {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, + {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, +] + [[package]] name = "cfgv" version = "3.4.0" @@ -39,6 +72,105 @@ files = [ {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"}, ] +[[package]] +name = "charset-normalizer" +version = "3.3.2" +description = "The Real First Universal Charset Detector. 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"ff3141131bbe26cdd25356cdddaf29dd8d4d41d4551b60169b04915b5b046671" diff --git a/pyproject.toml b/pyproject.toml index 357bb014..55b6d3eb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,7 @@ include = "neo4j_genai" from = "src" [tool.poetry.dependencies] -python = "^3.8" +python = "^3.8.1" neo4j = "^5.17.0" types-requests = "^2.31.0.20240218" pydantic = "^2.6.3" @@ -24,6 +24,7 @@ pytest-mock = "^3.12.0" pre-commit = { version = "^3.6.2", python = "^3.9" } coverage = "^7.4.3" ruff = "^0.3.0" +langchain-openai = "^0.1.1" [build-system] requires = ["poetry-core"] diff --git a/src/neo4j_genai/__init__.py b/src/neo4j_genai/__init__.py index c7748c58..de6038a8 100644 --- a/src/neo4j_genai/__init__.py +++ b/src/neo4j_genai/__init__.py @@ -1,4 +1,4 @@ -from .client import GenAIClient +from .retrievers import VectorRetriever -__all__ = ["GenAIClient"] +__all__ = ["VectorRetriever"] diff --git a/src/neo4j_genai/indexes.py b/src/neo4j_genai/indexes.py index d1e62ddc..29301d61 100644 --- a/src/neo4j_genai/indexes.py +++ b/src/neo4j_genai/indexes.py @@ -46,7 +46,7 @@ def create_vector_index( raise ValueError(f"Error for inputs to create_vector_index {str(e)}") query = ( - f"CREATE VECTOR INDEX $name IF NOT EXISTS FOR (n:{label}) ON n.{property} OPTIONS " + f"CREATE VECTOR INDEX $name FOR (n:{label}) ON n.{property} OPTIONS " "{ indexConfig: { `vector.dimensions`: toInteger($dimensions), `vector.similarity_function`: $similarity_fn } }" ) driver.execute_query( diff --git a/src/neo4j_genai/client.py b/src/neo4j_genai/retrievers.py similarity index 60% rename from src/neo4j_genai/client.py rename to src/neo4j_genai/retrievers.py index 82580a4d..ef1ab84d 100644 --- a/src/neo4j_genai/client.py +++ b/src/neo4j_genai/retrievers.py @@ -2,21 +2,23 @@ from pydantic import ValidationError from neo4j import Driver from .embedder import Embedder -from .types import VectorIndexModel, SimilaritySearchModel, Neo4jRecord +from .types import SimilaritySearchModel, Neo4jRecord -class GenAIClient: +class VectorRetriever: """ - Provides functionality to use Neo4j's GenAI features + Provides retrieval methods using vector search over embeddings """ def __init__( self, driver: Driver, + index_name: str, embedder: Optional[Embedder] = None, ) -> None: self.driver = driver self._verify_version() + self.index_name = index_name self.embedder = embedder def _verify_version(self) -> None: @@ -46,71 +48,8 @@ def _verify_version(self) -> None: "This package only supports Neo4j version 5.18.1 or greater" ) - def create_index( + def search( self, - name: str, - label: str, - property: str, - dimensions: int, - similarity_fn: str, - ) -> None: - """ - This method constructs a Cypher query and executes it - to create a new vector index in Neo4j. - - See Cypher manual on [Create node index](https://neo4j.com/docs/operations-manual/5/reference/procedures/#procedure_db_index_vector_createNodeIndex) - - Args: - name (str): The unique name of the index. - label (str): The node label to be indexed. - property (str): The property key of a node which contains embedding values. - dimensions (int): Vector embedding dimension - similarity_fn (str): case-insensitive values for the vector similarity function: - ``euclidean`` or ``cosine``. - - Raises: - ValueError: If validation of the input arguments fail. - """ - try: - VectorIndexModel( - **{ - "name": name, - "label": label, - "property": property, - "dimensions": dimensions, - "similarity_fn": similarity_fn, - } - ) - except ValidationError as e: - raise ValueError(f"Error for inputs to create_index {str(e)}") - - query = ( - f"CREATE VECTOR INDEX $name IF NOT EXISTS FOR (n:{label}) ON n.{property} OPTIONS " - "{ indexConfig: { `vector.dimensions`: toInteger($dimensions), `vector.similarity_function`: $similarity_fn } }" - ) - self.driver.execute_query( - query, - {"name": name, "dimensions": dimensions, "similarity_fn": similarity_fn}, - ) - - def drop_index(self, name: str) -> None: - """ - This method constructs a Cypher query and executes it - to drop a vector index in Neo4j. - See Cypher manual on [Drop vector indexes](https://neo4j.com/docs/cypher-manual/current/indexes-for-vector-search/#indexes-vector-drop) - - Args: - name (str): The name of the index to delete. - """ - query = "DROP INDEX $name" - parameters = { - "name": name, - } - self.driver.execute_query(query, parameters) - - def similarity_search( - self, - name: str, query_vector: Optional[List[float]] = None, query_text: Optional[str] = None, top_k: int = 5, @@ -136,7 +75,7 @@ def similarity_search( """ try: validated_data = SimilaritySearchModel( - index_name=name, + index_name=self.index_name, top_k=top_k, query_vector=query_vector, query_text=query_text, diff --git a/tests/conftest.py b/tests/conftest.py index f481cdb4..d05db4bd 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,5 +1,5 @@ import pytest -from neo4j_genai import GenAIClient +from neo4j_genai import VectorRetriever from neo4j import Driver from unittest.mock import MagicMock, patch @@ -10,6 +10,6 @@ def driver(): @pytest.fixture -@patch("neo4j_genai.GenAIClient._verify_version") -def client(_verify_version_mock, driver): - return GenAIClient(driver) +@patch("neo4j_genai.VectorRetriever._verify_version") +def retriever(_verify_version_mock, driver): + return VectorRetriever(driver, "my-index") diff --git a/tests/test_indexes.py b/tests/test_indexes.py index b431f0d4..2aa87d1f 100644 --- a/tests/test_indexes.py +++ b/tests/test_indexes.py @@ -9,7 +9,7 @@ def test_create_vector_index_happy_path(driver): create_query = ( - "CREATE VECTOR INDEX $name IF NOT EXISTS FOR (n:People) ON n.name OPTIONS " + "CREATE VECTOR INDEX $name FOR (n:People) ON n.name OPTIONS " "{ indexConfig: { `vector.dimensions`: toInteger($dimensions), `vector.similarity_function`: $similarity_fn } }" ) @@ -21,9 +21,9 @@ def test_create_vector_index_happy_path(driver): ) -def test_create_vector_index_ensure_escaping(driver, client): +def test_create_vector_index_ensure_escaping(driver): create_query = ( - "CREATE VECTOR INDEX $name IF NOT EXISTS FOR (n:People) ON n.name OPTIONS " + "CREATE VECTOR INDEX $name FOR (n:People) ON n.name OPTIONS " "{ indexConfig: { `vector.dimensions`: toInteger($dimensions), `vector.similarity_function`: $similarity_fn } }" ) @@ -97,7 +97,7 @@ def test_create_fulltext_index_empty_node_properties(driver): assert "Error for inputs to create_fulltext_index" in str(excinfo) -def test_create_fulltext_index_ensure_escaping(driver, client): +def test_create_fulltext_index_ensure_escaping(driver): label = "node-label" text_node_properties = ["property-1", "property-2"] create_query = ( diff --git a/tests/test_client.py b/tests/test_retrievers.py similarity index 69% rename from tests/test_client.py rename to tests/test_retrievers.py index 91c43395..cb8014e7 100644 --- a/tests/test_client.py +++ b/tests/test_retrievers.py @@ -1,51 +1,51 @@ import pytest -from neo4j_genai import GenAIClient -from neo4j_genai.types import Neo4jRecord from unittest.mock import patch, MagicMock +from neo4j_genai import VectorRetriever +from neo4j_genai.types import Neo4jRecord -def test_genai_client_supported_aura_version(driver): +def test_vector_retriever_supported_aura_version(driver): driver.execute_query.return_value = [[{"versions": ["5.18-aura"]}], None, None] - GenAIClient(driver=driver) + VectorRetriever(driver=driver, index_name="my-index") -def test_genai_client_no_supported_aura_version(driver): +def test_vector_retriever_no_supported_aura_version(driver): driver.execute_query.return_value = [[{"versions": ["5.3-aura"]}], None, None] with pytest.raises(ValueError) as excinfo: - GenAIClient(driver=driver) + VectorRetriever(driver=driver, index_name="my-index") assert "This package only supports Neo4j version 5.18.1 or greater" in str(excinfo) -def test_genai_client_supported_version(driver): +def test_vector_retriever_supported_version(driver): driver.execute_query.return_value = [[{"versions": ["5.19.0"]}], None, None] - GenAIClient(driver=driver) + VectorRetriever(driver=driver, index_name="my-index") -def test_genai_client_no_supported_version(driver): +def test_vector_retriever_no_supported_version(driver): driver.execute_query.return_value = [[{"versions": ["4.3.5"]}], None, None] with pytest.raises(ValueError) as excinfo: - GenAIClient(driver=driver) + VectorRetriever(driver=driver, index_name="my-index") assert "This package only supports Neo4j version 5.18.1 or greater" in str(excinfo) -@patch("neo4j_genai.GenAIClient._verify_version") +@patch("neo4j_genai.VectorRetriever._verify_version") def test_similarity_search_vector_happy_path(_verify_version_mock, driver): custom_embeddings = MagicMock() - client = GenAIClient(driver, custom_embeddings) - index_name = "my-index" dimensions = 1536 query_vector = [1.0 for _ in range(dimensions)] top_k = 5 - client.driver.execute_query.return_value = [ + retriever = VectorRetriever(driver, index_name, custom_embeddings) + + retriever.driver.execute_query.return_value = [ [{"node": "dummy-node", "score": 1.0}], None, None, @@ -55,13 +55,11 @@ def test_similarity_search_vector_happy_path(_verify_version_mock, driver): YIELD node, score """ - records = client.similarity_search( - name=index_name, query_vector=query_vector, top_k=top_k - ) + records = retriever.search(query_vector=query_vector, top_k=top_k) custom_embeddings.embed_query.assert_not_called() - client.driver.execute_query.assert_called_once_with( + retriever.driver.execute_query.assert_called_once_with( search_query, { "index_name": index_name, @@ -73,18 +71,18 @@ def test_similarity_search_vector_happy_path(_verify_version_mock, driver): assert records == [Neo4jRecord(node="dummy-node", score=1.0)] -@patch("neo4j_genai.GenAIClient._verify_version") +@patch("neo4j_genai.VectorRetriever._verify_version") def test_similarity_search_text_happy_path(_verify_version_mock, driver): embed_query_vector = [1.0 for _ in range(1536)] custom_embeddings = MagicMock() custom_embeddings.embed_query.return_value = embed_query_vector - client = GenAIClient(driver, custom_embeddings) - index_name = "my-index" query_text = "may thy knife chip and shatter" top_k = 5 + retriever = VectorRetriever(driver, index_name, custom_embeddings) + driver.execute_query.return_value = [ [{"node": "dummy-node", "score": 1.0}], None, @@ -96,9 +94,7 @@ def test_similarity_search_text_happy_path(_verify_version_mock, driver): YIELD node, score """ - records = client.similarity_search( - name=index_name, query_text=query_text, top_k=top_k - ) + records = retriever.search(query_text=query_text, top_k=top_k) custom_embeddings.embed_query.assert_called_once_with(query_text) @@ -114,17 +110,15 @@ def test_similarity_search_text_happy_path(_verify_version_mock, driver): assert records == [Neo4jRecord(node="dummy-node", score=1.0)] -def test_similarity_search_missing_embedder_for_text(client): - index_name = "my-index" +def test_similarity_search_missing_embedder_for_text(retriever): query_text = "may thy knife chip and shatter" top_k = 5 with pytest.raises(ValueError, match="Embedding method required for text query"): - client.similarity_search(name=index_name, query_text=query_text, top_k=top_k) + retriever.search(query_text=query_text, top_k=top_k) -def test_similarity_search_both_text_and_vector(client): - index_name = "my-index" +def test_similarity_search_both_text_and_vector(retriever): query_text = "may thy knife chip and shatter" query_vector = [1.1, 2.2, 3.3] top_k = 5 @@ -132,26 +126,25 @@ def test_similarity_search_both_text_and_vector(client): with pytest.raises( ValueError, match="You must provide exactly one of query_vector or query_text." ): - client.similarity_search( - name=index_name, + retriever.search( query_text=query_text, query_vector=query_vector, top_k=top_k, ) -@patch("neo4j_genai.GenAIClient._verify_version") +@patch("neo4j_genai.VectorRetriever._verify_version") def test_similarity_search_vector_bad_results(_verify_version_mock, driver): custom_embeddings = MagicMock() - client = GenAIClient(driver, custom_embeddings) - index_name = "my-index" dimensions = 1536 query_vector = [1.0 for _ in range(dimensions)] top_k = 5 - client.driver.execute_query.return_value = [ + retriever = VectorRetriever(driver, index_name, custom_embeddings) + + retriever.driver.execute_query.return_value = [ [{"node": "dummy-node", "score": "adsa"}], None, None, @@ -162,13 +155,11 @@ def test_similarity_search_vector_bad_results(_verify_version_mock, driver): """ with pytest.raises(ValueError): - client.similarity_search( - name=index_name, query_vector=query_vector, top_k=top_k - ) + retriever.search(query_vector=query_vector, top_k=top_k) custom_embeddings.embed_query.assert_not_called() - client.driver.execute_query.assert_called_once_with( + retriever.driver.execute_query.assert_called_once_with( search_query, { "index_name": index_name,