refactor: Fix spacing, remove unused config methods

Remove unused config methods so we don't have to maintain them.
Fixed spacing in test_pgvector integration test.

Refactor #COG-170
This commit is contained in:
Igor Ilic 2024-10-22 13:45:23 +02:00
parent c7ed46ddaa
commit 6b9a14270d
2 changed files with 29 additions and 48 deletions

View file

@ -39,41 +39,6 @@ class config():
cognify_config = get_cognify_config()
cognify_config.classification_model = classification_model
@staticmethod
def set_db_name(db_name: str):
cognify_config = get_relational_config()
cognify_config.db_name = db_name
@staticmethod
def set_db_path(db_path: str):
cognify_config = get_relational_config()
cognify_config.db_path = db_path
@staticmethod
def set_db_host(db_host: str):
cognify_config = get_relational_config()
cognify_config.db_host = db_host
@staticmethod
def set_db_port(db_port: str):
cognify_config = get_relational_config()
cognify_config.db_port = db_port
@staticmethod
def set_db_username(db_username: str):
cognify_config = get_relational_config()
cognify_config.db_username = db_username
@staticmethod
def set_db_password(db_password: str):
cognify_config = get_relational_config()
cognify_config.db_password = db_password
@staticmethod
def set_db_provider(db_provider: str):
cognify_config = get_relational_config()
cognify_config.db_provider = db_provider
@staticmethod
def set_summarization_model(summarization_model: object):
cognify_config = get_cognify_config()

View file

@ -1,5 +1,3 @@
import os
import logging
import pathlib
@ -8,32 +6,48 @@ from cognee.api.v1.search import SearchType
logging.basicConfig(level=logging.DEBUG)
async def main():
cognee.config.set_vector_db_config({ "vector_db_url": "",
"vector_db_key": "",
cognee.config.set_vector_db_config(
{
"vector_db_url": "",
"vector_db_key": "",
"vector_db_provider": "pgvector"
}
)
cognee.config.set_relational_db_config({"db_path": "",
cognee.config.set_relational_db_config(
{
"db_path": "",
"db_name": "cognee_db",
"db_host": "127.0.0.1",
"db_port": "5432",
"db_username": "cognee",
"db_password": "cognee",
"db_provider": "postgres"}
"db_provider": "postgres",
}
)
data_directory_path = str(pathlib.Path(os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_pgvector")).resolve())
data_directory_path = str(
pathlib.Path(
os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_pgvector")
).resolve()
)
cognee.config.data_root_directory(data_directory_path)
cognee_directory_path = str(pathlib.Path(os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_pgvector")).resolve())
cognee_directory_path = str(
pathlib.Path(
os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_pgvector")
).resolve()
)
cognee.config.system_root_directory(cognee_directory_path)
await cognee.prune.prune_data()
await cognee.prune.prune_system(metadata = True)
await cognee.prune.prune_system(metadata=True)
dataset_name = "cs_explanations"
explanation_file_path = os.path.join(pathlib.Path(__file__).parent, "test_data/Natural_language_processing.txt")
explanation_file_path = os.path.join(
pathlib.Path(__file__).parent, "test_data/Natural_language_processing.txt"
)
await cognee.add([explanation_file_path], dataset_name)
text = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
@ -49,23 +63,24 @@ async def main():
await cognee.cognify([dataset_name])
from cognee.infrastructure.databases.vector import get_vector_engine
vector_engine = get_vector_engine()
random_node = (await vector_engine.search("entities", "AI"))[0]
random_node_name = random_node.payload["name"]
search_results = await cognee.search(SearchType.INSIGHTS, query = random_node_name)
search_results = await cognee.search(SearchType.INSIGHTS, query=random_node_name)
assert len(search_results) != 0, "The search results list is empty."
print("\n\nExtracted sentences are:\n")
for result in search_results:
print(f"{result}\n")
search_results = await cognee.search(SearchType.CHUNKS, query = random_node_name)
search_results = await cognee.search(SearchType.CHUNKS, query=random_node_name)
assert len(search_results) != 0, "The search results list is empty."
print("\n\nExtracted chunks are:\n")
for result in search_results:
print(f"{result}\n")
search_results = await cognee.search(SearchType.SUMMARIES, query = random_node_name)
search_results = await cognee.search(SearchType.SUMMARIES, query=random_node_name)
assert len(search_results) != 0, "Query related summaries don't exist."
print("\n\Extracted summaries are:\n")
for result in search_results:
@ -74,4 +89,5 @@ async def main():
if __name__ == "__main__":
import asyncio
asyncio.run(main())