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Add support for supplying custom db params (#1276)

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This commit is contained in:
Deshraj Yadav
2024-02-21 16:15:57 -08:00
committed by GitHub
parent f8f69eab03
commit aa5ad625af
12 changed files with 36 additions and 32 deletions
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3
docs/components/introduction.mdx
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@@ -9,4 +9,5 @@ You can configure following components
* [Data Source](/components/data-sources/overview)
* [LLM](/components/llms)
* [Embedding Model](/components/embedding-models)
* [Vector Database](/components/vector-databases)
* [Vector Database](/components/vector-databases)
* [Evaluation](/components/evaluation)

27
embedchain/app.py
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@@ -15,7 +15,7 @@ from embedchain.cache import (Config, ExactMatchEvaluation,
gptcache_data_manager, gptcache_pre_function)
from embedchain.client import Client
from embedchain.config import AppConfig, CacheConfig, ChunkerConfig
from embedchain.core.db.database import get_session
from embedchain.core.db.database import get_session, init_db, setup_engine
from embedchain.core.db.models import DataSource
from embedchain.embedchain import EmbedChain
from embedchain.embedder.base import BaseEmbedder
@@ -86,15 +86,18 @@ class App(EmbedChain):
logging.basicConfig(level=log_level, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
self.logger = logging.getLogger(__name__)
# Initialize the metadata db for the app
setup_engine(database_uri=os.environ.get("EMBEDCHAIN_DB_URI"))
init_db()
self.auto_deploy = auto_deploy
# Store the dict config as an attribute to be able to send it
self.config_data = config_data if (config_data and validate_config(config_data)) else None
self.client = None
# pipeline_id from the backend
self.id = None
self.chunker = None
if chunker:
self.chunker = ChunkerConfig(**chunker)
self.chunker = ChunkerConfig(**chunker) if chunker else None
self.cache_config = cache_config
self.config = config or AppConfig()
@@ -321,18 +324,18 @@ class App(EmbedChain):
yaml_path: Optional[str] = None,
):
"""
Instantiate a Pipeline object from a configuration.
Instantiate a App object from a configuration.
:param config_path: Path to the YAML or JSON configuration file.
:type config_path: Optional[str]
:param config: A dictionary containing the configuration.
:type config: Optional[dict[str, Any]]
:param auto_deploy: Whether to deploy the pipeline automatically, defaults to False
:param auto_deploy: Whether to deploy the app automatically, defaults to False
:type auto_deploy: bool, optional
:param yaml_path: (Deprecated) Path to the YAML configuration file. Use config_path instead.
:type yaml_path: Optional[str]
:return: An instance of the Pipeline class.
:rtype: Pipeline
:return: An instance of the App class.
:rtype: App
"""
# Backward compatibility for yaml_path
if yaml_path and not config_path:
@@ -366,7 +369,7 @@ class App(EmbedChain):
raise Exception(f"Error occurred while validating the config. Error: {str(e)}")
app_config_data = config_data.get("app", {}).get("config", {})
db_config_data = config_data.get("vectordb", {})
vector_db_config_data = config_data.get("vectordb", {})
embedding_model_config_data = config_data.get("embedding_model", config_data.get("embedder", {}))
llm_config_data = config_data.get("llm", {})
chunker_config_data = config_data.get("chunker", {})
@@ -374,8 +377,8 @@ class App(EmbedChain):
app_config = AppConfig(**app_config_data)
db_provider = db_config_data.get("provider", "chroma")
db = VectorDBFactory.create(db_provider, db_config_data.get("config", {}))
vector_db_provider = vector_db_config_data.get("provider", "chroma")
vector_db = VectorDBFactory.create(vector_db_provider, vector_db_config_data.get("config", {}))
if llm_config_data:
llm_provider = llm_config_data.get("provider", "openai")
@@ -396,7 +399,7 @@ class App(EmbedChain):
return cls(
config=app_config,
llm=llm,
db=db,
db=vector_db,
embedding_model=embedding_model,
config_data=config_data,
auto_deploy=auto_deploy,

5
embedchain/client.py
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@@ -5,8 +5,7 @@ import uuid
import requests
from embedchain.constants import CONFIG_DIR, CONFIG_FILE, DB_URI
from embedchain.core.db.database import init_db, setup_engine
from embedchain.constants import CONFIG_DIR, CONFIG_FILE
class Client:
@@ -41,8 +40,6 @@ class Client:
:rtype: str
"""
os.makedirs(CONFIG_DIR, exist_ok=True)
setup_engine(database_uri=DB_URI)
init_db()
if os.path.exists(CONFIG_FILE):
with open(CONFIG_FILE, "r") as f:

1
embedchain/config/base_app_config.py
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@@ -61,4 +61,3 @@ class BaseAppConfig(BaseConfig, JSONSerializable):
logging.basicConfig(format="%(asctime)s [%(name)s] [%(levelname)s] %(message)s", level=level)
self.logger = logging.getLogger(__name__)
return

4
embedchain/constants.py
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@@ -6,4 +6,6 @@ HOME_DIR = str(Path.home())
CONFIG_DIR = os.path.join(HOME_DIR, ".embedchain")
CONFIG_FILE = os.path.join(CONFIG_DIR, "config.json")
SQLITE_PATH = os.path.join(CONFIG_DIR, "embedchain.db")
DB_URI = f"sqlite:///{SQLITE_PATH}"
# Set the environment variable for the database URI
os.environ.setdefault("EMBEDCHAIN_DB_URI", f"sqlite:///{SQLITE_PATH}")

6
embedchain/core/db/database.py
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@@ -11,8 +11,8 @@ from .models import Base
class DatabaseManager:
def __init__(self, database_uri: str = "sqlite:///embedchain.db", echo: bool = False):
self.database_uri = database_uri
def __init__(self, echo: bool = False):
self.database_uri = os.environ.get("EMBEDCHAIN_DB_URI")
self.echo = echo
self.engine: Engine = None
self._session_factory = None
@@ -58,7 +58,7 @@ database_manager = DatabaseManager()
# Convenience functions for backward compatibility and ease of use
def setup_engine(database_uri: str = "sqlite:///embedchain.db", echo: bool = False) -> None:
def setup_engine(database_uri: str, echo: bool = False) -> None:
database_manager.database_uri = database_uri
database_manager.echo = echo
database_manager.setup_engine()

8
embedchain/embedchain.py
View File

@@ -6,9 +6,7 @@ from typing import Any, Optional, Union
from dotenv import load_dotenv
from langchain.docstore.document import Document
from embedchain.cache import (adapt, get_gptcache_session,
gptcache_data_convert,
gptcache_update_cache_callback)
from embedchain.cache import adapt, get_gptcache_session, gptcache_data_convert, gptcache_update_cache_callback
from embedchain.chunkers.base_chunker import BaseChunker
from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig
from embedchain.config.base_app_config import BaseAppConfig
@@ -18,8 +16,7 @@ from embedchain.embedder.base import BaseEmbedder
from embedchain.helpers.json_serializable import JSONSerializable
from embedchain.llm.base import BaseLlm
from embedchain.loaders.base_loader import BaseLoader
from embedchain.models.data_type import (DataType, DirectDataType,
IndirectDataType, SpecialDataType)
from embedchain.models.data_type import DataType, DirectDataType, IndirectDataType, SpecialDataType
from embedchain.utils.misc import detect_datatype, is_valid_json_string
from embedchain.vectordb.base import BaseVectorDB
@@ -51,7 +48,6 @@ class EmbedChain(JSONSerializable):
:type system_prompt: Optional[str], optional
:raises ValueError: No database or embedder provided.
"""
self.config = config
self.cache_config = None
# Llm

4
embedchain/migrations/env.py
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@@ -1,9 +1,9 @@
import os
from logging.config import fileConfig
from alembic import context
from sqlalchemy import engine_from_config, pool
from embedchain.constants import DB_URI
from embedchain.core.db.models import Base
# this is the Alembic Config object, which provides
@@ -21,7 +21,7 @@ target_metadata = Base.metadata
# can be acquired:
# my_important_option = config.get_main_option("my_important_option")
# ... etc.
config.set_main_option("sqlalchemy.url", DB_URI)
config.set_main_option("sqlalchemy.url", os.environ.get("EMBEDCHAIN_DB_URI"))
def run_migrations_offline() -> None:

1
embedchain/utils/misc.py
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@@ -405,6 +405,7 @@ def validate_config(config_data):
"google",
"aws_bedrock",
"mistralai",
"vllm",
),
Optional("config"): {
Optional("model"): str,

2
pyproject.toml
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@@ -1,6 +1,6 @@
[tool.poetry]
name = "embedchain"
version = "0.1.82"
version = "0.1.83"
description = "Simplest open source retrieval(RAG) framework"
authors = [
"Taranjeet Singh <taranjeet@embedchain.ai>",

6
tests/telemetry/test_posthog.py
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@@ -1,6 +1,8 @@
import logging
import os
import pytest
from embedchain.telemetry.posthog import AnonymousTelemetry
@@ -16,7 +18,7 @@ class TestAnonymousTelemetry:
assert telemetry.user_id
mock_posthog.assert_called_once_with(project_api_key=telemetry.project_api_key, host=telemetry.host)
def test_init_with_disabled_telemetry(self, mocker, monkeypatch):
def test_init_with_disabled_telemetry(self, mocker):
mocker.patch("embedchain.telemetry.posthog.Posthog")
telemetry = AnonymousTelemetry()
assert telemetry.enabled is False
@@ -52,7 +54,9 @@ class TestAnonymousTelemetry:
properties,
)
@pytest.mark.skip(reason="Logging setup needs to be fixed to make this test to work")
def test_capture_with_exception(self, mocker, caplog):
os.environ["EC_TELEMETRY"] = "true"
mock_posthog = mocker.patch("embedchain.telemetry.posthog.Posthog")
mock_posthog.return_value.capture.side_effect = Exception("Test Exception")
telemetry = AnonymousTelemetry()

1
tests/vectordb/test_chroma_db.py
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@@ -84,6 +84,7 @@ def test_app_init_with_host_and_port_none(mock_client):
assert called_settings.chroma_server_http_port is None
@pytest.mark.skip(reason="Logging setup needs to be fixed to make this test to work")
def test_chroma_db_duplicates_throw_warning(caplog):
db = ChromaDB(config=ChromaDbConfig(allow_reset=True, dir="test-db"))
app = App(config=AppConfig(collect_metrics=False), db=db)