[Feature] Add support to use any sql database as the metadata storage for embedchain apps (#1273)

This commit is contained in:
Deshraj Yadav
2024-02-19 13:04:18 -08:00
committed by GitHub
parent 6c12bc9044
commit 5e2e7fb639
20 changed files with 601 additions and 202 deletions

1
.gitignore vendored
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@@ -165,6 +165,7 @@ cython_debug/
# Database
db
test-db
!embedchain/core/db/
.vscode
.idea/

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@@ -7,4 +7,4 @@ from embedchain.client import Client # noqa: F401
from embedchain.pipeline import Pipeline # noqa: F401
# Setup the user directory if doesn't exist already
Client.setup_dir()
Client.setup()

116
embedchain/alembic.ini Normal file
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@@ -0,0 +1,116 @@
# A generic, single database configuration.
[alembic]
# path to migration scripts
script_location = embedchain/migrations
# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
# Uncomment the line below if you want the files to be prepended with date and time
# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
# for all available tokens
# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
# sys.path path, will be prepended to sys.path if present.
# defaults to the current working directory.
prepend_sys_path = .
# timezone to use when rendering the date within the migration file
# as well as the filename.
# If specified, requires the python>=3.9 or backports.zoneinfo library.
# Any required deps can installed by adding `alembic[tz]` to the pip requirements
# string value is passed to ZoneInfo()
# leave blank for localtime
# timezone =
# max length of characters to apply to the
# "slug" field
# truncate_slug_length = 40
# set to 'true' to run the environment during
# the 'revision' command, regardless of autogenerate
# revision_environment = false
# set to 'true' to allow .pyc and .pyo files without
# a source .py file to be detected as revisions in the
# versions/ directory
# sourceless = false
# version location specification; This defaults
# to alembic/versions. When using multiple version
# directories, initial revisions must be specified with --version-path.
# The path separator used here should be the separator specified by "version_path_separator" below.
# version_locations = %(here)s/bar:%(here)s/bat:alembic/versions
# version path separator; As mentioned above, this is the character used to split
# version_locations. The default within new alembic.ini files is "os", which uses os.pathsep.
# If this key is omitted entirely, it falls back to the legacy behavior of splitting on spaces and/or commas.
# Valid values for version_path_separator are:
#
# version_path_separator = :
# version_path_separator = ;
# version_path_separator = space
version_path_separator = os # Use os.pathsep. Default configuration used for new projects.
# set to 'true' to search source files recursively
# in each "version_locations" directory
# new in Alembic version 1.10
# recursive_version_locations = false
# the output encoding used when revision files
# are written from script.py.mako
# output_encoding = utf-8
sqlalchemy.url = driver://user:pass@localhost/dbname
[post_write_hooks]
# post_write_hooks defines scripts or Python functions that are run
# on newly generated revision scripts. See the documentation for further
# detail and examples
# format using "black" - use the console_scripts runner, against the "black" entrypoint
# hooks = black
# black.type = console_scripts
# black.entrypoint = black
# black.options = -l 79 REVISION_SCRIPT_FILENAME
# lint with attempts to fix using "ruff" - use the exec runner, execute a binary
# hooks = ruff
# ruff.type = exec
# ruff.executable = %(here)s/.venv/bin/ruff
# ruff.options = --fix REVISION_SCRIPT_FILENAME
# Logging configuration
[loggers]
keys = root,sqlalchemy,alembic
[handlers]
keys = console
[formatters]
keys = generic
[logger_root]
level = WARN
handlers = console
qualname =
[logger_sqlalchemy]
level = WARN
handlers =
qualname = sqlalchemy.engine
[logger_alembic]
level = WARN
handlers =
qualname = alembic
[handler_console]
class = StreamHandler
args = (sys.stderr,)
level = NOTSET
formatter = generic
[formatter_generic]
format = %(levelname)-5.5s [%(name)s] %(message)s
datefmt = %H:%M:%S

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@@ -3,7 +3,6 @@ import concurrent.futures
import json
import logging
import os
import sqlite3
import uuid
from typing import Any, Optional, Union
@@ -16,7 +15,8 @@ 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.constants import SQLITE_PATH
from embedchain.core.db.database import get_session
from embedchain.core.db.models import DataSource
from embedchain.embedchain import EmbedChain
from embedchain.embedder.base import BaseEmbedder
from embedchain.embedder.openai import OpenAIEmbedder
@@ -33,9 +33,6 @@ from embedchain.utils.misc import validate_config
from embedchain.vectordb.base import BaseVectorDB
from embedchain.vectordb.chroma import ChromaDB
# Set up the user directory if it doesn't exist already
Client.setup_dir()
@register_deserializable
class App(EmbedChain):
@@ -120,6 +117,9 @@ class App(EmbedChain):
self.llm = llm or OpenAILlm()
self._init_db()
# Session for the metadata db
self.db_session = get_session()
# If cache_config is provided, initializing the cache ...
if self.cache_config is not None:
self._init_cache()
@@ -127,27 +127,6 @@ class App(EmbedChain):
# Send anonymous telemetry
self._telemetry_props = {"class": self.__class__.__name__}
self.telemetry = AnonymousTelemetry(enabled=self.config.collect_metrics)
# Establish a connection to the SQLite database
self.connection = sqlite3.connect(SQLITE_PATH, check_same_thread=False)
self.cursor = self.connection.cursor()
# Create the 'data_sources' table if it doesn't exist
self.cursor.execute(
"""
CREATE TABLE IF NOT EXISTS data_sources (
pipeline_id TEXT,
hash TEXT,
type TEXT,
value TEXT,
metadata TEXT,
is_uploaded INTEGER DEFAULT 0,
PRIMARY KEY (pipeline_id, hash)
)
"""
)
self.connection.commit()
# Send anonymous telemetry
self.telemetry.capture(event_name="init", properties=self._telemetry_props)
self.user_asks = []
@@ -307,20 +286,14 @@ class App(EmbedChain):
return False
def _mark_data_as_uploaded(self, data_hash):
self.cursor.execute(
"UPDATE data_sources SET is_uploaded = 1 WHERE hash = ? AND pipeline_id = ?",
(data_hash, self.local_id),
)
self.connection.commit()
self.db_session.query(DataSource).filter_by(hash=data_hash, app_id=self.local_id).update({"is_uploaded": 1})
def get_data_sources(self):
db_data = self.cursor.execute("SELECT * FROM data_sources WHERE pipeline_id = ?", (self.local_id,)).fetchall()
data_sources = []
for data in db_data:
data_sources.append({"data_type": data[2], "data_value": data[3], "metadata": data[4]})
return data_sources
data_sources = self.db_session.query(DataSource).filter_by(app_id=self.local_id).all()
results = []
for row in data_sources:
results.append({"data_type": row.data_type, "data_value": row.data_value, "metadata": row.metadata})
return results
def deploy(self):
if self.client is None:
@@ -329,14 +302,11 @@ class App(EmbedChain):
pipeline_data = self._create_pipeline()
self.id = pipeline_data["id"]
results = self.cursor.execute(
"SELECT * FROM data_sources WHERE pipeline_id = ? AND is_uploaded = 0", (self.local_id,) # noqa:E501
).fetchall()
results = self.db_session.query(DataSource).filter_by(app_id=self.local_id, is_uploaded=0).all()
if len(results) > 0:
print("🛠️ Adding data to your pipeline...")
for result in results:
data_hash, data_type, data_value = result[1], result[2], result[3]
data_hash, data_type, data_value = result.hash, result.data_type, result.data_value
self._process_and_upload_data(data_hash, data_type, data_value)
# Send anonymous telemetry
@@ -423,10 +393,6 @@ class App(EmbedChain):
else:
cache_config = None
# Send anonymous telemetry
event_properties = {"init_type": "config_data"}
AnonymousTelemetry().capture(event_name="init", properties=event_properties)
return cls(
config=app_config,
llm=llm,

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@@ -5,7 +5,8 @@ import uuid
import requests
from embedchain.constants import CONFIG_DIR, CONFIG_FILE
from embedchain.constants import CONFIG_DIR, CONFIG_FILE, DB_URI
from embedchain.core.db.database import init_db, setup_engine
class Client:
@@ -31,7 +32,7 @@ class Client:
)
@classmethod
def setup_dir(cls):
def setup(cls):
"""
Loads the user id from the config file if it exists, otherwise generates a new
one and saves it to the config file.
@@ -40,6 +41,9 @@ 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:
data = json.load(f)
@@ -53,7 +57,7 @@ class Client:
@classmethod
def load_config(cls):
if not os.path.exists(CONFIG_FILE):
cls.setup_dir()
cls.setup()
with open(CONFIG_FILE, "r") as config_file:
return json.load(config_file)

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@@ -6,3 +6,4 @@ 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}"

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@@ -0,0 +1,83 @@
import os
from alembic import command
from alembic.config import Config
from sqlalchemy import create_engine
from sqlalchemy.engine.base import Engine
from sqlalchemy.orm import Session as SQLAlchemySession
from sqlalchemy.orm import scoped_session, sessionmaker
from .models import Base
class DatabaseManager:
def __init__(self, database_uri: str = "sqlite:///embedchain.db", echo: bool = False):
self.database_uri = database_uri
self.echo = echo
self.engine: Engine = None
self._session_factory = None
def setup_engine(self) -> None:
"""Initializes the database engine and session factory."""
self.engine = create_engine(self.database_uri, echo=self.echo, connect_args={"check_same_thread": False})
self._session_factory = scoped_session(sessionmaker(bind=self.engine))
Base.metadata.bind = self.engine
def init_db(self) -> None:
"""Creates all tables defined in the Base metadata."""
if not self.engine:
raise RuntimeError("Database engine is not initialized. Call setup_engine() first.")
Base.metadata.create_all(self.engine)
def get_session(self) -> SQLAlchemySession:
"""Provides a session for database operations."""
if not self._session_factory:
raise RuntimeError("Session factory is not initialized. Call setup_engine() first.")
return self._session_factory()
def close_session(self) -> None:
"""Closes the current session."""
if self._session_factory:
self._session_factory.remove()
def execute_transaction(self, transaction_block):
"""Executes a block of code within a database transaction."""
session = self.get_session()
try:
transaction_block(session)
session.commit()
except Exception as e:
session.rollback()
raise e
finally:
self.close_session()
# Singleton pattern to use throughout the application
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:
database_manager.database_uri = database_uri
database_manager.echo = echo
database_manager.setup_engine()
def alembic_upgrade() -> None:
"""Upgrades the database to the latest version."""
alembic_config_path = os.path.join(os.path.dirname(__file__), "..", "..", "alembic.ini")
alembic_cfg = Config(alembic_config_path)
command.upgrade(alembic_cfg, "head")
def init_db() -> None:
alembic_upgrade()
def get_session() -> SQLAlchemySession:
return database_manager.get_session()
def execute_transaction(transaction_block):
database_manager.execute_transaction(transaction_block)

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@@ -0,0 +1,31 @@
import uuid
from sqlalchemy import TIMESTAMP, Column, Integer, String, Text, func
from sqlalchemy.orm import declarative_base
Base = declarative_base()
metadata = Base.metadata
class DataSource(Base):
__tablename__ = "ec_data_sources"
id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
app_id = Column(Text, index=True)
hash = Column(Text, index=True)
type = Column(Text, index=True)
value = Column(Text)
meta_data = Column(Text, name="metadata")
is_uploaded = Column(Integer, default=0)
class ChatHistory(Base):
__tablename__ = "ec_chat_history"
app_id = Column(String, primary_key=True)
id = Column(String, primary_key=True)
session_id = Column(String, primary_key=True, index=True)
question = Column(Text)
answer = Column(Text)
meta_data = Column(Text, name="metadata")
created_at = Column(TIMESTAMP, default=func.current_timestamp(), index=True)

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@@ -1,7 +1,6 @@
import hashlib
import json
import logging
import sqlite3
from typing import Any, Optional, Union
from dotenv import load_dotenv
@@ -13,7 +12,7 @@ from embedchain.cache import (adapt, get_gptcache_session,
from embedchain.chunkers.base_chunker import BaseChunker
from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig
from embedchain.config.base_app_config import BaseAppConfig
from embedchain.constants import SQLITE_PATH
from embedchain.core.db.models import DataSource
from embedchain.data_formatter import DataFormatter
from embedchain.embedder.base import BaseEmbedder
from embedchain.helpers.json_serializable import JSONSerializable
@@ -21,7 +20,6 @@ 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.telemetry.posthog import AnonymousTelemetry
from embedchain.utils.misc import detect_datatype, is_valid_json_string
from embedchain.vectordb.base import BaseVectorDB
@@ -85,30 +83,6 @@ class EmbedChain(JSONSerializable):
self.user_asks = []
self.chunker: Optional[ChunkerConfig] = None
# Send anonymous telemetry
self._telemetry_props = {"class": self.__class__.__name__}
self.telemetry = AnonymousTelemetry(enabled=self.config.collect_metrics)
# Establish a connection to the SQLite database
self.connection = sqlite3.connect(SQLITE_PATH, check_same_thread=False)
self.cursor = self.connection.cursor()
# Create the 'data_sources' table if it doesn't exist
self.cursor.execute(
"""
CREATE TABLE IF NOT EXISTS data_sources (
pipeline_id TEXT,
hash TEXT,
type TEXT,
value TEXT,
metadata TEXT,
is_uploaded INTEGER DEFAULT 0,
PRIMARY KEY (pipeline_id, hash)
)
"""
)
self.connection.commit()
# Send anonymous telemetry
self.telemetry.capture(event_name="init", properties=self._telemetry_props)
@property
def collect_metrics(self):
@@ -204,17 +178,21 @@ class EmbedChain(JSONSerializable):
if data_type in {DataType.DOCS_SITE}:
self.is_docs_site_instance = True
# Insert the data into the 'data' table
self.cursor.execute(
"""
INSERT OR REPLACE INTO data_sources (hash, pipeline_id, type, value, metadata)
VALUES (?, ?, ?, ?, ?)
""",
(source_hash, self.config.id, data_type.value, str(source), json.dumps(metadata)),
# Insert the data into the 'ec_data_sources' table
self.db_session.add(
DataSource(
hash=source_hash,
app_id=self.config.id,
type=data_type.value,
value=source,
metadata=json.dumps(metadata),
)
)
# Commit the transaction
self.connection.commit()
try:
self.db_session.commit()
except Exception as e:
logging.error(f"Error adding data source: {e}")
self.db_session.rollback()
if dry_run:
data_chunks_info = {"chunks": documents, "metadata": metadatas, "count": len(documents), "type": data_type}
@@ -666,9 +644,14 @@ class EmbedChain(JSONSerializable):
Resets the database. Deletes all embeddings irreversibly.
`App` does not have to be reinitialized after using this method.
"""
try:
self.db_session.query(DataSource).filter_by(app_id=self.config.id).delete()
self.db_session.commit()
except Exception as e:
logging.error(f"Error deleting chat history: {e}")
self.db_session.rollback()
return None
self.db.reset()
self.cursor.execute("DELETE FROM data_sources WHERE pipeline_id = ?", (self.config.id,))
self.connection.commit()
self.delete_all_chat_history(app_id=self.config.id)
# Send anonymous telemetry
self.telemetry.capture(event_name="reset", properties=self._telemetry_props)

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@@ -1,55 +1,40 @@
import json
import logging
import sqlite3
import uuid
from typing import Any, Optional
from embedchain.constants import SQLITE_PATH
from embedchain.core.db.database import get_session
from embedchain.core.db.models import ChatHistory as ChatHistoryModel
from embedchain.memory.message import ChatMessage
from embedchain.memory.utils import merge_metadata_dict
CHAT_MESSAGE_CREATE_TABLE_QUERY = """
CREATE TABLE IF NOT EXISTS ec_chat_history (
app_id TEXT,
id TEXT,
session_id TEXT,
question TEXT,
answer TEXT,
metadata TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id, app_id, session_id)
)
"""
class ChatHistory:
def __init__(self) -> None:
with sqlite3.connect(SQLITE_PATH, check_same_thread=False) as self.connection:
self.cursor = self.connection.cursor()
self.cursor.execute(CHAT_MESSAGE_CREATE_TABLE_QUERY)
self.connection.commit()
self.db_session = get_session()
def add(self, app_id, session_id, chat_message: ChatMessage) -> Optional[str]:
memory_id = str(uuid.uuid4())
metadata_dict = merge_metadata_dict(chat_message.human_message.metadata, chat_message.ai_message.metadata)
if metadata_dict:
metadata = self._serialize_json(metadata_dict)
ADD_CHAT_MESSAGE_QUERY = """
INSERT INTO ec_chat_history (app_id, id, session_id, question, answer, metadata)
VALUES (?, ?, ?, ?, ?, ?)
"""
self.cursor.execute(
ADD_CHAT_MESSAGE_QUERY,
(
app_id,
memory_id,
session_id,
chat_message.human_message.content,
chat_message.ai_message.content,
metadata if metadata_dict else "{}",
),
self.db_session.add(
ChatHistoryModel(
app_id=app_id,
id=memory_id,
session_id=session_id,
question=chat_message.human_message.content,
answer=chat_message.ai_message.content,
metadata=metadata if metadata_dict else "{}",
)
)
self.connection.commit()
try:
self.db_session.commit()
except Exception as e:
logging.error(f"Error adding chat memory to db: {e}")
self.db_session.rollback()
return None
logging.info(f"Added chat memory to db with id: {memory_id}")
return memory_id
@@ -63,15 +48,15 @@ class ChatHistory:
:return: None
"""
params = {"app_id": app_id}
if session_id:
DELETE_CHAT_HISTORY_QUERY = "DELETE FROM ec_chat_history WHERE app_id=? AND session_id=?"
params = (app_id, session_id)
else:
DELETE_CHAT_HISTORY_QUERY = "DELETE FROM ec_chat_history WHERE app_id=?"
params = (app_id,)
self.cursor.execute(DELETE_CHAT_HISTORY_QUERY, params)
self.connection.commit()
params["session_id"] = session_id
self.db_session.query(ChatHistoryModel).filter_by(**params).delete()
try:
self.db_session.commit()
except Exception as e:
logging.error(f"Error deleting chat history: {e}")
self.db_session.rollback()
def get(
self, app_id, session_id: str = "default", num_rounds=10, fetch_all: bool = False, display_format=False
@@ -85,50 +70,31 @@ class ChatHistory:
param: fetch_all (optional) - Whether to fetch all chat history or not. Defaults to False
param: display_format (optional) - Whether to return the chat history in display format. Defaults to False
"""
base_query = """
SELECT * FROM ec_chat_history
WHERE app_id=?
"""
if fetch_all:
additional_query = "ORDER BY created_at ASC"
params = (app_id,)
else:
additional_query = """
AND session_id=?
ORDER BY created_at ASC
LIMIT ?
"""
params = (app_id, session_id, num_rounds)
QUERY = base_query + additional_query
self.cursor.execute(
QUERY,
params,
params = {"app_id": app_id}
if not fetch_all:
params["session_id"] = session_id
results = (
self.db_session.query(ChatHistoryModel).filter_by(**params).order_by(ChatHistoryModel.created_at.asc())
)
results = self.cursor.fetchall()
results = results.limit(num_rounds) if not fetch_all else results
history = []
for result in results:
app_id, _, session_id, question, answer, metadata, timestamp = result
metadata = self._deserialize_json(metadata=metadata)
metadata = self._deserialize_json(metadata=result.meta_data or "{}")
# Return list of dict if display_format is True
if display_format:
history.append(
{
"session_id": session_id,
"human": question,
"ai": answer,
"metadata": metadata,
"timestamp": timestamp,
"session_id": result.session_id,
"human": result.question,
"ai": result.answer,
"metadata": result.meta_data,
"timestamp": result.created_at,
}
)
else:
memory = ChatMessage()
memory.add_user_message(question, metadata=metadata)
memory.add_ai_message(answer, metadata=metadata)
memory.add_user_message(result.question, metadata=metadata)
memory.add_ai_message(result.answer, metadata=metadata)
history.append(memory)
return history
@@ -141,16 +107,11 @@ class ChatHistory:
:return: The number of chat messages for a given app_id and session_id
"""
# Rewrite the logic below with sqlalchemy
params = {"app_id": app_id}
if session_id:
QUERY = "SELECT COUNT(*) FROM ec_chat_history WHERE app_id=? AND session_id=?"
params = (app_id, session_id)
else:
QUERY = "SELECT COUNT(*) FROM ec_chat_history WHERE app_id=?"
params = (app_id,)
self.cursor.execute(QUERY, params)
count = self.cursor.fetchone()[0]
return count
params["session_id"] = session_id
return self.db_session.query(ChatHistoryModel).filter_by(**params).count()
@staticmethod
def _serialize_json(metadata: dict[str, Any]):

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@@ -0,0 +1,74 @@
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
# access to the values within the .ini file in use.
config = context.config
# Interpret the config file for Python logging.
# This line sets up loggers basically.
if config.config_file_name is not None:
fileConfig(config.config_file_name)
target_metadata = Base.metadata
# other values from the config, defined by the needs of env.py,
# can be acquired:
# my_important_option = config.get_main_option("my_important_option")
# ... etc.
config.set_main_option("sqlalchemy.url", DB_URI)
def run_migrations_offline() -> None:
"""Run migrations in 'offline' mode.
This configures the context with just a URL
and not an Engine, though an Engine is acceptable
here as well. By skipping the Engine creation
we don't even need a DBAPI to be available.
Calls to context.execute() here emit the given string to the
script output.
"""
url = config.get_main_option("sqlalchemy.url")
context.configure(
url=url,
target_metadata=target_metadata,
literal_binds=True,
dialect_opts={"paramstyle": "named"},
)
with context.begin_transaction():
context.run_migrations()
def run_migrations_online() -> None:
"""Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
"""
connectable = engine_from_config(
config.get_section(config.config_ini_section, {}),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
with connectable.connect() as connection:
context.configure(connection=connection, target_metadata=target_metadata)
with context.begin_transaction():
context.run_migrations()
if context.is_offline_mode():
run_migrations_offline()
else:
run_migrations_online()

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@@ -0,0 +1,26 @@
"""${message}
Revision ID: ${up_revision}
Revises: ${down_revision | comma,n}
Create Date: ${create_date}
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
${imports if imports else ""}
# revision identifiers, used by Alembic.
revision: str = ${repr(up_revision)}
down_revision: Union[str, None] = ${repr(down_revision)}
branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
def upgrade() -> None:
${upgrades if upgrades else "pass"}
def downgrade() -> None:
${downgrades if downgrades else "pass"}

View File

@@ -0,0 +1,62 @@
"""Create initial migrations
Revision ID: 40a327b3debd
Revises:
Create Date: 2024-02-18 15:29:19.409064
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "40a327b3debd"
down_revision: Union[str, None] = None
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
op.create_table(
"ec_chat_history",
sa.Column("app_id", sa.String(), nullable=False),
sa.Column("id", sa.String(), nullable=False),
sa.Column("session_id", sa.String(), nullable=False),
sa.Column("question", sa.Text(), nullable=True),
sa.Column("answer", sa.Text(), nullable=True),
sa.Column("metadata", sa.Text(), nullable=True),
sa.Column("created_at", sa.TIMESTAMP(), nullable=True),
sa.PrimaryKeyConstraint("app_id", "id", "session_id"),
)
op.create_index(op.f("ix_ec_chat_history_created_at"), "ec_chat_history", ["created_at"], unique=False)
op.create_index(op.f("ix_ec_chat_history_session_id"), "ec_chat_history", ["session_id"], unique=False)
op.create_table(
"ec_data_sources",
sa.Column("id", sa.String(), nullable=False),
sa.Column("app_id", sa.Text(), nullable=True),
sa.Column("hash", sa.Text(), nullable=True),
sa.Column("type", sa.Text(), nullable=True),
sa.Column("value", sa.Text(), nullable=True),
sa.Column("metadata", sa.Text(), nullable=True),
sa.Column("is_uploaded", sa.Integer(), nullable=True),
sa.PrimaryKeyConstraint("id"),
)
op.create_index(op.f("ix_ec_data_sources_hash"), "ec_data_sources", ["hash"], unique=False)
op.create_index(op.f("ix_ec_data_sources_app_id"), "ec_data_sources", ["app_id"], unique=False)
op.create_index(op.f("ix_ec_data_sources_type"), "ec_data_sources", ["type"], unique=False)
# ### end Alembic commands ###
def downgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
op.drop_index(op.f("ix_ec_data_sources_type"), table_name="ec_data_sources")
op.drop_index(op.f("ix_ec_data_sources_app_id"), table_name="ec_data_sources")
op.drop_index(op.f("ix_ec_data_sources_hash"), table_name="ec_data_sources")
op.drop_table("ec_data_sources")
op.drop_index(op.f("ix_ec_chat_history_session_id"), table_name="ec_chat_history")
op.drop_index(op.f("ix_ec_chat_history_created_at"), table_name="ec_chat_history")
op.drop_table("ec_chat_history")
# ### end Alembic commands ###

View File

@@ -20,7 +20,7 @@ from embedchain.utils.misc import detect_datatype
logging.basicConfig(level=logging.WARN)
# Set up the user directory if it doesn't exist already
Client.setup_dir()
Client.setup()
class OpenAIAssistant:

110
poetry.lock generated
View File

@@ -161,6 +161,25 @@ files = [
[package.dependencies]
typing-extensions = "*"
[[package]]
name = "alembic"
version = "1.13.1"
description = "A database migration tool for SQLAlchemy."
optional = false
python-versions = ">=3.8"
files = [
{file = "alembic-1.13.1-py3-none-any.whl", hash = "sha256:2edcc97bed0bd3272611ce3a98d98279e9c209e7186e43e75bbb1b2bdfdbcc43"},
{file = "alembic-1.13.1.tar.gz", hash = "sha256:4932c8558bf68f2ee92b9bbcb8218671c627064d5b08939437af6d77dc05e595"},
]
[package.dependencies]
Mako = "*"
SQLAlchemy = ">=1.3.0"
typing-extensions = ">=4"
[package.extras]
tz = ["backports.zoneinfo"]
[[package]]
name = "annotated-types"
version = "0.6.0"
@@ -3334,6 +3353,25 @@ html5 = ["html5lib"]
htmlsoup = ["BeautifulSoup4"]
source = ["Cython (>=0.29.35)"]
[[package]]
name = "mako"
version = "1.3.2"
description = "A super-fast templating language that borrows the best ideas from the existing templating languages."
optional = false
python-versions = ">=3.8"
files = [
{file = "Mako-1.3.2-py3-none-any.whl", hash = "sha256:32a99d70754dfce237019d17ffe4a282d2d3351b9c476e90d8a60e63f133b80c"},
{file = "Mako-1.3.2.tar.gz", hash = "sha256:2a0c8ad7f6274271b3bb7467dd37cf9cc6dab4bc19cb69a4ef10669402de698e"},
]
[package.dependencies]
MarkupSafe = ">=0.9.2"
[package.extras]
babel = ["Babel"]
lingua = ["lingua"]
testing = ["pytest"]
[[package]]
name = "markdown"
version = "3.5"
@@ -3380,7 +3418,7 @@ testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
name = "markupsafe"
version = "2.1.3"
description = "Safely add untrusted strings to HTML/XML markup."
optional = true
optional = false
python-versions = ">=3.7"
files = [
{file = "MarkupSafe-2.1.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cd0f502fe016460680cd20aaa5a76d241d6f35a1c3350c474bac1273803893fa"},
@@ -6701,28 +6739,70 @@ files = [
[[package]]
name = "sqlalchemy"
version = "2.0.22"
version = "2.0.27"
description = "Database Abstraction Library"
optional = false
python-versions = ">=3.7"
files = [
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{file = "SQLAlchemy-2.0.22-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f776c2c30f0e5f4db45c3ee11a5f2a8d9de68e81eb73ec4237de1e32e04ae81c"},
{file = "SQLAlchemy-2.0.22-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:2c9bac865ee06d27a1533471405ad240a6f5d83195eca481f9fc4a71d8b87df8"},
{file = "SQLAlchemy-2.0.22-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:625b72d77ac8ac23da3b1622e2da88c4aedaee14df47c8432bf8f6495e655de2"},
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{file = "SQLAlchemy-2.0.22-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:3aa1472bf44f61dd27987cd051f1c893b7d3b17238bff8c23fceaef4f1133868"},
{file = "SQLAlchemy-2.0.22-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:56a7e2bb639df9263bf6418231bc2a92a773f57886d371ddb7a869a24919face"},
{file = "SQLAlchemy-2.0.22.tar.gz", hash = "sha256:5434cc601aa17570d79e5377f5fd45ff92f9379e2abed0be5e8c2fba8d353d2b"},
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{file = "SQLAlchemy-2.0.27.tar.gz", hash = "sha256:86a6ed69a71fe6b88bf9331594fa390a2adda4a49b5c06f98e47bf0d392534f8"},
]
[package.dependencies]
greenlet = {version = "!=0.4.17", markers = "platform_machine == \"win32\" or platform_machine == \"WIN32\" or platform_machine == \"AMD64\" or platform_machine == \"amd64\" or platform_machine == \"x86_64\" or platform_machine == \"ppc64le\" or platform_machine == \"aarch64\""}
typing-extensions = ">=4.2.0"
typing-extensions = ">=4.6.0"
[package.extras]
aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
asyncio = ["greenlet (!=0.4.17)"]
asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
@@ -6732,7 +6812,7 @@ mssql-pyodbc = ["pyodbc"]
mypy = ["mypy (>=0.910)"]
mysql = ["mysqlclient (>=1.4.0)"]
mysql-connector = ["mysql-connector-python"]
oracle = ["cx-oracle (>=7)"]
oracle = ["cx_oracle (>=8)"]
oracle-oracledb = ["oracledb (>=1.0.1)"]
postgresql = ["psycopg2 (>=2.7)"]
postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
@@ -6742,7 +6822,7 @@ postgresql-psycopg2binary = ["psycopg2-binary"]
postgresql-psycopg2cffi = ["psycopg2cffi"]
postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
pymysql = ["pymysql"]
sqlcipher = ["sqlcipher3-binary"]
sqlcipher = ["sqlcipher3_binary"]
[[package]]
name = "sse-starlette"
@@ -8362,4 +8442,4 @@ youtube = ["youtube-transcript-api", "yt_dlp"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.9,<3.12"
content-hash = "f613dc1a3e9b724c95b407d4d8b9e67518e718142c77ad4723b7cb1e43eec9db"
content-hash = "e62b0c29fbd4b394814cff9a59ed4a22e0e8b09ec9a9bf8fc34533cee810a2f3"

View File

@@ -154,6 +154,8 @@ boto3 = { version = "^1.34.20", optional = true }
langchain-mistralai = { version = "^0.0.3", optional = true }
langchain-openai = "^0.0.5"
langchain-google-vertexai = { version = "^0.0.5", optional = true }
sqlalchemy = "^2.0.27"
alembic = "^1.13.1"
[tool.poetry.group.dev.dependencies]
black = "^23.3.0"

View File

@@ -1,19 +1,31 @@
import os
import pytest
from sqlalchemy import MetaData, create_engine
from sqlalchemy.orm import sessionmaker
@pytest.fixture(autouse=True)
def clean_db():
db_path = os.path.expanduser("~/.embedchain/embedchain.db")
if os.path.exists(db_path):
os.remove(db_path)
db_url = f"sqlite:///{db_path}"
engine = create_engine(db_url)
metadata = MetaData()
metadata.reflect(bind=engine) # Reflect schema from the engine
Session = sessionmaker(bind=engine)
session = Session()
@pytest.fixture
def setup():
clean_db()
yield
clean_db()
try:
# Iterate over all tables in reversed order to respect foreign keys
for table in reversed(metadata.sorted_tables):
if table.name != "alembic_version": # Skip the Alembic version table
session.execute(table.delete())
session.commit()
except Exception as e:
session.rollback()
print(f"Error cleaning database: {e}")
finally:
session.close()
@pytest.fixture(autouse=True)

View File

@@ -27,10 +27,7 @@ def test_whole_app(app_instance, mocker):
mocker.patch.object(BaseLlm, "get_answer_from_llm", return_value=knowledge)
mocker.patch.object(BaseLlm, "get_llm_model_answer", return_value=knowledge)
mocker.patch.object(BaseLlm, "generate_prompt")
mocker.patch.object(
BaseLlm,
"add_history",
)
mocker.patch.object(BaseLlm, "add_history")
mocker.patch.object(ChatHistory, "delete", autospec=True)
app_instance.add(knowledge, data_type="text")