Merge pull request #23 from topoteretes/add_async_elements
Added async elements
This commit is contained in:
Vasilije
GitHub
commit
6ba24d162a
9 changed files with 539 additions and 402 deletions
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@ -1,5 +1,5 @@
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FROM python:3.11-slim
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FROM python:3.11
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# Set build argument
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ARG API_ENABLED
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@ -25,27 +25,37 @@ After that, you can run:
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```docker compose build promethai_mem ```
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## Run
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## Run the level 3
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Make sure you have Docker, Poetry, and Python 3.11 installed and postgres installed.
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Copy the .env.example to .env and fill the variables
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Start the docker:
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```docker compose up promethai_mem ```
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Use the poetry environment:
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``` poetry shell ```
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Make sure to run
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Make sure to run to initialize DB tables
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``` python scripts/create_database.py ```
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After that, you can run:
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After that, you can run the RAG test manager.
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``` python rag_test_manager.py \
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```
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python rag_test_manager.py \
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--url "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf" \
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--test_set "example_data/test_set.json" \
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--user_id "666" \
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--metadata "example_data/metadata.json"
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```
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To see example of test_set.json and metadata.json, check the files in the folder "example_data"
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Examples of metadata structure and test set are in the folder "example_data"
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## Clean database
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@ -1,14 +1,15 @@
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import os
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from sqlalchemy import create_engine
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from sqlalchemy.orm import declarative_base
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from sqlalchemy.orm import sessionmaker
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from contextlib import contextmanager
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from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
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from sqlalchemy.orm import declarative_base, sessionmaker
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from contextlib import asynccontextmanager
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from sqlalchemy.exc import OperationalError
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from time import sleep
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import asyncio
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import sys
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from dotenv import load_dotenv
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load_dotenv()
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# this is needed to import classes from other modules
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script_dir = os.path.dirname(os.path.abspath(__file__))
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# Get the parent directory of your script and add it to sys.path
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@ -25,35 +26,43 @@ password = os.getenv('POSTGRES_PASSWORD')
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database_name = os.getenv('POSTGRES_DB')
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host = os.getenv('POSTGRES_HOST')
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# Use the asyncpg driver for async operation
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SQLALCHEMY_DATABASE_URL = f"postgresql+asyncpg://{username}:{password}@{host}:5432/{database_name}"
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SQLALCHEMY_DATABASE_URL = f"postgresql://{username}:{password}@{host}:5432/{database_name}"
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engine = create_engine(
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engine = create_async_engine(
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SQLALCHEMY_DATABASE_URL,
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pool_recycle=3600, # recycle connections after 1 hour
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pool_pre_ping=True # test the connection for liveness upon each checkout
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pool_recycle=3600,
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echo=True # Enable logging for tutorial purposes
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)
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# Use AsyncSession for the session
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AsyncSessionLocal = sessionmaker(
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bind=engine,
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class_=AsyncSession,
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expire_on_commit=False,
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)
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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Base = declarative_base()
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@contextmanager
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def get_db():
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db = SessionLocal()
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# Use asynccontextmanager to define an async context manager
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@asynccontextmanager
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async def get_db():
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db = AsyncSessionLocal()
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try:
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yield db
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finally:
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db.close()
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await db.close()
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def safe_db_operation(db_op, *args, **kwargs):
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# Use async/await syntax for the async function
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async def safe_db_operation(db_op, *args, **kwargs):
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for attempt in range(MAX_RETRIES):
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with get_db() as db:
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async with get_db() as db:
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try:
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return db_op(db, *args, **kwargs)
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# Ensure your db_op is also async
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return await db_op(db, *args, **kwargs)
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except OperationalError as e:
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db.rollback()
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await db.rollback()
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if "server closed the connection unexpectedly" in str(e) and attempt < MAX_RETRIES - 1:
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sleep(RETRY_DELAY)
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await asyncio.sleep(RETRY_DELAY)
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else:
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raise
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@ -1,15 +1,31 @@
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from contextlib import asynccontextmanager
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import asyncio
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from contextlib import asynccontextmanager
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import logging
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# from database import AsyncSessionLocal
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@contextmanager
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def session_scope(session):
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logger = logging.getLogger(__name__)
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@asynccontextmanager
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async def session_scope(session):
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"""Provide a transactional scope around a series of operations."""
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# session = AsyncSessionLocal()
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try:
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yield session
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session.commit()
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await session.commit()
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except Exception as e:
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session.rollback()
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await session.rollback()
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logger.error(f"Session rollback due to: {str(e)}")
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raise
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finally:
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session.close()
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await session.close()
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async def add_entity(session, entity):
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async with session_scope(session) as s: # Use your async session_scope
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s.add(entity) # No need to commit; session_scope takes care of it
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s.commit()
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return "Successfully added entity"
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191
level_3/poetry.lock
generated
191
level_3/poetry.lock
generated
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@ -169,6 +169,59 @@ files = [
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{file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
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]
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[[package]]
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name = "asyncpg"
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version = "0.28.0"
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description = "An asyncio PostgreSQL driver"
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optional = false
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python-versions = ">=3.7.0"
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files = [
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{file = "asyncpg-0.28.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0a6d1b954d2b296292ddff4e0060f494bb4270d87fb3655dd23c5c6096d16d83"},
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{file = "asyncpg-0.28.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0740f836985fd2bd73dca42c50c6074d1d61376e134d7ad3ad7566c4f79f8184"},
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{file = "asyncpg-0.28.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e907cf620a819fab1737f2dd90c0f185e2a796f139ac7de6aa3212a8af96c050"},
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{file = "asyncpg-0.28.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86b339984d55e8202e0c4b252e9573e26e5afa05617ed02252544f7b3e6de3e9"},
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{file = "asyncpg-0.28.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:0c402745185414e4c204a02daca3d22d732b37359db4d2e705172324e2d94e85"},
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{file = "asyncpg-0.28.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c88eef5e096296626e9688f00ab627231f709d0e7e3fb84bb4413dff81d996d7"},
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{file = "asyncpg-0.28.0-cp310-cp310-win32.whl", hash = "sha256:90a7bae882a9e65a9e448fdad3e090c2609bb4637d2a9c90bfdcebbfc334bf89"},
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{file = "asyncpg-0.28.0-cp310-cp310-win_amd64.whl", hash = "sha256:76aacdcd5e2e9999e83c8fbcb748208b60925cc714a578925adcb446d709016c"},
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{file = "asyncpg-0.28.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:a0e08fe2c9b3618459caaef35979d45f4e4f8d4f79490c9fa3367251366af207"},
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{file = "asyncpg-0.28.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:b24e521f6060ff5d35f761a623b0042c84b9c9b9fb82786aadca95a9cb4a893b"},
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{file = "asyncpg-0.28.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:99417210461a41891c4ff301490a8713d1ca99b694fef05dabd7139f9d64bd6c"},
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{file = "asyncpg-0.28.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f029c5adf08c47b10bcdc857001bbef551ae51c57b3110964844a9d79ca0f267"},
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{file = "asyncpg-0.28.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ad1d6abf6c2f5152f46fff06b0e74f25800ce8ec6c80967f0bc789974de3c652"},
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{file = "asyncpg-0.28.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d7fa81ada2807bc50fea1dc741b26a4e99258825ba55913b0ddbf199a10d69d8"},
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{file = "asyncpg-0.28.0-cp311-cp311-win32.whl", hash = "sha256:f33c5685e97821533df3ada9384e7784bd1e7865d2b22f153f2e4bd4a083e102"},
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{file = "asyncpg-0.28.0-cp311-cp311-win_amd64.whl", hash = "sha256:5e7337c98fb493079d686a4a6965e8bcb059b8e1b8ec42106322fc6c1c889bb0"},
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{file = "asyncpg-0.28.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:1c56092465e718a9fdcc726cc3d9dcf3a692e4834031c9a9f871d92a75d20d48"},
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{file = "asyncpg-0.28.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4acd6830a7da0eb4426249d71353e8895b350daae2380cb26d11e0d4a01c5472"},
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{file = "asyncpg-0.28.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:63861bb4a540fa033a56db3bb58b0c128c56fad5d24e6d0a8c37cb29b17c1c7d"},
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{file = "asyncpg-0.28.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:a93a94ae777c70772073d0512f21c74ac82a8a49be3a1d982e3f259ab5f27307"},
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||||
{file = "asyncpg-0.28.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:d14681110e51a9bc9c065c4e7944e8139076a778e56d6f6a306a26e740ed86d2"},
|
||||
{file = "asyncpg-0.28.0-cp37-cp37m-win32.whl", hash = "sha256:8aec08e7310f9ab322925ae5c768532e1d78cfb6440f63c078b8392a38aa636a"},
|
||||
{file = "asyncpg-0.28.0-cp37-cp37m-win_amd64.whl", hash = "sha256:319f5fa1ab0432bc91fb39b3960b0d591e6b5c7844dafc92c79e3f1bff96abef"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b337ededaabc91c26bf577bfcd19b5508d879c0ad009722be5bb0a9dd30b85a0"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4d32b680a9b16d2957a0a3cc6b7fa39068baba8e6b728f2e0a148a67644578f4"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f4f62f04cdf38441a70f279505ef3b4eadf64479b17e707c950515846a2df197"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f20cac332c2576c79c2e8e6464791c1f1628416d1115935a34ddd7121bfc6a4"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:59f9712ce01e146ff71d95d561fb68bd2d588a35a187116ef05028675462d5ed"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:fc9e9f9ff1aa0eddcc3247a180ac9e9b51a62311e988809ac6152e8fb8097756"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-win32.whl", hash = "sha256:9e721dccd3838fcff66da98709ed884df1e30a95f6ba19f595a3706b4bc757e3"},
|
||||
{file = "asyncpg-0.28.0-cp38-cp38-win_amd64.whl", hash = "sha256:8ba7d06a0bea539e0487234511d4adf81dc8762249858ed2a580534e1720db00"},
|
||||
{file = "asyncpg-0.28.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d009b08602b8b18edef3a731f2ce6d3f57d8dac2a0a4140367e194eabd3de457"},
|
||||
{file = "asyncpg-0.28.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ec46a58d81446d580fb21b376ec6baecab7288ce5a578943e2fc7ab73bf7eb39"},
|
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{file = "asyncpg-0.28.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7b48ceed606cce9e64fd5480a9b0b9a95cea2b798bb95129687abd8599c8b019"},
|
||||
{file = "asyncpg-0.28.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8858f713810f4fe67876728680f42e93b7e7d5c7b61cf2118ef9153ec16b9423"},
|
||||
{file = "asyncpg-0.28.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:5e18438a0730d1c0c1715016eacda6e9a505fc5aa931b37c97d928d44941b4bf"},
|
||||
{file = "asyncpg-0.28.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:e9c433f6fcdd61c21a715ee9128a3ca48be8ac16fa07be69262f016bb0f4dbd2"},
|
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{file = "asyncpg-0.28.0-cp39-cp39-win32.whl", hash = "sha256:41e97248d9076bc8e4849da9e33e051be7ba37cd507cbd51dfe4b2d99c70e3dc"},
|
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{file = "asyncpg-0.28.0-cp39-cp39-win_amd64.whl", hash = "sha256:3ed77f00c6aacfe9d79e9eff9e21729ce92a4b38e80ea99a58ed382f42ebd55b"},
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{file = "asyncpg-0.28.0.tar.gz", hash = "sha256:7252cdc3acb2f52feaa3664280d3bcd78a46bd6c10bfd681acfffefa1120e278"},
|
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]
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[package.extras]
|
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docs = ["Sphinx (>=5.3.0,<5.4.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-asyncio (>=0.3.0,<0.4.0)"]
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test = ["flake8 (>=5.0,<6.0)", "uvloop (>=0.15.3)"]
|
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|
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[[package]]
|
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name = "atlassian-python-api"
|
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version = "3.41.2"
|
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|
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@ -685,13 +738,13 @@ pdf = ["pypdf (>=3.3.0,<4.0.0)"]
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|
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[[package]]
|
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name = "deepeval"
|
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version = "0.20.1"
|
||||
version = "0.20.6"
|
||||
description = "DeepEval provides evaluation and unit testing to accelerate development of LLMs and Agents."
|
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optional = false
|
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python-versions = "*"
|
||||
files = [
|
||||
{file = "deepeval-0.20.1-py3-none-any.whl", hash = "sha256:f9880a1246a2a8ba77d88b1d2f977759d34741df6d584bb3c55fadc95c52bc89"},
|
||||
{file = "deepeval-0.20.1.tar.gz", hash = "sha256:e3e36745f5e77bc6055def0b98e7a3274c87564f498f50337b670a291fde32a5"},
|
||||
{file = "deepeval-0.20.6-py3-none-any.whl", hash = "sha256:aa0b96fa062f63398858fe2af1c4982ee9e4d53cd3e322c7bbc3812fe1267614"},
|
||||
{file = "deepeval-0.20.6.tar.gz", hash = "sha256:502c6bb8bc27069d4bbac171c2aac1a760ec8e5c11e3c87a7a8ed2a81ef21db6"},
|
||||
]
|
||||
|
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[package.dependencies]
|
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|
|
@ -702,6 +755,7 @@ pytest = "*"
|
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requests = "*"
|
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rich = "*"
|
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sentence-transformers = "*"
|
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sentry-sdk = "*"
|
||||
tabulate = "*"
|
||||
tqdm = "*"
|
||||
transformers = "*"
|
||||
|
|
@ -3519,6 +3573,51 @@ files = [
|
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{file = "sentencepiece-0.1.99.tar.gz", hash = "sha256:189c48f5cb2949288f97ccdb97f0473098d9c3dcf5a3d99d4eabe719ec27297f"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "sentry-sdk"
|
||||
version = "1.32.0"
|
||||
description = "Python client for Sentry (https://sentry.io)"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "sentry-sdk-1.32.0.tar.gz", hash = "sha256:935e8fbd7787a3702457393b74b13d89a5afb67185bc0af85c00cb27cbd42e7c"},
|
||||
{file = "sentry_sdk-1.32.0-py2.py3-none-any.whl", hash = "sha256:eeb0b3550536f3bbc05bb1c7e0feb3a78d74acb43b607159a606ed2ec0a33a4d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
certifi = "*"
|
||||
urllib3 = {version = ">=1.26.11", markers = "python_version >= \"3.6\""}
|
||||
|
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[package.extras]
|
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aiohttp = ["aiohttp (>=3.5)"]
|
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arq = ["arq (>=0.23)"]
|
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asyncpg = ["asyncpg (>=0.23)"]
|
||||
beam = ["apache-beam (>=2.12)"]
|
||||
bottle = ["bottle (>=0.12.13)"]
|
||||
celery = ["celery (>=3)"]
|
||||
chalice = ["chalice (>=1.16.0)"]
|
||||
clickhouse-driver = ["clickhouse-driver (>=0.2.0)"]
|
||||
django = ["django (>=1.8)"]
|
||||
falcon = ["falcon (>=1.4)"]
|
||||
fastapi = ["fastapi (>=0.79.0)"]
|
||||
flask = ["blinker (>=1.1)", "flask (>=0.11)", "markupsafe"]
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grpcio = ["grpcio (>=1.21.1)"]
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||||
httpx = ["httpx (>=0.16.0)"]
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||||
huey = ["huey (>=2)"]
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||||
loguru = ["loguru (>=0.5)"]
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opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
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||||
pure-eval = ["asttokens", "executing", "pure-eval"]
|
||||
pymongo = ["pymongo (>=3.1)"]
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||||
pyspark = ["pyspark (>=2.4.4)"]
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||||
quart = ["blinker (>=1.1)", "quart (>=0.16.1)"]
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||||
rq = ["rq (>=0.6)"]
|
||||
sanic = ["sanic (>=0.8)"]
|
||||
sqlalchemy = ["sqlalchemy (>=1.2)"]
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||||
starlette = ["starlette (>=0.19.1)"]
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||||
starlite = ["starlite (>=1.48)"]
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||||
tornado = ["tornado (>=5)"]
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||||
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||||
[[package]]
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||||
name = "setuptools"
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version = "68.1.2"
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|
|
@ -3816,52 +3915,52 @@ files = [
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[[package]]
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||||
name = "sqlalchemy"
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version = "2.0.20"
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version = "2.0.21"
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description = "Database Abstraction Library"
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optional = false
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||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4778,4 +4877,4 @@ multidict = ">=4.0"
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "cf14b96576c57633fea1b0cc1f7266a5fb265d4ff4ce2d3479a036483082b3b4"
|
||||
content-hash = "b3f795baef70806c8dab1058b644d95f3c36b1c2fae53a7e5784a633731bc268"
|
||||
|
|
|
|||
|
|
@ -40,11 +40,13 @@ weaviate-client = "^3.22.1"
|
|||
python-multipart = "^0.0.6"
|
||||
deep-translator = "^1.11.4"
|
||||
humanize = "^4.8.0"
|
||||
deepeval = "^0.20.1"
|
||||
deepeval = "^0.20.6"
|
||||
pymupdf = "^1.23.3"
|
||||
psycopg2 = "^2.9.8"
|
||||
llama-index = "^0.8.39.post2"
|
||||
llama-hub = "^0.0.34"
|
||||
sqlalchemy = "^2.0.21"
|
||||
asyncpg = "^0.28.0"
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -20,6 +20,8 @@ from database.database import engine
|
|||
from vectorstore_manager import Memory
|
||||
import uuid
|
||||
from contextlib import contextmanager
|
||||
from database.database import AsyncSessionLocal
|
||||
from database.database_crud import session_scope
|
||||
|
||||
import random
|
||||
import string
|
||||
|
|
@ -30,103 +32,65 @@ dotenv.load_dotenv()
|
|||
import openai
|
||||
logger = logging.getLogger(__name__)
|
||||
openai.api_key = os.getenv("OPENAI_API_KEY", "")
|
||||
@contextmanager
|
||||
def session_scope(session):
|
||||
"""Provide a transactional scope around a series of operations."""
|
||||
|
||||
async def retrieve_latest_test_case(session, user_id, memory_id):
|
||||
try:
|
||||
yield session
|
||||
session.commit()
|
||||
except Exception as e:
|
||||
session.rollback()
|
||||
logger.error(f"Session rollback due to: {str(e)}")
|
||||
raise
|
||||
finally:
|
||||
session.close()
|
||||
|
||||
def retrieve_latest_test_case(session, user_id, memory_id):
|
||||
"""
|
||||
Retrieve the most recently created test case from the database filtered by user_id and memory_id.
|
||||
|
||||
Parameters:
|
||||
- session (Session): A database session.
|
||||
- user_id (int/str): The ID of the user to filter test cases by.
|
||||
- memory_id (int/str): The ID of the memory to filter test cases by.
|
||||
|
||||
Returns:
|
||||
- Object: The most recent test case attributes filtered by user_id and memory_id, or None if an error occurs.
|
||||
"""
|
||||
try:
|
||||
return (
|
||||
# Use await with session.execute() and row.fetchone() or row.all() for async query execution
|
||||
result = await session.execute(
|
||||
session.query(TestSet.attributes_list)
|
||||
.filter_by(user_id=user_id, memory_id=memory_id)
|
||||
.order_by(TestSet.created_at.desc())
|
||||
.first()
|
||||
.order_by(TestSet.created_at).first()
|
||||
)
|
||||
return result.scalar_one_or_none() # scalar_one_or_none() is a non-blocking call
|
||||
except Exception as e:
|
||||
logger.error(f"An error occurred while retrieving the latest test case: {str(e)}")
|
||||
return None
|
||||
|
||||
|
||||
def add_entity(session, entity):
|
||||
"""
|
||||
Add an entity (like TestOutput, Session, etc.) to the database.
|
||||
|
||||
Parameters:
|
||||
- session (Session): A database session.
|
||||
- entity (Base): An instance of an SQLAlchemy model.
|
||||
|
||||
Returns:
|
||||
- str: A message indicating whether the addition was successful.
|
||||
"""
|
||||
with session_scope(session):
|
||||
session.add(entity)
|
||||
session.commit()
|
||||
async def add_entity(session, entity):
|
||||
async with session_scope(session) as s: # Use your async session_scope
|
||||
s.add(entity) # No need to commit; session_scope takes care of it
|
||||
s.commit()
|
||||
return "Successfully added entity"
|
||||
|
||||
|
||||
def retrieve_job_by_id(session, user_id, job_id):
|
||||
"""
|
||||
Retrieve a job by user ID and job ID.
|
||||
|
||||
Parameters:
|
||||
- session (Session): A database session.
|
||||
- user_id (int/str): The ID of the user.
|
||||
- job_id (int/str): The ID of the job to retrieve.
|
||||
|
||||
Returns:
|
||||
- Object: The job attributes filtered by user_id and job_id, or None if an error occurs.
|
||||
"""
|
||||
async def retrieve_job_by_id(session, user_id, job_id):
|
||||
try:
|
||||
return (
|
||||
result = await session.execute(
|
||||
session.query(Session.id)
|
||||
.filter_by(user_id=user_id, id=job_id)
|
||||
.order_by(Session.created_at.desc())
|
||||
.first()
|
||||
.order_by(Session.created_at)
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
except Exception as e:
|
||||
logger.error(f"An error occurred while retrieving the job: {str(e)}")
|
||||
return None
|
||||
|
||||
def fetch_job_id(session, user_id=None, memory_id=None, job_id=None):
|
||||
async def fetch_job_id(session, user_id=None, memory_id=None, job_id=None):
|
||||
try:
|
||||
return (
|
||||
result = await session.execute(
|
||||
session.query(Session.id)
|
||||
.filter_by(user_id=user_id, id=job_id)
|
||||
.order_by(Session.created_at.desc())
|
||||
.first()
|
||||
.order_by(Session.created_at).first()
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
except Exception as e:
|
||||
# Handle exceptions as per your application's requirements.
|
||||
print(f"An error occurred: {str(e)}")
|
||||
logger.error(f"An error occurred: {str(e)}")
|
||||
return None
|
||||
|
||||
|
||||
def compare_output(output, expected_output):
|
||||
"""Compare the output against the expected output."""
|
||||
pass
|
||||
|
||||
|
||||
async def fetch_test_set_id(session, user_id, id):
|
||||
try:
|
||||
# Await the execution of the query and fetching of the result
|
||||
result = await session.execute(
|
||||
session.query(TestSet.id)
|
||||
.filter_by(user_id=user_id, id=id)
|
||||
.order_by(TestSet.created_at).desc().first()
|
||||
)
|
||||
return result.scalar_one_or_none() # scalar_one_or_none() is a non-blocking call
|
||||
except Exception as e:
|
||||
logger.error(f"An error occurred while retrieving the test set: {str(e)}")
|
||||
return None
|
||||
|
||||
# Adding "embeddings" to the parameter variants function
|
||||
|
||||
def generate_param_variants(base_params=None, increments=None, ranges=None, included_params=None):
|
||||
"""Generate parameter variants for testing.
|
||||
|
|
@ -142,38 +106,39 @@ def generate_param_variants(base_params=None, increments=None, ranges=None, incl
|
|||
list: A list of dictionaries containing parameter variants.
|
||||
"""
|
||||
|
||||
# Default base values
|
||||
# Default values
|
||||
defaults = {
|
||||
'chunk_size': 500,
|
||||
'chunk_size': 250,
|
||||
'chunk_overlap': 20,
|
||||
'similarity_score': 0.5,
|
||||
'metadata_variation': 0,
|
||||
'search_type': 'hybrid'
|
||||
'search_type': 'hybrid',
|
||||
'embeddings': 'openai' # Default value added for 'embeddings'
|
||||
}
|
||||
|
||||
# Update defaults with provided base parameters
|
||||
params = {**defaults, **(base_params if base_params is not None else {})}
|
||||
params = {**defaults, **(base_params or {})}
|
||||
|
||||
default_increments = {
|
||||
'chunk_size': 500,
|
||||
'chunk_size': 150,
|
||||
'chunk_overlap': 10,
|
||||
'similarity_score': 0.1,
|
||||
'metadata_variation': 1
|
||||
}
|
||||
|
||||
# Update default increments with provided increments
|
||||
increments = {**default_increments, **(increments if increments is not None else {})}
|
||||
increments = {**default_increments, **(increments or {})}
|
||||
|
||||
# Default ranges
|
||||
default_ranges = {
|
||||
'chunk_size': 3,
|
||||
'chunk_overlap': 3,
|
||||
'similarity_score': 3,
|
||||
'metadata_variation': 3
|
||||
'chunk_size': 2,
|
||||
'chunk_overlap': 2,
|
||||
'similarity_score': 2,
|
||||
'metadata_variation': 2
|
||||
}
|
||||
|
||||
# Update default ranges with provided ranges
|
||||
ranges = {**default_ranges, **(ranges if ranges is not None else {})}
|
||||
ranges = {**default_ranges, **(ranges or {})}
|
||||
|
||||
# Generate parameter variant ranges
|
||||
param_ranges = {
|
||||
|
|
@ -181,10 +146,9 @@ def generate_param_variants(base_params=None, increments=None, ranges=None, incl
|
|||
for key in ['chunk_size', 'chunk_overlap', 'similarity_score', 'metadata_variation']
|
||||
}
|
||||
|
||||
|
||||
param_ranges['cognitive_architecture'] = ["simple_index", "cognitive_architecture"]
|
||||
# Add search_type with possible values
|
||||
# Add search_type and embeddings with possible values
|
||||
param_ranges['search_type'] = ['text', 'hybrid', 'bm25', 'generate', 'generate_grouped']
|
||||
param_ranges['embeddings'] = ['openai', 'cohere', 'huggingface'] # Added 'embeddings' values
|
||||
|
||||
# Filter param_ranges based on included_params
|
||||
if included_params is not None:
|
||||
|
|
@ -197,6 +161,10 @@ def generate_param_variants(base_params=None, increments=None, ranges=None, incl
|
|||
|
||||
return param_variants
|
||||
|
||||
|
||||
# Generate parameter variants and display a sample of the generated combinations
|
||||
|
||||
|
||||
async def generate_chatgpt_output(query:str, context:str=None):
|
||||
response = openai.ChatCompletion.create(
|
||||
model="gpt-3.5-turbo",
|
||||
|
|
@ -278,195 +246,200 @@ def generate_letter_uuid(length=8):
|
|||
letters = string.ascii_uppercase # A-Z
|
||||
return ''.join(random.choice(letters) for _ in range(length))
|
||||
|
||||
async def start_test(data, test_set=None, user_id=None, params=None, job_id=None, metadata=None):
|
||||
|
||||
def fetch_test_set_id(session, user_id, id):
|
||||
try:
|
||||
return (
|
||||
session.query(TestSet.id)
|
||||
.filter_by(user_id=user_id, id=id)
|
||||
.order_by(TestSet.created_at)
|
||||
.desc().first()
|
||||
|
||||
async with session_scope(session=AsyncSessionLocal()) as session:
|
||||
memory = await Memory.create_memory(user_id, session, namespace="SEMANTICMEMORY")
|
||||
job_id = await fetch_job_id(session, user_id=user_id, job_id=job_id)
|
||||
test_set_id = await fetch_test_set_id(session, user_id=user_id, id=job_id)
|
||||
|
||||
if job_id is None:
|
||||
job_id = str(uuid.uuid4())
|
||||
await add_entity(session, Operation(id=job_id, user_id=user_id))
|
||||
|
||||
if test_set_id is None:
|
||||
test_set_id = str(uuid.uuid4())
|
||||
await add_entity(session, TestSet(id=test_set_id, user_id=user_id, content=str(test_set)))
|
||||
|
||||
if params is None:
|
||||
data_format = data_format_route(data) # Assume data_format_route is predefined
|
||||
data_location = data_location_route(data) # Assume data_location_route is predefined
|
||||
test_params = generate_param_variants(
|
||||
included_params=['chunk_size', 'chunk_overlap', 'search_type'])
|
||||
|
||||
print("Here are the test params", str(test_params))
|
||||
|
||||
loader_settings = {
|
||||
"format": f"{data_format}",
|
||||
"source": f"{data_location}",
|
||||
"path": "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf"
|
||||
}
|
||||
|
||||
async def run_test(test, loader_settings, metadata):
|
||||
test_id = str(generate_letter_uuid()) + "_" + "SEMANTICEMEMORY"
|
||||
await memory.add_memory_instance("ExampleMemory")
|
||||
existing_user = await Memory.check_existing_user(user_id, session)
|
||||
await memory.manage_memory_attributes(existing_user)
|
||||
test_class = test_id + "_class"
|
||||
await memory.add_dynamic_memory_class(test_id.lower(), test_id)
|
||||
dynamic_memory_class = getattr(memory, test_class.lower(), None)
|
||||
|
||||
# Assuming add_method_to_class and dynamic_method_call are predefined methods in Memory class
|
||||
|
||||
if dynamic_memory_class is not None:
|
||||
await memory.add_method_to_class(dynamic_memory_class, 'add_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
if dynamic_memory_class is not None:
|
||||
await memory.add_method_to_class(dynamic_memory_class, 'fetch_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
print(f"Trying to access: {test_class.lower()}")
|
||||
print("Available memory classes:", await memory.list_memory_classes())
|
||||
|
||||
print(f"Trying to check: ", test)
|
||||
loader_settings.update(test)
|
||||
|
||||
|
||||
async def run_load_test_element(test, loader_settings, metadata, test_id):
|
||||
|
||||
test_class = test_id + "_class"
|
||||
# memory.test_class
|
||||
|
||||
await memory.add_dynamic_memory_class(test_id.lower(), test_id)
|
||||
dynamic_memory_class = getattr(memory, test_class.lower(), None)
|
||||
if dynamic_memory_class is not None:
|
||||
await memory.add_method_to_class(dynamic_memory_class, 'add_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
if dynamic_memory_class is not None:
|
||||
await memory.add_method_to_class(dynamic_memory_class, 'fetch_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
print(f"Trying to access: {test_class.lower()}")
|
||||
print("Available memory classes:", await memory.list_memory_classes())
|
||||
|
||||
print(f"Trying to check: ", test)
|
||||
# print("Here is the loader settings", str(loader_settings))
|
||||
# print("Here is the medatadata", str(metadata))
|
||||
load_action = await memory.dynamic_method_call(dynamic_memory_class, 'add_memories',
|
||||
observation='some_observation', params=metadata,
|
||||
loader_settings=loader_settings)
|
||||
async def run_search_eval_element(test_item, test_id):
|
||||
|
||||
test_class = test_id + "_class"
|
||||
await memory.add_dynamic_memory_class(test_id.lower(), test_id)
|
||||
dynamic_memory_class = getattr(memory, test_class.lower(), None)
|
||||
|
||||
retrieve_action = await memory.dynamic_method_call(dynamic_memory_class, 'fetch_memories',
|
||||
observation=test_item["question"],
|
||||
search_type=test_item["search_type"])
|
||||
test_result = await eval_test(query=test_item["question"], expected_output=test_item["answer"],
|
||||
context=str(retrieve_action))
|
||||
print(test_result)
|
||||
delete_mems = await memory.dynamic_method_call(dynamic_memory_class, 'delete_memories',
|
||||
namespace=test_id)
|
||||
return test_result
|
||||
test_load_pipeline = await asyncio.gather(
|
||||
*(run_load_test_element(test_item,loader_settings, metadata, test_id) for test_item in test_set)
|
||||
)
|
||||
|
||||
test_eval_pipeline = await asyncio.gather(
|
||||
*(run_search_eval_element(test_item, test_id) for test_item in test_set)
|
||||
)
|
||||
logging.info("Results of the eval pipeline %s", str(test_eval_pipeline))
|
||||
await add_entity(session, TestOutput(id=test_id, user_id=user_id, test_results=str(test_eval_pipeline)))
|
||||
|
||||
# # Gather and run all tests in parallel
|
||||
results = await asyncio.gather(
|
||||
*(run_test(test, loader_settings, metadata) for test in test_params)
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"An error occurred while retrieving the job: {str(e)}")
|
||||
return None
|
||||
|
||||
|
||||
async def start_test(data, test_set=None, user_id=None, params=None, job_id=None ,metadata=None):
|
||||
|
||||
Session = sessionmaker(bind=engine)
|
||||
session = Session()
|
||||
|
||||
|
||||
#do i need namespace in memory instance, fix it
|
||||
memory = Memory.create_memory(user_id, session, namespace="SEMANTICMEMORY")
|
||||
|
||||
job_id = fetch_job_id(session, user_id = user_id,job_id =job_id)
|
||||
test_set_id = fetch_test_set_id(session, user_id=user_id, id=job_id)
|
||||
if job_id is None:
|
||||
job_id = str(uuid.uuid4())
|
||||
logging.info("we are adding a new job ID")
|
||||
add_entity(session, Operation(id = job_id, user_id = user_id))
|
||||
if test_set_id is None:
|
||||
test_set_id = str(uuid.uuid4())
|
||||
add_entity(session, TestSet(id = test_set_id, user_id = user_id, content = str(test_set)))
|
||||
|
||||
|
||||
|
||||
if params is None:
|
||||
|
||||
data_format = data_format_route(data)
|
||||
data_location = data_location_route(data)
|
||||
test_params = generate_param_variants( included_params=['chunk_size', 'chunk_overlap', 'similarity_score'])
|
||||
|
||||
|
||||
|
||||
loader_settings = {
|
||||
"format": f"{data_format}",
|
||||
"source": f"{data_location}",
|
||||
"path": "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf"
|
||||
}
|
||||
|
||||
for test in test_params:
|
||||
test_id = str(generate_letter_uuid()) + "_" + "SEMANTICEMEMORY"
|
||||
|
||||
# Adding a memory instance
|
||||
memory.add_memory_instance("ExampleMemory")
|
||||
|
||||
# Managing memory attributes
|
||||
existing_user = Memory.check_existing_user(user_id, session)
|
||||
print("here is the existing user", existing_user)
|
||||
memory.manage_memory_attributes(existing_user)
|
||||
|
||||
test_class = test_id + "_class"
|
||||
# memory.test_class
|
||||
|
||||
memory.add_dynamic_memory_class(test_id.lower(), test_id)
|
||||
dynamic_memory_class = getattr(memory, test_class.lower(), None)
|
||||
|
||||
|
||||
|
||||
if dynamic_memory_class is not None:
|
||||
memory.add_method_to_class(dynamic_memory_class, 'add_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
if dynamic_memory_class is not None:
|
||||
memory.add_method_to_class(dynamic_memory_class, 'fetch_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
|
||||
print(f"Trying to access: {test_class.lower()}")
|
||||
print("Available memory classes:", memory.list_memory_classes())
|
||||
|
||||
print(f"Trying to check: ", test)
|
||||
loader_settings.update(test)
|
||||
load_action = await memory.dynamic_method_call(dynamic_memory_class, 'add_memories',
|
||||
observation='some_observation', params=metadata, loader_settings=loader_settings)
|
||||
loader_settings = {key: value for key, value in loader_settings.items() if key not in test}
|
||||
|
||||
|
||||
|
||||
test_result_collection =[]
|
||||
|
||||
for test in test_set:
|
||||
retrieve_action = await memory.dynamic_method_call(dynamic_memory_class, 'fetch_memories',
|
||||
observation=test["question"])
|
||||
|
||||
test_results = await eval_test( query=test["question"], expected_output=test["answer"], context= str(retrieve_action))
|
||||
test_result_collection.append(test_results)
|
||||
|
||||
print(test_results)
|
||||
if dynamic_memory_class is not None:
|
||||
memory.add_method_to_class(dynamic_memory_class, 'delete_memories')
|
||||
else:
|
||||
print(f"No attribute named {test_class.lower()} in memory.")
|
||||
delete_mems = await memory.dynamic_method_call(dynamic_memory_class, 'delete_memories',
|
||||
namespace =test_id)
|
||||
|
||||
print(test_result_collection)
|
||||
|
||||
add_entity(session, TestOutput(id=test_id, user_id=user_id, test_results=str(test_result_collection)))
|
||||
return results
|
||||
|
||||
async def main():
|
||||
|
||||
params = {
|
||||
"version": "1.0",
|
||||
"agreement_id": "AG123456",
|
||||
"privacy_policy": "https://example.com/privacy",
|
||||
"terms_of_service": "https://example.com/terms",
|
||||
"format": "json",
|
||||
"schema_version": "1.1",
|
||||
"checksum": "a1b2c3d4e5f6",
|
||||
"owner": "John Doe",
|
||||
"license": "MIT",
|
||||
"validity_start": "2023-08-01",
|
||||
"validity_end": "2024-07-31",
|
||||
}
|
||||
|
||||
test_set = [
|
||||
{
|
||||
"question": "Who is the main character in 'The Call of the Wild'?",
|
||||
"answer": "Buck"
|
||||
},
|
||||
{
|
||||
"question": "Who wrote 'The Call of the Wild'?",
|
||||
"answer": "Jack London"
|
||||
},
|
||||
{
|
||||
"question": "Where does Buck live at the start of the book?",
|
||||
"answer": "In the Santa Clara Valley, at Judge Miller’s place."
|
||||
},
|
||||
{
|
||||
"question": "Why is Buck kidnapped?",
|
||||
"answer": "He is kidnapped to be sold as a sled dog in the Yukon during the Klondike Gold Rush."
|
||||
},
|
||||
{
|
||||
"question": "How does Buck become the leader of the sled dog team?",
|
||||
"answer": "Buck becomes the leader after defeating the original leader, Spitz, in a fight."
|
||||
}
|
||||
]
|
||||
result = await start_test("https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf", test_set=test_set, user_id="666", params=None, metadata=params)
|
||||
#
|
||||
# params = {
|
||||
# "version": "1.0",
|
||||
# "agreement_id": "AG123456",
|
||||
# "privacy_policy": "https://example.com/privacy",
|
||||
# "terms_of_service": "https://example.com/terms",
|
||||
# "format": "json",
|
||||
# "schema_version": "1.1",
|
||||
# "checksum": "a1b2c3d4e5f6",
|
||||
# "owner": "John Doe",
|
||||
# "license": "MIT",
|
||||
# "validity_start": "2023-08-01",
|
||||
# "validity_end": "2024-07-31",
|
||||
# }
|
||||
# parser = argparse.ArgumentParser(description="Run tests against a document.")
|
||||
# parser.add_argument("--url", required=True, help="URL of the document to test.")
|
||||
# parser.add_argument("--test_set", required=True, help="Path to JSON file containing the test set.")
|
||||
# parser.add_argument("--user_id", required=True, help="User ID.")
|
||||
# parser.add_argument("--params", help="Additional parameters in JSON format.")
|
||||
# parser.add_argument("--metadata", required=True, help="Path to JSON file containing metadata.")
|
||||
#
|
||||
# test_set = [
|
||||
# {
|
||||
# "question": "Who is the main character in 'The Call of the Wild'?",
|
||||
# "answer": "Buck"
|
||||
# },
|
||||
# {
|
||||
# "question": "Who wrote 'The Call of the Wild'?",
|
||||
# "answer": "Jack London"
|
||||
# },
|
||||
# {
|
||||
# "question": "Where does Buck live at the start of the book?",
|
||||
# "answer": "In the Santa Clara Valley, at Judge Miller’s place."
|
||||
# },
|
||||
# {
|
||||
# "question": "Why is Buck kidnapped?",
|
||||
# "answer": "He is kidnapped to be sold as a sled dog in the Yukon during the Klondike Gold Rush."
|
||||
# },
|
||||
# {
|
||||
# "question": "How does Buck become the leader of the sled dog team?",
|
||||
# "answer": "Buck becomes the leader after defeating the original leader, Spitz, in a fight."
|
||||
# }
|
||||
# ]
|
||||
# result = await start_test("https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf", test_set=test_set, user_id="666", params=None, metadata=params)
|
||||
# args = parser.parse_args()
|
||||
#
|
||||
parser = argparse.ArgumentParser(description="Run tests against a document.")
|
||||
parser.add_argument("--url", required=True, help="URL of the document to test.")
|
||||
parser.add_argument("--test_set", required=True, help="Path to JSON file containing the test set.")
|
||||
parser.add_argument("--user_id", required=True, help="User ID.")
|
||||
parser.add_argument("--params", help="Additional parameters in JSON format.")
|
||||
parser.add_argument("--metadata", required=True, help="Path to JSON file containing metadata.")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
with open(args.test_set, "r") as file:
|
||||
test_set = json.load(file)
|
||||
if not isinstance(test_set, list): # Expecting a list
|
||||
raise TypeError("Parsed test_set JSON is not a list.")
|
||||
except Exception as e:
|
||||
print(f"Error loading test_set: {str(e)}")
|
||||
return
|
||||
|
||||
try:
|
||||
with open(args.metadata, "r") as file:
|
||||
metadata = json.load(file)
|
||||
if not isinstance(metadata, dict):
|
||||
raise TypeError("Parsed metadata JSON is not a dictionary.")
|
||||
except Exception as e:
|
||||
print(f"Error loading metadata: {str(e)}")
|
||||
return
|
||||
|
||||
if args.params:
|
||||
try:
|
||||
params = json.loads(args.params)
|
||||
if not isinstance(params, dict):
|
||||
raise TypeError("Parsed params JSON is not a dictionary.")
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"Error parsing params: {str(e)}")
|
||||
return
|
||||
else:
|
||||
params = None
|
||||
#clean up params here
|
||||
await start_test(args.url, test_set, args.user_id, params=None, metadata=metadata)
|
||||
# try:
|
||||
# with open(args.test_set, "r") as file:
|
||||
# test_set = json.load(file)
|
||||
# if not isinstance(test_set, list): # Expecting a list
|
||||
# raise TypeError("Parsed test_set JSON is not a list.")
|
||||
# except Exception as e:
|
||||
# print(f"Error loading test_set: {str(e)}")
|
||||
# return
|
||||
#
|
||||
# try:
|
||||
# with open(args.metadata, "r") as file:
|
||||
# metadata = json.load(file)
|
||||
# if not isinstance(metadata, dict):
|
||||
# raise TypeError("Parsed metadata JSON is not a dictionary.")
|
||||
# except Exception as e:
|
||||
# print(f"Error loading metadata: {str(e)}")
|
||||
# return
|
||||
#
|
||||
# if args.params:
|
||||
# try:
|
||||
# params = json.loads(args.params)
|
||||
# if not isinstance(params, dict):
|
||||
# raise TypeError("Parsed params JSON is not a dictionary.")
|
||||
# except json.JSONDecodeError as e:
|
||||
# print(f"Error parsing params: {str(e)}")
|
||||
# return
|
||||
# else:
|
||||
# params = None
|
||||
# #clean up params here
|
||||
# await start_test(args.url, test_set, args.user_id, params=None, metadata=metadata)
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
|
|
|
|||
|
|
@ -179,17 +179,17 @@ class WeaviateVectorDB(VectorDB):
|
|||
["id", "creationTimeUnix", "lastUpdateTimeUnix", "score", 'distance']
|
||||
).with_where(params_user_id).with_limit(10)
|
||||
|
||||
n_of_observations = kwargs.get('n_of_observations', 2)
|
||||
|
||||
try:
|
||||
if search_type == 'text':
|
||||
query_output = (
|
||||
base_query
|
||||
.with_near_text({"concepts": [observation]})
|
||||
.with_autocut(n_of_observations)
|
||||
.do()
|
||||
)
|
||||
elif search_type == 'hybrid':
|
||||
n_of_observations = kwargs.get('n_of_observations', 2)
|
||||
|
||||
|
||||
query_output = (
|
||||
base_query
|
||||
.with_hybrid(query=observation, fusion_type=HybridFusion.RELATIVE_SCORE)
|
||||
|
|
@ -200,6 +200,7 @@ class WeaviateVectorDB(VectorDB):
|
|||
query_output = (
|
||||
base_query
|
||||
.with_bm25(query=observation)
|
||||
.with_autocut(n_of_observations)
|
||||
.do()
|
||||
)
|
||||
elif search_type == 'generate':
|
||||
|
|
@ -208,6 +209,7 @@ class WeaviateVectorDB(VectorDB):
|
|||
base_query
|
||||
.with_generate(single_prompt=generate_prompt)
|
||||
.with_near_text({"concepts": [observation]})
|
||||
.with_autocut(n_of_observations)
|
||||
.do()
|
||||
)
|
||||
elif search_type == 'generate_grouped':
|
||||
|
|
@ -216,6 +218,7 @@ class WeaviateVectorDB(VectorDB):
|
|||
base_query
|
||||
.with_generate(grouped_task=generate_prompt)
|
||||
.with_near_text({"concepts": [observation]})
|
||||
.with_autocut(n_of_observations)
|
||||
.do()
|
||||
)
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -1,5 +1,7 @@
|
|||
import logging
|
||||
|
||||
from sqlalchemy.future import select
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
import marvin
|
||||
from dotenv import load_dotenv
|
||||
|
|
@ -15,6 +17,7 @@ from models.operation import Operation
|
|||
load_dotenv()
|
||||
import ast
|
||||
import tracemalloc
|
||||
from database.database_crud import session_scope, add_entity
|
||||
|
||||
tracemalloc.start()
|
||||
|
||||
|
|
@ -48,7 +51,7 @@ class DynamicBaseMemory(BaseMemory):
|
|||
self.associations = []
|
||||
|
||||
|
||||
def add_method(self, method_name):
|
||||
async def add_method(self, method_name):
|
||||
"""
|
||||
Add a method to the memory class.
|
||||
|
||||
|
|
@ -60,7 +63,7 @@ class DynamicBaseMemory(BaseMemory):
|
|||
"""
|
||||
self.methods.add(method_name)
|
||||
|
||||
def add_attribute(self, attribute_name):
|
||||
async def add_attribute(self, attribute_name):
|
||||
"""
|
||||
Add an attribute to the memory class.
|
||||
|
||||
|
|
@ -72,7 +75,7 @@ class DynamicBaseMemory(BaseMemory):
|
|||
"""
|
||||
self.attributes.add(attribute_name)
|
||||
|
||||
def get_attribute(self, attribute_name):
|
||||
async def get_attribute(self, attribute_name):
|
||||
"""
|
||||
Check if the attribute is in the memory class.
|
||||
|
||||
|
|
@ -84,7 +87,7 @@ class DynamicBaseMemory(BaseMemory):
|
|||
"""
|
||||
return attribute_name in self.attributes
|
||||
|
||||
def add_association(self, associated_memory):
|
||||
async def add_association(self, associated_memory):
|
||||
"""
|
||||
Add an association to another memory class.
|
||||
|
||||
|
|
@ -149,26 +152,26 @@ class Memory:
|
|||
self.OPENAI_TEMPERATURE = float(os.getenv("OPENAI_TEMPERATURE", 0.0))
|
||||
self.OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
|
||||
@classmethod
|
||||
def create_memory(cls, user_id: str, session, **kwargs):
|
||||
async def create_memory(cls, user_id: str, session, **kwargs):
|
||||
"""
|
||||
Class method that acts as a factory method for creating Memory instances.
|
||||
It performs necessary DB checks or updates before instance creation.
|
||||
"""
|
||||
existing_user = cls.check_existing_user(user_id, session)
|
||||
existing_user = await cls.check_existing_user(user_id, session)
|
||||
|
||||
if existing_user:
|
||||
|
||||
# Handle existing user scenario...
|
||||
memory_id = cls.check_existing_memory(user_id, session)
|
||||
memory_id = await cls.check_existing_memory(user_id, session)
|
||||
logging.info(f"Existing user {user_id} found in the DB. Memory ID: {memory_id}")
|
||||
else:
|
||||
# Handle new user scenario...
|
||||
memory_id = cls.handle_new_user(user_id, session)
|
||||
memory_id = await cls.handle_new_user(user_id, session)
|
||||
logging.info(f"New user {user_id} created in the DB. Memory ID: {memory_id}")
|
||||
|
||||
return cls(user_id=user_id, session=session, memory_id=memory_id, **kwargs)
|
||||
|
||||
def list_memory_classes(self):
|
||||
async def list_memory_classes(self):
|
||||
"""
|
||||
Lists all available memory classes in the memory instance.
|
||||
"""
|
||||
|
|
@ -176,32 +179,36 @@ class Memory:
|
|||
return [attr for attr in dir(self) if attr.endswith("_class")]
|
||||
|
||||
@staticmethod
|
||||
def check_existing_user(user_id: str, session):
|
||||
async def check_existing_user(user_id: str, session):
|
||||
"""Check if a user exists in the DB and return it."""
|
||||
return session.query(User).filter_by(id=user_id).first()
|
||||
result = await session.execute(
|
||||
select(User).where(User.id == user_id)
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
|
||||
@staticmethod
|
||||
def check_existing_memory(user_id: str, session):
|
||||
async def check_existing_memory(user_id: str, session):
|
||||
"""Check if a user memory exists in the DB and return it."""
|
||||
return session.query(MemoryModel.id).filter_by(user_id=user_id).first()
|
||||
result = await session.execute(
|
||||
select(MemoryModel.id).where(MemoryModel.user_id == user_id)
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
|
||||
@staticmethod
|
||||
def handle_new_user(user_id: str, session):
|
||||
async def handle_new_user(user_id: str, session):
|
||||
"""Handle new user creation in the DB and return the new memory ID."""
|
||||
|
||||
#handle these better in terms of retry and error handling
|
||||
memory_id = str(uuid.uuid4())
|
||||
new_user = User(id=user_id)
|
||||
session.add(new_user)
|
||||
session.commit()
|
||||
await add_entity(session, new_user)
|
||||
|
||||
memory = MemoryModel(id=memory_id, user_id=user_id, methods_list=str(['Memory', 'SemanticMemory', 'EpisodicMemory']),
|
||||
attributes_list=str(['user_id', 'index_name', 'db_type', 'knowledge_source', 'knowledge_type', 'memory_id', 'long_term_memory', 'short_term_memory', 'namespace']))
|
||||
session.add(memory)
|
||||
session.commit()
|
||||
await add_entity(session, memory)
|
||||
return memory_id
|
||||
|
||||
def add_memory_instance(self, memory_class_name: str):
|
||||
async def add_memory_instance(self, memory_class_name: str):
|
||||
"""Add a new memory instance to the memory_instances list."""
|
||||
instance = DynamicBaseMemory(memory_class_name, self.user_id,
|
||||
self.memory_id, self.index_name,
|
||||
|
|
@ -209,15 +216,26 @@ class Memory:
|
|||
print("The following instance was defined", instance)
|
||||
self.memory_instances.append(instance)
|
||||
|
||||
def manage_memory_attributes(self, existing_user):
|
||||
async def query_method(self):
|
||||
methods_list = await self.session.execute(
|
||||
select(MemoryModel.methods_list).where(MemoryModel.id == self.memory_id)
|
||||
)
|
||||
methods_list = methods_list.scalar_one_or_none()
|
||||
return methods_list
|
||||
|
||||
async def manage_memory_attributes(self, existing_user):
|
||||
"""Manage memory attributes based on the user existence."""
|
||||
if existing_user:
|
||||
print(f"ID before query: {self.memory_id}, type: {type(self.memory_id)}")
|
||||
attributes_list = self.session.query(MemoryModel.attributes_list).filter_by(id=self.memory_id[0]).scalar()
|
||||
|
||||
|
||||
|
||||
# attributes_list = await self.session.query(MemoryModel.attributes_list).filter_by(id=self.memory_id[0]).scalar()
|
||||
attributes_list = await self.query_method()
|
||||
logging.info(f"Attributes list: {attributes_list}")
|
||||
if attributes_list is not None:
|
||||
attributes_list = ast.literal_eval(attributes_list)
|
||||
self.handle_attributes(attributes_list)
|
||||
await self.handle_attributes(attributes_list)
|
||||
else:
|
||||
logging.warning("attributes_list is None!")
|
||||
else:
|
||||
|
|
@ -225,20 +243,25 @@ class Memory:
|
|||
'knowledge_source', 'knowledge_type',
|
||||
'memory_id', 'long_term_memory',
|
||||
'short_term_memory', 'namespace']
|
||||
self.handle_attributes(attributes_list)
|
||||
await self.handle_attributes(attributes_list)
|
||||
|
||||
def handle_attributes(self, attributes_list):
|
||||
async def handle_attributes(self, attributes_list):
|
||||
"""Handle attributes for existing memory instances."""
|
||||
for attr in attributes_list:
|
||||
self.memory_class.add_attribute(attr)
|
||||
await self.memory_class.add_attribute(attr)
|
||||
|
||||
def manage_memory_methods(self, existing_user):
|
||||
async def manage_memory_methods(self, existing_user):
|
||||
"""
|
||||
Manage memory methods based on the user existence.
|
||||
"""
|
||||
if existing_user:
|
||||
# Fetch existing methods from the database
|
||||
methods_list = self.session.query(MemoryModel.methods_list).filter_by(id=self.memory_id).scalar()
|
||||
# methods_list = await self.session.query(MemoryModel.methods_list).filter_by(id=self.memory_id).scalar()
|
||||
|
||||
methods_list = await self.session.execute(
|
||||
select(MemoryModel.methods_list).where(MemoryModel.id == self.memory_id[0])
|
||||
)
|
||||
methods_list = methods_list.scalar_one_or_none()
|
||||
methods_list = ast.literal_eval(methods_list)
|
||||
else:
|
||||
# Define default methods for a new user
|
||||
|
|
@ -260,20 +283,20 @@ class Memory:
|
|||
return await method(*args, **kwargs)
|
||||
raise AttributeError(f"{dynamic_base_memory_instance.name} object has no attribute {method_name}")
|
||||
|
||||
def add_dynamic_memory_class(self, class_name: str, namespace: str):
|
||||
async def add_dynamic_memory_class(self, class_name: str, namespace: str):
|
||||
logging.info("Here is the memory id %s", self.memory_id[0])
|
||||
new_memory_class = DynamicBaseMemory(class_name, self.user_id, self.memory_id[0], self.index_name,
|
||||
self.db_type, namespace)
|
||||
setattr(self, f"{class_name.lower()}_class", new_memory_class)
|
||||
return new_memory_class
|
||||
|
||||
def add_attribute_to_class(self, class_instance, attribute_name: str):
|
||||
async def add_attribute_to_class(self, class_instance, attribute_name: str):
|
||||
#add this to database for a particular user and load under memory id
|
||||
class_instance.add_attribute(attribute_name)
|
||||
await class_instance.add_attribute(attribute_name)
|
||||
|
||||
def add_method_to_class(self, class_instance, method_name: str):
|
||||
async def add_method_to_class(self, class_instance, method_name: str):
|
||||
#add this to database for a particular user and load under memory id
|
||||
class_instance.add_method(method_name)
|
||||
await class_instance.add_method(method_name)
|
||||
|
||||
|
||||
|
||||
|
|
@ -297,35 +320,37 @@ async def main():
|
|||
}
|
||||
loader_settings = {
|
||||
"format": "PDF",
|
||||
"source": "url",
|
||||
"source": "URL",
|
||||
"path": "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf"
|
||||
}
|
||||
# memory_instance = Memory(namespace='SEMANTICMEMORY')
|
||||
# sss = await memory_instance.dynamic_method_call(memory_instance.semantic_memory_class, 'fetch_memories', observation='some_observation')
|
||||
#
|
||||
# Create a DB session
|
||||
Session = sessionmaker(bind=engine)
|
||||
session = Session()
|
||||
memory = Memory.create_memory("676", session, namespace='SEMANTICMEMORY')
|
||||
|
||||
# Adding a memory instance
|
||||
memory.add_memory_instance("ExampleMemory")
|
||||
from database.database_crud import session_scope
|
||||
from database.database import AsyncSessionLocal
|
||||
|
||||
async with session_scope(AsyncSessionLocal()) as session:
|
||||
memory = await Memory.create_memory("676", session, namespace='SEMANTICMEMORY')
|
||||
|
||||
# Adding a memory instance
|
||||
await memory.add_memory_instance("ExampleMemory")
|
||||
|
||||
|
||||
# Managing memory attributes
|
||||
existing_user = Memory.check_existing_user("676", session)
|
||||
print("here is the existing user", existing_user)
|
||||
memory.manage_memory_attributes(existing_user)
|
||||
# Managing memory attributes
|
||||
existing_user = await Memory.check_existing_user("676", session)
|
||||
print("here is the existing user", existing_user)
|
||||
await memory.manage_memory_attributes(existing_user)
|
||||
# aeehuvyq_semanticememory_class
|
||||
|
||||
memory.add_dynamic_memory_class('SemanticMemory', 'SEMANTICMEMORY')
|
||||
memory.add_method_to_class(memory.semanticmemory_class, 'add_memories')
|
||||
memory.add_method_to_class(memory.semanticmemory_class, 'fetch_memories')
|
||||
sss = await memory.dynamic_method_call(memory.semanticmemory_class, 'add_memories',
|
||||
observation='some_observation', params=params)
|
||||
await memory.add_dynamic_memory_class('SemanticMemory', 'SEMANTICMEMORY')
|
||||
await memory.add_method_to_class(memory.semanticmemory_class, 'add_memories')
|
||||
await memory.add_method_to_class(memory.semanticmemory_class, 'fetch_memories')
|
||||
sss = await memory.dynamic_method_call(memory.semanticmemory_class, 'add_memories',
|
||||
observation='some_observation', params=params, loader_settings=loader_settings)
|
||||
|
||||
susu = await memory.dynamic_method_call(memory.semanticmemory_class, 'fetch_memories',
|
||||
observation='some_observation')
|
||||
print(susu)
|
||||
susu = await memory.dynamic_method_call(memory.semanticmemory_class, 'fetch_memories',
|
||||
observation='some_observation')
|
||||
print(susu)
|
||||
|
||||
# Adding a dynamic memory class
|
||||
# dynamic_memory = memory.add_dynamic_memory_class("DynamicMemory", "ExampleNamespace")
|
||||
|
|
@ -337,8 +362,8 @@ async def main():
|
|||
|
||||
|
||||
# print(sss)
|
||||
# load_jack_london = await memory._add_semantic_memory(observation = "bla", loader_settings=loader_settings, params=params)
|
||||
# print(load_jack_london)
|
||||
load_jack_london = await memory._add_semantic_memory(observation = "bla", loader_settings=loader_settings, params=params)
|
||||
print(load_jack_london)
|
||||
|
||||
modulator = {"relevance": 0.1, "frequency": 0.1}
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue