mirror of
https://github.com/EvolutionAPI/adk-python.git
synced 2025-07-13 15:14:50 -06:00
feat(memory)!: Uses the new MemoryEntry schema for all memory related components.
BREAKING CHANGE. This commit changes all memory related interface to using the newly introduced MemoryEntry class. PiperOrigin-RevId: 758464887
This commit is contained in:
parent
825f5d4f2e
commit
30947b48b8
@ -12,20 +12,31 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import random
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from datetime import datetime
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from google.adk import Agent
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from google.adk.agents.callback_context import CallbackContext
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from google.adk.tools.load_memory_tool import load_memory_tool
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from google.adk.tools.preload_memory_tool import preload_memory_tool
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from google.genai import types
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def update_current_time(callback_context: CallbackContext):
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callback_context.state['_time'] = datetime.now().isoformat()
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root_agent = Agent(
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model='gemini-2.0-flash-exp',
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model='gemini-2.0-flash-001',
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name='memory_agent',
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description='agent that have access to memory tools.',
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instruction="""
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You are an agent that help user answer questions.
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""",
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tools=[load_memory_tool, preload_memory_tool],
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before_agent_callback=update_current_time,
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instruction="""\
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You are an agent that help user answer questions.
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Current time: {_time}
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""",
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tools=[
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load_memory_tool,
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preload_memory_tool,
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],
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)
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111
contributing/samples/memory/asyncio_run.py
Executable file
111
contributing/samples/memory/asyncio_run.py
Executable file
@ -0,0 +1,111 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import asyncio
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from datetime import datetime
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from datetime import timedelta
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from typing import cast
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import warnings
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import agent
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from dotenv import load_dotenv
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from google.adk.cli.utils import logs
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from google.adk.runners import InMemoryRunner
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from google.adk.sessions import Session
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from google.genai import types
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load_dotenv(override=True)
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warnings.filterwarnings('ignore', category=UserWarning)
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logs.log_to_tmp_folder()
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async def main():
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app_name = 'my_app'
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user_id_1 = 'user1'
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runner = InMemoryRunner(
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app_name=app_name,
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agent=agent.root_agent,
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)
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async def run_prompt(session: Session, new_message: str) -> Session:
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content = types.Content(
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role='user', parts=[types.Part.from_text(text=new_message)]
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)
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print('** User says:', content.model_dump(exclude_none=True))
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async for event in runner.run_async(
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user_id=user_id_1,
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session_id=session.id,
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new_message=content,
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):
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if not event.content or not event.content.parts:
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continue
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if event.content.parts[0].text:
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print(f'** {event.author}: {event.content.parts[0].text}')
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elif event.content.parts[0].function_call:
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print(
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f'** {event.author}: fc /'
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f' {event.content.parts[0].function_call.name} /'
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f' {event.content.parts[0].function_call.args}\n'
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)
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elif event.content.parts[0].function_response:
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print(
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f'** {event.author}: fr /'
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f' {event.content.parts[0].function_response.name} /'
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f' {event.content.parts[0].function_response.response}\n'
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)
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return cast(
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Session,
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runner.session_service.get_session(
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app_name=app_name, user_id=user_id_1, session_id=session.id
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),
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)
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session_1 = runner.session_service.create_session(
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app_name=app_name, user_id=user_id_1
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)
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print(f'----Session to create memory: {session_1.id} ----------------------')
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session_1 = await run_prompt(session_1, 'Hi')
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session_1 = await run_prompt(session_1, 'My name is Jack')
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session_1 = await run_prompt(session_1, 'I like badminton.')
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session_1 = await run_prompt(
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session_1,
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f'I ate a burger on {(datetime.now() - timedelta(days=1)).date()}.',
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)
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session_1 = await run_prompt(
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session_1,
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f'I ate a banana on {(datetime.now() - timedelta(days=2)).date()}.',
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)
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print('Saving session to memory service...')
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if runner.memory_service:
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await runner.memory_service.add_session_to_memory(session_1)
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print('-------------------------------------------------------------------')
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session_2 = runner.session_service.create_session(
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app_name=app_name, user_id=user_id_1
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)
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print(f'----Session to use memory: {session_2.id} ----------------------')
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session_2 = await run_prompt(session_2, 'Hi')
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session_2 = await run_prompt(session_2, 'What do I like to do?')
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# ** memory_agent: You like badminton.
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session_2 = await run_prompt(session_2, 'When did I say that?')
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# ** memory_agent: You said you liked badminton on ...
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session_2 = await run_prompt(session_2, 'What did I eat yesterday?')
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# ** memory_agent: You ate a burger yesterday...
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print('-------------------------------------------------------------------')
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if __name__ == '__main__':
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asyncio.run(main())
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23
src/google/adk/memory/_utils.py
Normal file
23
src/google/adk/memory/_utils.py
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@ -0,0 +1,23 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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from datetime import datetime
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def format_timestamp(timestamp: float) -> str:
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"""Formats the timestamp of the memory entry."""
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return datetime.fromtimestamp(timestamp).isoformat()
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@ -12,46 +12,44 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import abc
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from __future__ import annotations
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from abc import ABC
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from abc import abstractmethod
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from typing import TYPE_CHECKING
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from pydantic import BaseModel
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from pydantic import Field
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from ..events.event import Event
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from ..sessions.session import Session
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from .memory_entry import MemoryEntry
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class MemoryResult(BaseModel):
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"""Represents a single memory retrieval result.
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Attributes:
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session_id: The session id associated with the memory.
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events: A list of events in the session.
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"""
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session_id: str
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events: list[Event]
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if TYPE_CHECKING:
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from ..sessions.session import Session
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class SearchMemoryResponse(BaseModel):
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"""Represents the response from a memory search.
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Attributes:
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memories: A list of memory results matching the search query.
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memories: A list of memory entries that relate to the search query.
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"""
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memories: list[MemoryResult] = Field(default_factory=list)
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memories: list[MemoryEntry] = Field(default_factory=list)
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class BaseMemoryService(abc.ABC):
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class BaseMemoryService(ABC):
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"""Base class for memory services.
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The service provides functionalities to ingest sessions into memory so that
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the memory can be used for user queries.
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"""
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@abc.abstractmethod
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async def add_session_to_memory(self, session: Session):
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@abstractmethod
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async def add_session_to_memory(
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self,
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session: Session,
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):
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"""Adds a session to the memory service.
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A session may be added multiple times during its lifetime.
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@ -60,9 +58,13 @@ class BaseMemoryService(abc.ABC):
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session: The session to add.
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"""
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@abc.abstractmethod
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@abstractmethod
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async def search_memory(
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self, *, app_name: str, user_id: str, query: str
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self,
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*,
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app_name: str,
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user_id: str,
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query: str,
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) -> SearchMemoryResponse:
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"""Searches for sessions that match the query.
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@ -12,11 +12,31 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ..events.event import Event
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from ..sessions.session import Session
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from __future__ import annotations
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import re
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from typing import TYPE_CHECKING
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from typing_extensions import override
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from . import _utils
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from .base_memory_service import BaseMemoryService
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from .base_memory_service import MemoryResult
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from .base_memory_service import SearchMemoryResponse
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from .memory_entry import MemoryEntry
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if TYPE_CHECKING:
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from ..events.event import Event
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from ..sessions.session import Session
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def _user_key(app_name: str, user_id: str):
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return f'{app_name}/{user_id}'
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def _extract_words_lower(text: str) -> set[str]:
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"""Extracts words from a string and converts them to lowercase."""
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return set([word.lower() for word in re.findall(r'[A-Za-z]+', text)])
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class InMemoryMemoryService(BaseMemoryService):
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@ -26,37 +46,49 @@ class InMemoryMemoryService(BaseMemoryService):
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"""
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def __init__(self):
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self.session_events: dict[str, list[Event]] = {}
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"""keys are app_name/user_id/session_id"""
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self._session_events: dict[str, dict[str, list[Event]]] = {}
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"""Keys are app_name/user_id, session_id. Values are session event lists."""
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@override
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async def add_session_to_memory(self, session: Session):
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key = f'{session.app_name}/{session.user_id}/{session.id}'
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self.session_events[key] = [
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event for event in session.events if event.content
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user_key = _user_key(session.app_name, session.user_id)
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self._session_events[user_key] = self._session_events.get(
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_user_key(session.app_name, session.user_id), {}
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)
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self._session_events[user_key][session.id] = [
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event
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for event in session.events
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if event.content and event.content.parts
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]
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@override
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async def search_memory(
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self, *, app_name: str, user_id: str, query: str
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) -> SearchMemoryResponse:
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"""Prototyping purpose only."""
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keywords = set(query.lower().split())
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user_key = _user_key(app_name, user_id)
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if user_key not in self._session_events:
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return SearchMemoryResponse()
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words_in_query = set(query.lower().split())
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response = SearchMemoryResponse()
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for key, events in self.session_events.items():
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if not key.startswith(f'{app_name}/{user_id}/'):
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continue
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matched_events = []
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for event in events:
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for session_events in self._session_events[user_key].values():
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for event in session_events:
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if not event.content or not event.content.parts:
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continue
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parts = event.content.parts
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text = '\n'.join([part.text for part in parts if part.text]).lower()
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for keyword in keywords:
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if keyword in text:
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matched_events.append(event)
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break
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if matched_events:
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session_id = key.split('/')[-1]
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response.memories.append(
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MemoryResult(session_id=session_id, events=matched_events)
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words_in_event = _extract_words_lower(
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' '.join([part.text for part in event.content.parts if part.text])
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)
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if not words_in_event:
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continue
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if any(query_word in words_in_event for query_word in words_in_query):
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response.memories.append(
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MemoryEntry(
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content=event.content,
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author=event.author,
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timestamp=_utils.format_timestamp(event.timestamp),
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)
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)
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return response
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@ -16,6 +16,7 @@ from collections import OrderedDict
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import json
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import os
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import tempfile
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from typing import Optional
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from google.genai import types
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from typing_extensions import override
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@ -23,9 +24,10 @@ from vertexai.preview import rag
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from ..events.event import Event
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from ..sessions.session import Session
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from . import _utils
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from .base_memory_service import BaseMemoryService
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from .base_memory_service import MemoryResult
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from .base_memory_service import SearchMemoryResponse
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from .memory_entry import MemoryEntry
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class VertexAiRagMemoryService(BaseMemoryService):
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@ -33,8 +35,8 @@ class VertexAiRagMemoryService(BaseMemoryService):
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def __init__(
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self,
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rag_corpus: str = None,
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similarity_top_k: int = None,
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rag_corpus: Optional[str] = None,
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similarity_top_k: Optional[int] = None,
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vector_distance_threshold: float = 10,
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):
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"""Initializes a VertexAiRagMemoryService.
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@ -47,8 +49,10 @@ class VertexAiRagMemoryService(BaseMemoryService):
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vector_distance_threshold: Only returns contexts with vector distance
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smaller than the threshold..
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"""
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self.vertex_rag_store = types.VertexRagStore(
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rag_resources=[rag.RagResource(rag_corpus=rag_corpus)],
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self._vertex_rag_store = types.VertexRagStore(
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rag_resources=[
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types.VertexRagStoreRagResource(rag_corpus=rag_corpus),
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],
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similarity_top_k=similarity_top_k,
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vector_distance_threshold=vector_distance_threshold,
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)
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@ -79,7 +83,11 @@ class VertexAiRagMemoryService(BaseMemoryService):
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output_string = "\n".join(output_lines)
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temp_file.write(output_string)
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temp_file_path = temp_file.name
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for rag_resource in self.vertex_rag_store.rag_resources:
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if not self._vertex_rag_store.rag_resources:
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raise ValueError("Rag resources must be set.")
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for rag_resource in self._vertex_rag_store.rag_resources:
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rag.upload_file(
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corpus_name=rag_resource.rag_corpus,
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path=temp_file_path,
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@ -97,10 +105,10 @@ class VertexAiRagMemoryService(BaseMemoryService):
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"""Searches for sessions that match the query using rag.retrieval_query."""
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response = rag.retrieval_query(
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text=query,
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rag_resources=self.vertex_rag_store.rag_resources,
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rag_corpora=self.vertex_rag_store.rag_corpora,
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similarity_top_k=self.vertex_rag_store.similarity_top_k,
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vector_distance_threshold=self.vertex_rag_store.vector_distance_threshold,
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rag_resources=self._vertex_rag_store.rag_resources,
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rag_corpora=self._vertex_rag_store.rag_corpora,
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similarity_top_k=self._vertex_rag_store.similarity_top_k,
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vector_distance_threshold=self._vertex_rag_store.vector_distance_threshold,
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)
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memory_results = []
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@ -144,9 +152,16 @@ class VertexAiRagMemoryService(BaseMemoryService):
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for session_id, event_lists in session_events_map.items():
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for events in _merge_event_lists(event_lists):
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sorted_events = sorted(events, key=lambda e: e.timestamp)
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memory_results.append(
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MemoryResult(session_id=session_id, events=sorted_events)
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)
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memory_results.extend([
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MemoryEntry(
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author=event.author,
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content=event.content,
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timestamp=_utils.format_timestamp(event.timestamp),
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)
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for event in sorted_events
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if event.content
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])
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return SearchMemoryResponse(memories=memory_results)
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|
@ -18,7 +18,9 @@ import asyncio
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import logging
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import queue
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import threading
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from typing import AsyncGenerator, Generator, Optional
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from typing import AsyncGenerator
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from typing import Generator
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from typing import Optional
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import warnings
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|
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from deprecated import deprecated
|
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|
30
src/google/adk/tools/_memory_entry_utils.py
Normal file
30
src/google/adk/tools/_memory_entry_utils.py
Normal file
@ -0,0 +1,30 @@
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# Copyright 2025 Google LLC
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
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#
|
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# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ..memory.memory_entry import MemoryEntry
|
||||
|
||||
|
||||
def extract_text(memory: MemoryEntry, splitter: str = ' ') -> str:
|
||||
"""Extracts the text from the memory entry."""
|
||||
if not memory.content.parts:
|
||||
return ''
|
||||
return splitter.join(
|
||||
[part.text for part in memory.content.parts if part.text]
|
||||
)
|
@ -17,19 +17,25 @@ from __future__ import annotations
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from google.genai import types
|
||||
from openai import BaseModel
|
||||
from pydantic import Field
|
||||
from typing_extensions import override
|
||||
|
||||
from ..memory.memory_entry import MemoryEntry
|
||||
from .function_tool import FunctionTool
|
||||
from .tool_context import ToolContext
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ..memory.base_memory_service import MemoryResult
|
||||
from ..models import LlmRequest
|
||||
|
||||
|
||||
class LoadMemoryResponse(BaseModel):
|
||||
memories: list[MemoryEntry] = Field(default_factory=list)
|
||||
|
||||
|
||||
async def load_memory(
|
||||
query: str, tool_context: ToolContext
|
||||
) -> 'list[MemoryResult]':
|
||||
) -> LoadMemoryResponse:
|
||||
"""Loads the memory for the current user.
|
||||
|
||||
Args:
|
||||
@ -38,12 +44,15 @@ async def load_memory(
|
||||
Returns:
|
||||
A list of memory results.
|
||||
"""
|
||||
response = await tool_context.search_memory(query)
|
||||
return response.memories
|
||||
search_memory_response = await tool_context.search_memory(query)
|
||||
return LoadMemoryResponse(memories=search_memory_response.memories)
|
||||
|
||||
|
||||
class LoadMemoryTool(FunctionTool):
|
||||
"""A tool that loads the memory for the current user."""
|
||||
"""A tool that loads the memory for the current user.
|
||||
|
||||
NOTE: Currently this tool only uses text part from the memory.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(load_memory)
|
||||
|
@ -14,11 +14,11 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from typing_extensions import override
|
||||
|
||||
from . import _memory_entry_utils
|
||||
from .base_tool import BaseTool
|
||||
from .tool_context import ToolContext
|
||||
|
||||
@ -27,7 +27,10 @@ if TYPE_CHECKING:
|
||||
|
||||
|
||||
class PreloadMemoryTool(BaseTool):
|
||||
"""A tool that preloads the memory for the current user."""
|
||||
"""A tool that preloads the memory for the current user.
|
||||
|
||||
NOTE: Currently this tool only uses text part from the memory.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
# Name and description are not used because this tool only
|
||||
@ -41,29 +44,35 @@ class PreloadMemoryTool(BaseTool):
|
||||
tool_context: ToolContext,
|
||||
llm_request: LlmRequest,
|
||||
) -> None:
|
||||
parts = tool_context.user_content.parts
|
||||
if not parts or not parts[0].text:
|
||||
user_content = tool_context.user_content
|
||||
if (
|
||||
not user_content
|
||||
or not user_content.parts
|
||||
or not user_content.parts[0].text
|
||||
):
|
||||
return
|
||||
query = parts[0].text
|
||||
response = await tool_context.search_memory(query)
|
||||
|
||||
user_query: str = user_content.parts[0].text
|
||||
response = await tool_context.search_memory(user_query)
|
||||
if not response.memories:
|
||||
return
|
||||
memory_text = ''
|
||||
|
||||
memory_text_lines = []
|
||||
for memory in response.memories:
|
||||
time_str = datetime.fromtimestamp(memory.events[0].timestamp).isoformat()
|
||||
memory_text += f'Time: {time_str}\n'
|
||||
for event in memory.events:
|
||||
# TODO: support multi-part content.
|
||||
if (
|
||||
event.content
|
||||
and event.content.parts
|
||||
and event.content.parts[0].text
|
||||
):
|
||||
memory_text += f'{event.author}: {event.content.parts[0].text}\n'
|
||||
if time_str := (f'Time: {memory.timestamp}' if memory.timestamp else ''):
|
||||
memory_text_lines.append(time_str)
|
||||
if memory_text := _memory_entry_utils.extract_text(memory):
|
||||
memory_text_lines.append(
|
||||
f'{memory.author}: {memory_text}' if memory.author else memory_text
|
||||
)
|
||||
if not memory_text_lines:
|
||||
return
|
||||
|
||||
full_memory_text = '\n'.join(memory_text_lines)
|
||||
si = f"""The following content is from your previous conversations with the user.
|
||||
They may be useful for answering the user's current query.
|
||||
<PAST_CONVERSATIONS>
|
||||
{memory_text}
|
||||
{full_memory_text}
|
||||
</PAST_CONVERSATIONS>
|
||||
"""
|
||||
llm_request.append_instructions([si])
|
||||
|
Loading…
Reference in New Issue
Block a user