Simple LLM Memory
Project description
Memento
Simple LLM Memory.
Memento automatically manages your conversations with LLMs with just 3 lines of code. It leverages SQLAlchemy and Alembic to store conversations between users and assistants in SQLite3 or in memory.
Getting Started
To install Memento, run pip install memento-llm
in your terminal.
With Memento, you no longer have to worry about setting up message storage logic in your application, here is how I can be integrated into your code:
from openai import OpenAI
from memento import Memento
client = OpenAI()
### Stores message history in-memory.
memory = Memento()
@memory ### Memento provides a decorator for your LLM generation function.
def generate():
return client.chat.completions.create(
model="gpt-3.5-turbo",
# messages=[ ### No longer worry about the message parameter.
# {"role": "user", "content": "Extract Jason is 25 years old"},
# ],
)
response_1 = generate("My name is Anibal")
print(response_1) # Output: Hello Anibal!
response_2 = generate("What´s my name?")
print(response_2) # Output: Your name is Anibal.
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