langassist 0.0.9

The framework for language assistants

Assistants

Developing language assistants with LLMs in a low-code way.

Quick Install

Install using pip:

pip install langassist

The framework requires a database to register the assistants. The default database used is MongoAtlas. Future versions of the framework will support additional database types. Currently, there is a MongoDB collection named assistants which registers each assistant as shown below:

_id : 6556db6cf114addad09420c6
assistant_name: "test_assist"
assistant_id: "asst_52TLl1OdJW6ulmLCEsDlizz8"
file_id: "file-lZUBJ3ZnxtkTfqsuE0WYMXDI"

What are Assistants?

Assistants is a framework for developing language-based assistants using micro agents, akin to the microservices concept. Each micro agent, like a microservice, can be independently developed and deployed. The framework adheres to the Single Responsibility Principle (SRP), allowing these assistants to be combined to address complex business processes through workflows.

Capabilities of the Framework

In time, the framework will include built-in assistants for immediate deployment within OpenAI environments. It will also support the development of custom assistants.

Contribution

Contributions are welcome in any form, be it through new features or improved documentation.

Example Usage

The repository includes various examples demonstrating framework usage.

# This is an example that shows how to use and deploy the summarization agent
# Deploy the agent first
# and then run the assistant
import os

from assistants.langassist.summarize_assistant import SummarizeAssistant

from dotenv import load_dotenv

from assistants.langregister.mongo_db_atlas import MongoAtlas

load_dotenv()
OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY')
MONGO_PASSWORD = os.getenv("MONGO_PASSWORD")

mongo_client = MongoAtlas()
mongo_client.uri = "mongodb+srv://rajib76:{MONGO_PASSWORD}@cluster0.cp3rxai.mongodb.net/?retryWrites=true&w=majority".format(
    MONGO_PASSWORD=MONGO_PASSWORD)

assistant_name = "summarize_assistant_03"
file = "gen_ai.pdf"
def deploy_assistant():
    sc = SummarizeAssistant(file=file,assistant_name=assistant_name)
    fileobj, assistantobj = sc.deploy_assistant(mongo_client)
    print(fileobj,assistantobj)

def run_assistant():
    sc = SummarizeAssistant(assistant_name=assistant_name)
    question = "Summarize the content in 300 words. Please ensure all points are covered"
    print(sc.run_assistant(question,client=mongo_client))



if __name__ == "__main__":
    # First deploy
    # deploy_assistant()

    #Then run
    run_assistant()