The framework for language assistants
Project description
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()
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