athulnairrr / OneLastTime

Team OneLastTime project for the KLEOS 2.0 2024 hackathon

OneLastTime

Team OneLastTime project for the KLEOS 2.0 2024 hackathon

Checkout the Demo here »

Problem Statement:

Tentative System Architecture:

• The User first sends a query to the LLM.

• The LLM takes the user's query and checks it against the vector database (Qdrant) - This database will contain verified and trusted health information

• If the data is present in database, then send the response back to the user.

• If the data is not present, then using AI Agent, we will do a web search on the user's query (we will use CrewAI and SerperAPI).

• This web scraped data will be then sent to a panel of Medical experts, who will verify the data.

• This result will also be shown to the user, with a warning saying

  ⚠️ This data was taken from the web with these sources [....]: Please wait for our Medical experts to verify the data.

• When the Medical experts verify the data, the user will be informed.

• In case, the results from the web is wrong, the the Medical Expert can send their own trusted opinion to the user.

• This final trusted and verified source will also be added to the vector database, making an ever growing set of perfect data. 🤗

Tasks:

PART 1: Backend Pipeline

• Create a Notebook in which we will experiment AI Agents
• Create a AI Agent for searching the web and summarising the scraped results
• Test different prompts to verify which gives the best results
• Create a Notebook to push the dataset into the database (Qdrant)
• Check the threshold and FAITHFUL score of the database to ensure that the LLM can retrieve the data correctly (RAG)

PART 2: Backend

• Integrate the various pipeline into a single backend file (We will use FastAPI)

• Create a MongoDB database for storing logs and Medical Expert's details.

• Develop the workflow for connecting the API calls between the Medical Experts, the LLM and the users.

• Email Notification Service

PART 3: Frontend

• Create a demo frontend to show working of backend.
• Create a landing page.
• Create a Chat Page for user to interact with.
• Create a Medical Expert page where they can validate and verify the user's query.

Sources:

• Dataset Used: https://www.huggingface.co/datasets/lavita/ChatDoctor-HealthCareMagic-100k?row=36
• CrewAI: https://docs.crewai.com/
• Serper API: https://www.serper.dev
• Qdrant: https://cloud.qdrant.io
• https://arxiv.org/html/2402.04620v1
• https://www.analyticsvidhya.com/blog/2024/06/agentic-workflow-with-crewai-and-groq/