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🧬AI Oncologist Agent

A research agent template implemented as an AI oncologist. Read papers, isolate important information, and produce actionable reports.

Altruistic AI Agents - Lilypad Oncologist

Agent Details

The AI Oncologist serves as a Research agent template that can be used to conduct a wide range of research. The Agent is an intelligent system for analyzing research papers using a multi-agent approach.

The system consists of three main agents:

Paper Relevance Agent

  • Searches through PDF documents in the documents directory

  • Uses embeddings and cosine similarity for initial filtering

  • Verifies relevance using LLM-based analysis

  • Returns a list of most relevant paper filenames

Top Paragraphs Agent

  • Extracts text from identified papers

  • Splits content into manageable chunks

  • Scores paragraph relevance using LLM

  • Returns top-scoring paragraphs with relevance scores

Text Query Agent

  • Analyzes provided text passages

  • Generates focused answers to specific queries

  • Uses contextual understanding to provide accurate responses

Getting Started

A guide to launch the Research agent locally and run inference on the Lilypad Network with the Lilypad Inference API.

Prerequisites

  • Python 3.8+

  • OpenAI API key or compatible API (e.g., DeepSeek)

  • PDF files

Installation

  1. Clone the repository:

git clone https://github.com/mavericb/ai-oncologist.git
cd ai-oncologist
  1. Install required packages:

pip install -r requirements.txt
  1. Create a .env file in the project root with the following variables:

# OpenAI-Like API configuration
BASE_URL="https://api.deepseek.com"
OPENAI_API_KEY=your_deepseek_api_key
MODEL="deepseek-chat"

ANURA_BASE_URL=https://anura-testnet.lilypad.tech
ANURA_API_KEY=your_anura_api_key
ANURA_MODEL=phi4:14b

# Search configuration
MAX_RESULTS=3
SIMILARITY_THRESHOLD=0.3
  • BASE_URL: API endpoint for OpenAI Compatible LLM service (default: "https://api.deepseek.com")

  • OPENAI_API_KEY: Your OpenAI Compatible API key (for example: DeepSeek API Docs)

  • MODEL: One OpenAI Compatible model to use (default: "deepseek-chat")

  • ANURA_BASE_URL: API endpoint for the Anura LLM service (default: "https://anura-testnet.lilypad.tech")

  • ANURA_API_KEY: Your Anura API key (get it here: Lilypad Inference API Docs)

  • ANURA_MODEL: The Anura model to use (default: "phi4:14b")

  • MAX_RESULTS: Maximum number of papers to return (default: 3)

  • SIMILARITY_THRESHOLD: Minimum similarity score for document selection (default: 0.3)

Usage

  1. Place your PDF research papers in the documents/ directory.

  2. Run the main script:

python AIOncologist.py

Resources

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