Skip to content

Latest commit

 

History

History
71 lines (48 loc) · 2.21 KB

File metadata and controls

71 lines (48 loc) · 2.21 KB

AI-Powered Research Synthesizer

This project is an AI-powered research assistant that can gather, process, and synthesize information on any given topic, leveraging the Llama 3 70B Instruct model through NVIDIA's API and the LangChain framework.

Features

  • Topic-based information gathering
  • Text summarization
  • Automatic question generation and answering
  • Information synthesis

Setup

  1. Clone this repository
  2. Install dependencies:
    pip install -r requirements.txt
    
  3. Set up your NVIDIA API key in config.py

Usage

Run the main script:

python main.py

Enter a research topic when prompted. The system will gather information, process it, and provide a synthesis including a summary and relevant questions and answers.

Example Output

Here is an example of the output you can expect:

Enter a research topic (or 'quit' to exit): Artificial Intelligence
Gathering data...
Processing data...
Synthesizing information...

Synthesis on Artificial Intelligence:

Summary: Artificial Intelligence (AI) is a branch of computer science that aims to create machines capable of intelligent behavior. It encompasses various subfields such as machine learning, natural language processing, and robotics.

Q1: What is Artificial Intelligence?
A1: Artificial Intelligence (AI) is a branch of computer science that aims to create machines capable of intelligent behavior.

Q2: What are the subfields of AI?
A2: The subfields of AI include machine learning, natural language processing, and robotics.

Q3: How is AI used in robotics?
A3: AI is used in robotics to enable machines to perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Project Structure

  • main.py: Main script to run the application
  • agents/: Contains Researcher and Synthesizer classes
  • utils/: Contains utility functions for API calls and text processing
  • config.py: Configuration file for API keys

Dependencies

  • langchain
  • requests
  • nltk

Example Outputs

To view example outputs please see the photo pdf in this folder. View the PDF