Internyl Program Discovery Agent

Internyl Website Repo: https://github.com/internyl-dev/internyl-frontend
Internyl Data Acquisition Repo: https://github.com/internyl-dev/internyl-ai-wrapper/tree/refactor
Internyl Website: https://internyl.org

Table of Contents

1. How to use
   • Add API Keys
   • Run main
2. How it works
   • Models
   • Tools

How to use

Add API Keys

1. Navigate to .env and input any API keys you may have there

Run main

# 1. Create a virtual environment
python -m venv .venv

# 2. Activate the virtual environment
Set-ExecutionPolicy -ExecutionPolicy Bypass -Scope Process
.venv/scripts/activate

# 3. Install requirements
pip install -r requirements.txt
playwright install

# 4. Run run.py
python run.py

How it works

The augmentor agent utilizes a LangChain agent execution chain to perform the agentic behavior. All it does is take a specific set of instructions, utilizing internet search APIs to populate missing information in a given schema.

Prompt

src/
└── prompts/
    ├── assets/
    │   └── prompt.py
    └── prompt_create.py

The model query aims at prioritizing the following:

1. Following the schema exactly
   • Never adding new sections to the schema
   • Assuming the already added information is true
   • Completely follow the directions of the structure and where to put the necessary data
2. Completely populating all fields
   • Only inputting "not provided" if truly no information can be found
3. Accuracy
   • Don't infer information
4. Efficient search methods

Tools

src/
└── tools/
    ├── content_scraper.py
    ├── ddgs_run.py
    └── links_scraper.py

Search - search (search_term:str, max_results:int)
Using the DDGS search module, return the search results given a search term.

Visit URL - visit_url (url:str)
Using Playwright return the parsed webpage contents of a URL.

Get All Links - get_all_links (url:str)
Using Playwright return all URLs found within a webpage.