Internet-Access-to-LLM

This repository provides a framework to integrate internet search capabilities with a Language Learning Model (LLM), specifically using Gemini 1.5 API. This allows the LLM to fetch and use real-time data from the internet to enhance its responses to user queries.

Features

• Keyword Extraction: Uses KeyBERT to extract relevant keywords from the user's prompt.
• Internet Search: Utilizes DuckDuckGo Search API to gather articles, videos, and images based on extracted keywords.
• Zero-Shot Classification: Employs a zero-shot classifier to decide whether a query needs internet search or can be answered using the LLM's knowledge.
• Integration with Gemini 1.5: Connects with Gemini 1.5 API for generating responses.

Installation

1. Clone the repository:

   git clone https://github.com/LikithMeruvu/Internet-Access-to-LLM.git
   cd Internet-Access-to-LLM

2. Install the required dependencies:

   pip install -r requirements.txt

3. Set up your API keys:

   • Replace GEMINI_API_KEY in the code with your Gemini API key.

Usage

Go to Main.py and Update the genai.config with your gemini api key !!

To run the program, execute the following command:

python main.py

Code Overview

Keyword Extraction

The keyword_extractor function uses KeyBERT to extract top keywords from the user's prompt. These keywords are then used for internet search.

def keyword_extractor(prompts):
    ...

Internet Search

The DuckDuckGoSearcher class handles searching for articles, videos, and images using DuckDuckGo's API.

class DuckDuckGoSearcher:
    ...

Zero-Shot Classification

This classifier decides whether a query requires internet search based on the prompt.

classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
...

Generating Responses

Depending on the classification result, the program either uses the LLM's knowledge or performs an internet search to gather additional information before generating a response.

def get_response(prompt):
    ...

Example

Here's how the process works:

1. User Input: The user provides a query.
2. Classification: The query is classified to determine if internet search is needed.
3. Keyword Extraction: Relevant keywords are extracted from the query.
4. Internet Search: If required, the program performs an internet search and gathers data.
5. Response Generation: The LLM generates a response, optionally using the gathered data.

Contributing

Contributions are welcome! Please submit a pull request or open an issue for any feature requests or bug reports.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or suggestions, please open an issue or contact the repository owner.