QueryQuill

Revolutionize how you find and use information with intelligent search and comprehensive content analysis.

Overview

QueryQuill is a Streamlit application that integrates Google Gemini's API to create an intelligent assistant capable of interacting with uploaded documents, and fetching the latest news based on user-defined topics. The application is designed to assist users in various tasks such as researching topics, analyzing content, and staying updated with current events.

Key Features

• File Upload and Search: Upload files(PDFs) and store them in a vector database. The assistant can then answer questions related to these files.
• News Fetching: Get the latest news on a given topic with details such as the title, author and description etc.
• Intelligent Assistant: Powered by Google Gemini's latest models, the assistant uses a combination of tools (file search, code interpreter, news fetching) to answer user queries.

Installation

To install and run this application locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/Ishant-Mad/QueryQuill
   cd QueryQuill

2. Set up a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Configure API keys:

   • Create a config.py file in the project directory and add your OpenAI API key and News API key:

   API_KEY = "your-gemini-api-key"
   news_api_key = "your-news-api-key"

5. Run the application:

   streamlit run app.py

6. Access the application:

   Open your web browser and navigate to http://localhost:8501 to interact with the application.

Usage

Creating an Assistant

1. Enter a Title: This will be the name of your assistant session.
2. Initiate the First Question: Provide a prompt to start the conversation with the assistant.
3. Upload Files: Upload any files you want the assistant to reference. These files will be stored in a vector database for search and retrieval.
4. Ask Questions: Once the assistant is initialized, you can ask follow-up questions related to the uploaded files or other content.

News Fetching

• News Fetching: Provide a topic, and the assistant will fetch the latest news articles related to that topic.

Example Use Cases

• Research and Study: Upload research papers and websites related to a subject, and ask the assistant to summarize and provide insights.
• Job Preparation: Upload resumes and company profiles to receive tailored advice on job applications and interview preparation.

Requirements

• Python 3.7+
• Streamlit
• Gemini API Key
• News API Key

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.