Skip to main content

A package for automated research data collection using LLMs and Web Search API

Project description

AI Research CLI Tool

Overview

The AI Research CLI Tool is a command-line interface designed to assist users in generating structured, tabular data for research purposes. By leveraging the Bing Web Search API and the GPT-4o model, this tool transforms raw research topics into organized data that can be easily exported and utilized.

Features

  • AI-Suggested Column Headers: Automatically generate relevant column headers and descriptions for your research data.
  • Custom Header Editing: Modify or create your own headers to suit your specific research needs.
  • Data Generation: Generate between 1 to 100 rows of structured research data based on your queries.
  • Beautiful Terminal Interface: Enjoy a visually appealing and user-friendly command-line interface.
  • Export-Ready Data: Easily export the generated data in a structured format for further analysis.

Installation

To install the necessary dependencies, you can use the following command:

pip install -r requirements.txt

Usage

  1. Start the Application: Run the CLI tool from your terminal.

    python grid/cli.py
    
  2. Input Research Topic: When prompted, enter the topic you would like to research.

  3. Choose Header Creation Method:

    • Get AI Suggestions: Use the AI to generate suggested headers.
    • Create Manually: Input your own headers.
  4. Specify Number of Rows: Indicate how many rows of data you wish to generate.

  5. Data Generation: The tool will perform a web search using the Bing API and generate structured data based on the retrieved information.

  6. Export Data: The generated data will be returned in a pandas.DataFrame, ready for your use.

Requirements

  • Python 3.8 or higher
  • OpenAI API Key
  • Bing Search API Key

Environment Variables

Make sure to set the following environment variables in your .env file:

OPENAI_API_KEY=your_openai_api_key
BING_SEARCH_V7_SUBSCRIPTION_KEY=your_bing_search_api_key

Contributing

Contributions are welcome! If you have suggestions for improvements or new features, feel free to open an issue or submit a pull request.

License

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

Acknowledgments

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

grid_research-0.1.5.tar.gz (10.8 kB view details)

Uploaded Source

Built Distribution

grid_research-0.1.5-py3-none-any.whl (11.7 kB view details)

Uploaded Python 3

File details

Details for the file grid_research-0.1.5.tar.gz.

File metadata

  • Download URL: grid_research-0.1.5.tar.gz
  • Upload date:
  • Size: 10.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.1

File hashes

Hashes for grid_research-0.1.5.tar.gz
Algorithm Hash digest
SHA256 c8587dba160f4cb43d63b37fb507bb05a1c60e6ccabceef87ab6c8da35c874e9
MD5 6d85c8f953877fd10270371e2006a829
BLAKE2b-256 8843d0d45dd134238dc1730ddb2d3463f8c57ab9f74d8e3c9a0968427b2be348

See more details on using hashes here.

File details

Details for the file grid_research-0.1.5-py3-none-any.whl.

File metadata

File hashes

Hashes for grid_research-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 e4e7fcc26b7afa18f8913ff704295f62dc111d752ca5e2415fe9725a48a097a1
MD5 59f2d9dcc6f65d079f0af335e2203ebd
BLAKE2b-256 ac22aa36fd209d51d409bca03adfe74a1dd5454a75fc9177b94cffeac87d57d9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page