Skip to main content

Small project for aiding in research and development

Project description

curious-me

Small library to ask questions, get reviews and citations of papers. Currently papers are fetched from arxiv but it can be possible to use other sources as well.

Installation

  1. Create virtual environment and activate it
python -m venv venv

In Windows

venv\Scripts\activate

In GNU/Linux

source venv/bin/activate
  1. Install package If using pip
pip install curious-me

If cloned the repo

cd curious-me/curious_me
pip install .
  1. Run the application, first open python then run the following commands
from curious_me import Curious
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
            model_name="grok-2-1212",
            temperature=0.1,
            base_url="https://api.x.ai/v1",
            api_key=<your api key>,
        )

topics = ['GPT', 'LLM', 'Decoder', 'Artificial generative Intelligence']
curious = Curious(topics=topics, llm=llm) # or Curious(topics=topics, llm=llm, skip_search=True) if you # want to search papers and build vector store again
curious.ask("What are recent advances in GPT?")
curious.get_review("RAG")
curious.get_citation(claim="Leaky ReLU is better than ReLU")

Demo

Note:

Steps for using own pdfs

  1. Clone the repo.
  2. Add your pdfs in the folder curious-me/curious_me/research_papers
  3. Run the following commands
from curious_me import Curious
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
            model_name="grok-2-1212",
            temperature=0.1,
            base_url="https://api.x.ai/v1",
            api_key=<your api key>,
        )
topics = [] # your topics
curious = Curious(topics=topics, llm=llm, skip_search=True, rebuild_vec_store=True)
curious.ask("Questions?")

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

curious_me-0.1.1.tar.gz (10.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

curious_me-0.1.1-py3-none-any.whl (12.8 kB view details)

Uploaded Python 3

File details

Details for the file curious_me-0.1.1.tar.gz.

File metadata

  • Download URL: curious_me-0.1.1.tar.gz
  • Upload date:
  • Size: 10.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.11.9

File hashes

Hashes for curious_me-0.1.1.tar.gz
Algorithm Hash digest
SHA256 42bf823ac1ea25c440e2f947ca39812a10b60b2dfc8875e00f05ecbe7db60add
MD5 f748e35fc30eca8b0065816d8ace392f
BLAKE2b-256 240168e9bbb1662b30dfeb0f81ff729dc7b5d47a2d754eb14ce10399632d8242

See more details on using hashes here.

File details

Details for the file curious_me-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: curious_me-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 12.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.11.9

File hashes

Hashes for curious_me-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6ad9184460f4a10a66e553577a61c25c2898f42ab58cd6f95cd3d3cf89f976af
MD5 83ad32beab8d773bf930a2a46ef5da40
BLAKE2b-256 2e769c32ad95cbbae5cb6fe3179f9f8e3028cff941e302fcf667bad1759111c3

See more details on using hashes here.

Supported by

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