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README

Discus

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⚡ Quick Install

pip install discus

for the most recent version please do pip install discus@git+https://github.com/discus-labs/discus

📖 Documentation

https://discus.ai/docs/index.html

🏷 What is Discus

Access to high-quality and large datasets is critical when it comes to ML testing/evaluation. Discus is a Python library that leverages LLM's to generate user guided data to solve this critical problem.

Keep up with updates on our twitter or our discord.

Get Started with Discus

Here are a few quick steps to get Discus working.

After installing Discus, make sure to integrate in your LLM provider. For example,

export OPENAI_API_KEY=your-api-key-here

We can now get started. First, create your json following these guidelines:

  • task_name: what you want to call your task
  • task_type: the type of data you want to generate. Currently either LLM-Instances or LLM-Instructions
  • task_explained: the specific guidelines of your task.
  • generated_dataset_name: what you want the returned csv to be called.
  • model_provider: the LLM you want to use. Currently only OpenAI.
  • model_name: the exact model from your provider.
  • number_of_rows: the number of data points you want to generate/enrich
config = {
    "task_name": "English2Spanish",
    "task_type": "LLM-Instances",
    "task_explained": "generate english to spanish translation.", # fill in the blank. "you are trying to _____"
    "generated_dataset_name": "eng2spanish.csv",
    "model_provider": "openai",
    "model_name": "gpt-3.5-turbo",
    "number_of_rows": "1500"
}

To run, import Discus. Then, create a Generator object.

from discus import Generator

discus = Generator(config = "config_file_path")
generated_data = discus.run()

Achieve better results by providing your model with a seed dataset.

discus = Generator(config = "config_file_path", seed_dataset = "csv_file_path")
generated_data = discus.run()

Support

Discus is a rapidly developing project. We welcome contributions in all forms - bug reports, pull requests and ideas for improving the library.

Open an issue on Github for bugs and request features. Grab an open issue, and submit a pull request! Discus is a rapidly developing project. We welcome contributions in all forms - bug reports, pull requests and ideas for improving the library.

  1. Open an issue on Github for bugs and request features.
  2. Grab an open issue, and submit a pull request!

Core symbols most depended-on inside this repo

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Method 35
Class 11
Function 8

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Python100%

Modules by API surface

src/discus/knowledge.py9 symbols
src/discus/datasets/dataset.py9 symbols
src/discus/knowledge_old.py5 symbols
src/discus/generator.py5 symbols
src/discus/operations/instruction.py4 symbols
src/discus/operations/instance.py4 symbols
src/discus/models/openai.py4 symbols
src/discus/models/huggingface.py4 symbols
src/discus/json/config.py4 symbols
src/discus/schema.py3 symbols
src/discus/json/architecture.py3 symbols

For agents

$ claude mcp add discus \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact

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