From ce0d458386749a2440d0a2a26ec5acebfac042cb Mon Sep 17 00:00:00 2001 From: balabanovan530 <175+balabanovan530@noreply.localhost> Date: Thu, 28 May 2026 13:40:46 +0000 Subject: [PATCH] Update README.md --- README.md | 60 ++++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 59 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 7284513..c996149 100644 --- a/README.md +++ b/README.md @@ -1 +1,59 @@ - \ No newline at end of file +# Task Card Processor + +This project extracts a structured task card from a raw user text using a single LLM call and a Pydantic parser. + +## Installation + +```bash +# Create a virtual environment (recommended) +python -m venv .venv +source .venv/bin/activate # On Windows use .venv\Scripts\activate + +# Install dependencies +pip install -r requirements.txt +``` + +## Configuration + +The script uses OpenAI API. Set the following environment variables before running: + +- `OPENAI_API_KEY` – your OpenAI API key. +- `OPENAI_API_BASE` (optional) – override the default OpenAI base URL if you use a local LLM. + +## Usage + +You can pipe raw text into the script or provide it as a command‑line argument. + +```bash +# From stdin +cat raw_text.txt | python agent.py + +# As an argument +python agent.py "Generate a task card for a math homework assignment." +``` + +The script prints a validated JSON object followed by a short summary. + +## Example Output + +```json +--- Task Card JSON --- +{ + "title": "Math Homework", + "subject": "Algebra", + "deadline_hint": "Next Friday", + "deliverable_type": "Problem set", + "grading_hints": "Include solutions and explanations" +} + +--- Summary --- +Title: Math Homework +Subject: Algebra +Deadline: Next Friday +Deliverable: Problem set +Grading hints: Include solutions and explanations +``` + +## License + +MIT License.