semvec/pypi-packages huggingface dataset:
task-refiner-llm 2025.9.92037
Refine unstructured briefs into implementation-ready JSON via LLM7 and llmatch.
Requires Python: >=3.11

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# task_refiner_llm  
  
`task_refiner_llm` is a Python package that provides a function to convert loose user briefs into structured, implementation-ready task descriptions formatted in strict JSON. It leverages language models with robust extraction techniques to ensure precise, usable output for software engineering tasks.  
  
## Installation  
  
Install via pip:  
  
```bash  
pip install task_refiner_llm  
```  
  
## Usage  
  
The main function, `task_refiner_llm`, accepts an LLM instance and a raw user brief to return a structured JSON object describing the refined task. If no LLM is provided, it initializes a deterministic `ChatLLM7`. The function employs `llmatch` for reliable extraction of JSON from LLM output, raising errors if extraction or parsing fails.  
  
### Example  
  
```python  
from langchain_core.language_models import BaseChatModel  
from task_refiner_llm import refine_task_with_llm  
  
# Optional: create your own LLM or pass None to use default  
result = refine_task_with_llm(  
    llm=None,  
    custom_text="Create a script to analyze sales data and generate a report.",  
    project_name="SalesAnalysis",  
    audience="junior developer",  
    include_examples=True  
)  
  
print(result)  
```  
  
This call refines an unstructured brief into a detailed, JSON-formatted task description suitable for implementation.  
  
## Author  
  
Author: Eugene Evstafev <hi@eugene.plus>  
Repository: https://github.com/chigwell/refine_task_with_llm
ffcapcha 1.3.8
service is aimed at protecting telegram bots from suspicious requests and DDoS attacks. Documentation about the module and resource news -> https://t.me/ffcapcha
Requires Python: >=3.7

# FFcapcha

Thank you for installing FF.capcha. Our service is aimed at protecting telegram bots from suspicious requests and DDoS attacks. Documentation about the module and resource news -> https://t.me/ffcapcha

powered by Vnd.FF, pavyk, gilov

## Installation

```bash
pip install ffcapcha