semvec/pypi-packages huggingface dataset:
tidytcells 2.2.0
Standardise TR/MH data
Requires Python: >=3.8
Keywords: immunology, bioinformatics, TCR, TR, MHC, MH, HLA, T cell, IMGT

<div align="center">

<img src="https://raw.githubusercontent.com/yutanagano/tidytcells/main/tidytcells.png" width=700>
<br><br>

![Tests](https://github.com/yutanagano/tidytcells/actions/workflows/tests.yaml/badge.svg)
[![Docs](https://readthedocs.org/projects/tidytcells/badge/?version=latest)](https://tidytcells.readthedocs.io)
[![License](https://img.shields.io/badge/license-MIT-blue)](https://github.com/yutanagano/tidytcells?tab=MIT-1-ov-file#readme)
[![DOI](https://img.shields.io/badge/DOI-10.3389/fimmu.2023.1276106-pink)](https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106)

### Check out the [documentation page](https://tidytcells.readthedocs.io).

</div>

---

`tidytcells` is a lightweight python package that cleans and standardizes T cell receptor (TR), Major Histocompatibility (MH), and Immunoglobulin (IG) data to be [IMGT](https://www.imgt.org/)-compliant.
The main purpose of the package is to solve the problem of parsing and collating together non-standardized TR datasets.
It is often difficult to compile TR data from multiple sources because the formats/nomenclature of how each dataset encodes TR and MH gene names are slightly different, or even inconsistent within themselves.
`tidytcells` can ameliorate this issue by auto-correcting and auto-standardizing your data.

## Installation

```bash
$ pip install tidytcells
```

## Citing tidytcells

Please cite [our manuscript](https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106).

### BibTex

```bibtex
@ARTICLE{10.3389/fimmu.2023.1276106,
         AUTHOR={Nagano, Yuta  and Chain, Benjamin },
         TITLE={tidytcells: standardizer for TR/MH nomenclature},
         JOURNAL={Frontiers in Immunology},
         VOLUME={14},
         YEAR={2023},
         URL={https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1276106},
         DOI={10.3389/fimmu.2023.1276106},
         ISSN={1664-3224}
}
```
llm-station 1.0.1
Agent framework with tool calling for OpenAI, Anthropic, and Google
Requires Python: >=3.9
Keywords: llm, agents, tools, openai, anthropic, gemini, smart-tools, ai, chatgpt, claude, gemini

# LLM Station

A unified, provider-agnostic agent framework for OpenAI, Google Gemini, and Anthropic Claude with tool integration.

## Quick Start

### Install
```bash
# Install from PyPI (recommended)
pip install llm-station

# Optional: Install with specific provider support
pip install llm-station[openai]     # OpenAI only
pip install llm-station[anthropic]  # Anthropic only  
pip install llm-station[google]     # Google only
pip install llm-station[all]        # All providers

# Development install
git clone https://github.com/your-repo/llm_station.git
cd llm_station
pip install -e .[dev]
```

### Set Up API Keys
```bash
# Add to .env file
echo "OPENAI_API_KEY=your-openai-key" >> .env
echo "GEMINI_API_KEY=your-gemini-key" >> .env  
echo "ANTHROPIC_API_KEY=your-anthropic-key" >> .env
```

### Use Any Provider
```python
from llm_station import Agent
from dotenv import load_dotenv
import os

load_dotenv()

# Same interface, any provider
agent = Agent(
    provider="openai", # or "google", "anthropic"
    model="gpt-4o-mini",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Basic chat
response = agent.generate("What is machine learning?")
print(response.content)

# Use tools with simple, memorable names
response = agent.generate(
    "Search for recent AI developments",
    tools=["search"]  # Auto-routes to best search provider
)

print(response.content)
if response.grounding_metadata:
    sources = response.grounding_metadata.get("sources", [])
    print(f"Found {len(sources)} sources")

# Multiple tools work together
response = agent.generate(
    "Research AI trends, analyze the data, and create a summary",
    tools=["search", "code", "json"]
)
```

## Documentation

- **[OPENAI.md](OPENAI.md)** - OpenAI provider setup and tools
- **[GOOGLE.md](GOOGLE.md)** - Google Gemini provider setup and tools  
- **[CLAUDE.md](CLAUDE.md)** - Anthropic Claude provider setup and tools