histextractor 2025.12.21165426
A new package that extracts and structures key historical facts and insights from textual descriptions of historical events, such as the Lend-Lease program during World War II. The package takes a tex
License: MIT
Requires Python: >=3.9

# `histextractor`
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[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
[![Downloads](https://static.pepy.tech/badge/histextractor)](https://pepy.tech/project/histextractor)
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`histextractor` is a lightweight Python package that extracts and structures key historical facts from natural‑language descriptions of historical events.  
Given a text passage such as a summary of the Lend‑Lease program during World War II, the package returns a list of structured strings containing the main participants, key actions, outcomes, and notable controversies. The output follows a consistent format, making it ideal for educational tools, research databases, or historical analysis platforms.

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## 📦 Installation

```bash
pip install histextractor
```

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## 🚀 Quick Start

```python
from histextractor import histextractor

user_input = """
The Lend‑Lease program was a U.S. policy during World War II that supplied Allied nations
with military aid. It involved the United States sending vehicles, weapons, and supplies
to the United Kingdom, the Soviet Union, China, and others. This assistance was crucial
in sustaining Allied forces before the U.S. formally entered the war.
"""

# Use the default ChatLLM7
response = histextractor(user_input)

for idx, item in enumerate(response, 1):
    print(f"{idx}. {item}")
```

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## 📚 How `histextractor` Works

1. **LLM Choice**  
   - By default, the package uses **ChatLLM7** from `langchain_llm7`.  
   - You can overwrite this by passing any `langchain` compatible `BaseChatModel`.

2. **API Key**  
   - If you do not specify an `api_key`, the function will look for the environment
     variable `LLM7_API_KEY`.  
   - If that is also missing, it will fall back to the string `"None"`, which still
     triggers the credentials that the free tier of LLM7 provides.

3. **Output Format**  
   - The function returns a `List[str]`.  
   - Each entry in the list follows the regex pattern defined in `pattern.py`, ensuring
     consistent structure.

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## 🔌 Custom LLM Examples

### Using OpenAI

```python
from langchain_openai import ChatOpenAI
from histextractor import histextractor

llm = ChatOpenAI()
response = histextractor(user_input, llm=llm)
```

### Using Anthropic

```python
from langchain_anthropic import ChatAnthropic
from histextractor import histextractor

llm = ChatAnthropic()
response = histextractor(user_input, llm=llm)
```

### Using Google Gemini

```python
from langchain_google_genai import ChatGoogleGenerativeAI
from histextractor import histextractor

llm = ChatGoogleGenerativeAI()
response = histextractor(user_input, llm=llm)
```

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## ⚙️ Rate Limits & API Keys

- **LLM7 Free Tier** rate limits are sufficient for most use cases.
- For higher limits, provide your own API key via:
  - Environment variable: `export LLM7_API_KEY=your_key_here`  
  - Parameter: `histextractor(user_input, api_key="your_key_here")`
- Obtain a free API key at: https://token.llm7.io/

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## 🐛 Issues & Feedback

Please file issues at:
https://github.com/chigwell/histextractor/issues

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## 👤 Author

- **Eugene Evstafev**  
  Email: hi@euegne.plus  
  GitHub: [chigwell](https://github.com/chigwell)

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