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phenomenon-interpreter\n[![PyPI version](https://badge.fury.io/py/phenomenon-interpreter.svg)](https://badge.fury.io/py/phenomenon-interpreter)\n[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)\n[![Downloads](https://static.pepy.tech/badge/phenomenon-interpreter)](https://pepy.tech/project/phenomenon-interpreter)\n[![LinkedIn](https://img.shields.io/badge/LinkedIn-blue)](https://www.linkedin.com/in/eugene-evstafev-716669181/)\n\n\nA Python package for interpreting user-submitted text about natural or scientific phenomena, extracting structured insights, and classifying events based on textual input.\n\n---\n\n## 📌 Overview\n`phenomenon_interpreter` is designed to analyze free-form descriptions of phenomena (e.g., solar storms, earthquakes, or other natural events) and generate structured summaries or classifications. It leverages large language models (LLMs) to extract domain-specific insights from unstructured text, enabling automated analysis without requiring multimedia processing.\n\n---\n\n## 🚀 Installation\nInstall the package via pip:\n\n```bash\npip install phenomenon_interpreter\n```\n\n---\n\n## 🔧 Usage\n\n### Basic Usage (Default LLM: ChatLLM7)\n```python\nfrom phenomenon_interpreter import phenomenon_interpreter\n\nuser_input = \"A massive solar storm caused radio blackouts in Australia today.\"\nresponse = phenomenon_interpreter(user_input)\nprint(response)  # Structured output based on the input\n```\n\n### Custom LLM Integration\nYou can replace the default `ChatLLM7` with any LangChain-compatible LLM (e.g., OpenAI, Anthropic, Google Generative AI). Example:\n\n#### Using OpenAI:\n```python\nfrom langchain_openai import ChatOpenAI\nfrom phenomenon_interpreter import phenomenon_interpreter\n\nllm = ChatOpenAI()\nresponse = phenomenon_interpreter(user_input, llm=llm)\n```\n\n#### Using Anthropic:\n```python\nfrom langchain_anthropic import ChatAnthropic\nfrom phenomenon_interpreter import phenomenon_interpreter\n\nllm = ChatAnthropic()\nresponse = phenomenon_interpreter(user_input, llm=llm)\n```\n\n#### Using Google Generative AI:\n```python\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom phenomenon_interpreter import phenomenon_interpreter\n\nllm = ChatGoogleGenerativeAI()\nresponse = phenomenon_interpreter(user_input, llm=llm)\n```\n\n---\n\n## 🔑 API Key Configuration\nBy default, the package uses `ChatLLM7` with an API key fetched from the environment variable `LLM7_API_KEY`. You can:\n1. Set it via environment variable:\n   ```bash\n   export LLM7_API_KEY=\"your_api_key_here\"\n   ```\n2. Pass it directly:\n   ```python\n   from phenomenon_interpreter import phenomenon_interpreter\n   response = phenomenon_interpreter(user_input, api_key=\"your_api_key_here\")\n   ```\n\nGet a free API key from [LLM7](https://token.llm7.io/).\n\n---\n\n## 📝 Parameters\n| Parameter | Type               | Description                                                                 |\n|-----------|--------------------|-----------------------------------------------------------------------------|\n| `user_input` | `str`             | The text describing the phenomenon to analyze.                             |\n| `api_key`    | `Optional[str]`    | LLM7 API key (default: fetched from `LLM7_API_KEY` environment variable).   |\n| `llm`         | `Optional[BaseChatModel]` | Custom LLM instance (e.g., `ChatOpenAI`, `ChatAnthropic`). Default: `ChatLLM7`. |\n\n---\n\n## 📊 Output\nThe function returns a **list of structured insights** extracted from the input text, formatted to match predefined patterns (e.g., impact classification, event nature).\n\n---\n\n## 🔄 Rate Limits\n- **LLM7 Free Tier**: Sufficient for most use cases.\n- **Custom API Key**: For higher rate limits, provide your own `api_key` or set `LLM7_API_KEY`.\n\n---\n\n## 📜 License\nMIT License.\n\n---\n\n## 📢 Support \u0026 Issues\nFor bugs or feature requests, open an issue on [GitHub](https://github.com/chigwell/phenomenon-interpreter/issues).\n\n---\n\n## 👤 Author\n- **Eugene Evstafev** ([GitHub](https://github.com/chigwell))\n- **Email**: [hi@euegne.plus](mailto:hi@euegne.plus)\n\n---","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Fphenomenon-interpreter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchigwell%2Fphenomenon-interpreter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Fphenomenon-interpreter/lists"}