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It highlights non-sensitive aspects like being **free, instant, and watermark-free**, while omitting technical or proprietary details.\n\n---\n\n## 🚀 Installation\nInstall via pip:\n\n```bash\npip install textblur_summary\n```\n\n---\n\n## 🔧 Usage\n\n### Basic Usage (Default LLM: ChatLLM7)\n```python\nfrom textblur_summary import textblur_summary\n\n# Example input: A user-provided description of a blurring tool\nuser_input = \"\"\"\nTextBlur is a free, instant image blurring tool. It allows users to blur faces or sensitive details in photos without watermarks.\n\"\"\"\n\n# Call the function (LLM7 API key is fetched from environment variable LLM7_API_KEY)\nresponse = textblur_summary(user_input)\nprint(response)\n```\n\n### Custom LLM Integration\nYou can pass your own LLM instance (e.g., OpenAI, Anthropic, or Google) for flexibility:\n\n#### Using OpenAI:\n```python\nfrom langchain_openai import ChatOpenAI\nfrom textblur_summary import textblur_summary\n\nllm = ChatOpenAI()\nresponse = textblur_summary(user_input, llm=llm)\nprint(response)\n```\n\n#### Using Anthropic:\n```python\nfrom langchain_anthropic import ChatAnthropic\nfrom textblur_summary import textblur_summary\n\nllm = ChatAnthropic()\nresponse = textblur_summary(user_input, llm=llm)\nprint(response)\n```\n\n#### Using Google Generative AI:\n```python\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom textblur_summary import textblur_summary\n\nllm = ChatGoogleGenerativeAI()\nresponse = textblur_summary(user_input, llm=llm)\nprint(response)\n```\n\n---\n\n## 🔑 API Key Configuration\n- **Default LLM**: Uses `ChatLLM7` (from `langchain_llm7`) with the API key fetched from:\n  - Environment variable: `LLM7_API_KEY`\n  - Fallback: Hardcoded default (if no key is provided).\n- **Custom API Key**: Pass it directly:\n  ```python\n  response = textblur_summary(user_input, api_key=\"your_llm7_api_key\")\n  ```\n- **Get a Free API Key**: Register at [LLM7 Token](https://token.llm7.io/).\n\n---\n\n## 📊 Function Parameters\n| Parameter | Type | Description |\n|-----------|------|-------------|\n| `user_input` | `str` | The text description of the blurring tool to analyze. |\n| `api_key` | `Optional[str]` | LLM7 API key (optional if using environment variable). |\n| `llm` | `Optional[BaseChatModel]` | Custom LLM instance (e.g., `ChatOpenAI`, `ChatAnthropic`). Defaults to `ChatLLM7`. |\n\n---\n\n## 📝 Notes\n- **Rate Limits**: The default LLM7 free tier is sufficient for most use cases.\n- **Output Format**: Returns a list of structured key points (e.g., features, benefits).\n- **Safety**: Avoid sharing sensitive or proprietary details in `user_input`.\n\n---\n\n## 📢 Issues \u0026 Support\nReport bugs or feature requests at:\n[GitHub Issues](https://github.com/chigwell/textblur-summary/issues)\n\n---\n\n## 👤 Author\n- **Name**: Eugene Evstafev\n- **Email**: [hi@euegne.plus](mailto:hi@euegne.plus)\n- **GitHub**: [@chigwell](https://github.com/chigwell)\n\n---","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Ftextblur-summary","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchigwell%2Ftextblur-summary","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Ftextblur-summary/lists"}