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It processes unstructured text inputs to produce a standardized output that includes the collaborating companies, the focus area of their collaboration, and the potential impact or goals mentioned. This facilitates quick analysis and comparison of multiple partnership announcements, helping business analysts, investors, and researchers identify industry trends, competitive advantages, and market opportunities.\n\n## Features\n\n- Extracts key partnership details from free-text sources\n- Outputs structured, consistent data for easier downstream analysis\n- Utilizes advanced language models with flexible options\n- Easy to integrate into larger data processing pipelines\n\n## Installation\n\nInstall PartnershipParser via pip:\n\n```bash\npip install partnershipparser\n```\n\n## Usage\n\nBelow is an example of how to use the package in your Python code:\n\n```python\nfrom partnershipparser import partnershipparser\n\nuser_input = \"Apple and Google announced a collaboration to develop sustainable AI chips.\"\nresponse = partnershipparser(user_input)\nprint(response)\n```\n\n### Parameters:\n\n- `user_input` (str): The text content of the article or press release to analyze.\n- `llm` (Optional[BaseChatModel]): An instance of a language model to use for processing. Defaults to `ChatLLM7` from `langchain_llm7`.\n- `api_key` (Optional[str]): API key for `ChatLLM7`. If not provided, it will attempt to read from environment variable `LLM7_API_KEY`. You can also pass it directly.\n\n## Supported Language Models\n\nThe package defaults to `ChatLLM7` from `langchain_llm7` ( https://pypi.org/project/langchain-llm7/ ). Users can pass custom language model instances such as:\n\n```python\nfrom langchain_openai import ChatOpenAI\nfrom partnershipparser import partnershipparser\n\nllm = ChatOpenAI()\nresponse = partnershipparser(user_input, llm=llm)\n```\n\nYou can also use other supported models by importing and instantiating them similarly, such as `ChatAnthropic`, `ChatGoogleGenerativeAI`, etc. Refer to their respective documentation for setup.\n\n## Rate Limits and API Keys\n\nThe default rate limits for LLM7's free tier are suitable for most uses of this package. To obtain higher limits, you can:\n\n- Set `LLM7_API_KEY` environment variable\n- Pass your API key directly in `partnershipparser()`:\n\n```python\nresponse = partnershipparser(user_input, api_key=\"your_api_key\")\n```\n\nRegister for a free API key at https://token.llm7.io/\n\n## Contributing\n\nContributions are welcome! Please open issues or pull requests on our GitHub repository.\n\n## License\n\nThis project is licensed under the MIT License.\n\n## Contact\n\nAuthor: Eugene Evstafev  \nEmail: hi@euegne.plus  \nGitHub: [chigwell](https://github.com/chigwell)  \nIssues: [https://github.com/yourrepo/partnershipparser/issues](https://github.com/yourrepo/partnershipparser/issues)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Fpartnershipparser","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchigwell%2Fpartnershipparser","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchigwell%2Fpartnershipparser/lists"}