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@@ -86,11 +86,33 @@ By default, there is a `GenericProvider` that support a `SimpleProcessor` using
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> Note: Because these providers do not support the BCOP standard natively, maybe there are some gaps on the implemented parser that will be refined with new test cases. We encourage you to report related **issues**!
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#### LLM-powered Parsers
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The library supports an optional parser option leveraging Large Language Model (LLM) to provide best-effort parsing when the specific parsers have not been successful.
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> Warning: Some of these integrations, such as OpenAI, require of extras installations parameters. Check the [extras section](#extras)
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When the appropriate environment variable(s) are set (see below), these LLM parsers are automatically appended after all existing processors for each defined Provider.
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> These integrations may involve some costs for API usage. Use it carefully! As an order of magnitude, a parsing of an email with OpenAI GPT gpt-3.5-turbo model costs $0.004.
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These are the currently supported LLM integrations:
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-[OpenAI](https://openai.com/product), these are the supported ENVs:
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-`OPENAI_API_KEY` (Required): OpenAI API Key.
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-`OPENAI_MODEL` (Optional): Model to use, it defaults to "gpt-3.5-turbo".
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## Installation
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The library is available as a Python package in pypi and can be installed with pip:
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`pip install circuit-maintenance-parser`
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### Extras
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#### OpenAI
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`pip install circuit-maintenance-parser[openai]`
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## How to use it?
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The library requires two things:
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...omitted debug logs...
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====================================================== 99 passed, 174 deselected, 17 warnings in 10.35s ======================================================
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```
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7. Run some final CI tests locally to ensure that there is no linting/formatting issues with your changes. You should look to get a code score of 10/10. See the example below: `invoke tests --local`
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