# Main Options **Options Overview:** ``` --help ``` Displays a help message outlining all available options and their usage. This is useful if you're unsure about the correct syntax or need a quick reference for what commands are available.\ Aliases: ``` -h --help ``` **Main Configuration Options:** ``` --openai-api-key OPENAI_API_KEY ``` This option allows you to specify the OpenAI API key directly via the command line. The key is required for authenticating requests to OpenAI's services. If you prefer, you can also set this key using the environment variable `PAPERTLAB_OPENAI_API_KEY`, which allows you to avoid hard-coding sensitive information in your scripts. ``` --anthropic-api-key ANTHROPIC_API_KEY ``` Similar to the OpenAI key, this option lets you provide the Anthropic API key, which is necessary to access Anthropic’s models. The key can be specified on the command line or set as an environment variable `PAPERTLAB_ANTHROPIC_API_KEY` to keep it secure and easily configurable across different environments. ``` --model MODEL ``` This option specifies which AI model you want PapertLab to use for the main chat. Different models can have various capabilities and performance characteristics. By setting this option, you can tailor the behavior of PapertLab to better suit your needs. The model can be specified via the command line or by using the environment variable `PAPERTLAB_MODEL`. ``` --opus ``` If you want to use the `claude-3-opus-20240229` model for your main chat interactions, you can select this option. This model might be optimized for specific types of conversations or performance parameters. You can also set this option using the `PAPERTLAB_OPUS` environment variable to make it your default choice without having to specify it each time. ``` --sonnet ``` This option selects the `claude-3-5-sonnet-20240620` model for your main chat. This model may have different strengths or features compared to others. If you frequently use this model, setting it via the `PAPERTLAB_SONNET` environment variable could save you time. ``` --4 ``` This allows you to choose the `gpt-4-0613` model for the main chat. GPT-4 is a powerful language model known for its extensive capabilities in natural language understanding and generation. This model can be selected directly or by setting the `PAPERTLAB_4` environment variable.\ Aliases: ``` --4 -4 ``` ``` --4o ``` If you prefer the `gpt-4o-2024-08-06` variant for your main chat, use this option. The `gpt-4o` might offer different performance or be better suited to specific tasks. This model can also be set as the default using the `PAPERTLAB_4O` environment variable. ``` --mini ``` This option selects the `gpt-4o-mini` model, which could be a lighter version of the GPT-4 family, offering faster response times or lower resource usage. Ideal for scenarios where efficiency is more critical than the expansive capabilities of the full GPT-4 models. This can be specified via the `PAPERTLAB_MINI` environment variable. ``` --4-turbo ``` The `gpt-4-1106-preview` model can be selected with this option. This variant may be in a preview phase, offering access to the latest features and improvements before they are widely available. You can also set this as your default model using the `PAPERTLAB_4_TURBO` environment variable. ``` --35turbo ``` This option is used to select the `gpt-3.5-turbo` model for the main chat. The `gpt-3.5-turbo` is a streamlined version of GPT-3, optimized for performance. This is a good choice if you need a balance between power and efficiency. You can set this model as your default by using the `PAPERTLAB_35TURBO` environment variable.\ Aliases: ``` --35turbo --35-turbo --3 -3 ``` --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.papert.in/aruguments/main-options.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.