> For the complete documentation index, see [llms.txt](https://docs.ebbot.ai/ebbot-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ebbot.ai/ebbot-docs/core-capabilities/automations/workflow-nodes/llm-nodes/llm-node-prompts.md). # LLM Node Prompts ### Language Getting the LLM to generate a message in the "correct" language can sometimes be tricky if there are several different languages present in the prompt, its source documents, or the mail/message it is supposed to reply to. That is why it is best practice to minimize the amount of redundant information you send to the model. For example, if it is processing an email, it is much better to only import the core email body. Avoiding the header, footer, and signature of the email prevents the model from being confused by boilerplate text that might be in the wrong language. #### Language Prompt Directives When building your prompt, use these explicit instructions to force the LLM to focus on the correct language context. You can copy and paste these directly into your system instructions: * **Primary Directive**: ALWAYS detect and respond in the language of the INCOMING EMAIL BODY. * **Exclusion Rule**: Ignore languages in headers, metadata, signatures, titles, disclaimers, or mixed closings (e.g., "Kind regards", "Sent from my iPhone"). * **System Override**: IMPORTANT: The language used in this prompt and/or the background documents MAY be different from the language you must answer in. ALWAYS stick to the language in the user's primary message, no matter what. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://docs.ebbot.ai/ebbot-docs/core-capabilities/automations/workflow-nodes/llm-nodes/llm-node-prompts.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.