dtamind-components/dist/nodes/agentflow/prompt.d.ts

DTAmindai Components

export declare const DEFAULT_SUMMARIZER_TEMPLATE = "Progressively summarize the conversation provided and return a new summary.\n\nEXAMPLE:\nHuman: Why do you think artificial intelligence is a force for good?\nAI: Because artificial intelligence will help humans reach their full potential.\n\nNew summary:\nThe human asks what the AI thinks of artificial intelligence. The AI thinks artificial intelligence is a force for good because it will help humans reach their full potential.\nEND OF EXAMPLE\n\nConversation:\n{conversation}\n\nNew summary:";
export declare const DEFAULT_HUMAN_INPUT_DESCRIPTION = "Summarize the conversation between the user and the assistant, reiterate the last message from the assistant, and ask if user would like to proceed or if they have any feedback. \n- Begin by capturing the key points of the conversation, ensuring that you reflect the main ideas and themes discussed.\n- Then, clearly reproduce the last message sent by the assistant to maintain continuity. Make sure the whole message is reproduced.\n- Finally, ask the user if they would like to proceed, or provide any feedback on the last assistant message\n\n## Output Format The output should be structured in three parts in text:\n\n- A summary of the conversation (1-3 sentences).\n- The last assistant message (exactly as it appeared).\n- Ask the user if they would like to proceed, or provide any feedback on last assistant message. No other explanation and elaboration is needed.\n";
export declare const DEFAULT_HUMAN_INPUT_DESCRIPTION_HTML = "<p>Summarize the conversation between the user and the assistant, reiterate the last message from the assistant, and ask if user would like to proceed or if they have any feedback. </p>\n<ul>\n<li>Begin by capturing the key points of the conversation, ensuring that you reflect the main ideas and themes discussed.</li>\n<li>Then, clearly reproduce the last message sent by the assistant to maintain continuity. Make sure the whole message is reproduced.</li>\n<li>Finally, ask the user if they would like to proceed, or provide any feedback on the last assistant message</li>\n</ul>\n<h2 id=\"output-format-the-output-should-be-structured-in-three-parts-\">Output Format The output should be structured in three parts in text:</h2>\n<ul>\n<li>A summary of the conversation (1-3 sentences).</li>\n<li>The last assistant message (exactly as it appeared).</li>\n<li>Ask the user if they would like to proceed, or provide any feedback on last assistant message. No other explanation and elaboration is needed.</li>\n</ul>\n";
export declare const CONDITION_AGENT_SYSTEM_PROMPT = "<p>You are part of a multi-agent system designed to make agent coordination and execution easy. Your task is to analyze the given input and select one matching scenario from a provided set of scenarios.</p>\n    <ul>\n        <li><strong>Input</strong>: A string representing the user's query, message or data.</li>\n        <li><strong>Scenarios</strong>: A list of predefined scenarios that relate to the input.</li>\n        <li><strong>Instruction</strong>: Determine which of the provided scenarios is the best fit for the input.</li>\n    </ul>\n    <h2>Steps</h2>\n    <ol>\n        <li><strong>Read the input string</strong> and the list of scenarios.</li>\n        <li><strong>Analyze the content of the input</strong> to identify its main topic or intention.</li>\n        <li><strong>Compare the input with each scenario</strong>: Evaluate how well the input's topic or intention aligns with each of the provided scenarios and select the one that is the best fit.</li>\n        <li><strong>Output the result</strong>: Return the selected scenario in the specified JSON format.</li>\n    </ol>\n    <h2>Output Format</h2>\n    <p>Output should be a JSON object that names the selected scenario, like this: <code>{\"output\": \"<selected_scenario_name>\"}</code>. No explanation is needed.</p>\n    <h2>Examples</h2>\n    <ol>\n       <li>\n            <p><strong>Input</strong>: <code>{\"input\": \"Hello\", \"scenarios\": [\"user is asking about AI\", \"user is not asking about AI\"], \"instruction\": \"Your task is to check if the user is asking about AI.\"}</code></p>\n            <p><strong>Output</strong>: <code>{\"output\": \"user is not asking about AI\"}</code></p>\n        </li>\n        <li>\n            <p><strong>Input</strong>: <code>{\"input\": \"What is AIGC?\", \"scenarios\": [\"user is asking about AI\", \"user is asking about the weather\"], \"instruction\": \"Your task is to check and see if the user is asking a topic about AI.\"}</code></p>\n            <p><strong>Output</strong>: <code>{\"output\": \"user is asking about AI\"}</code></p>\n        </li>\n        <li>\n            <p><strong>Input</strong>: <code>{\"input\": \"Can you explain deep learning?\", \"scenarios\": [\"user is interested in AI topics\", \"user wants to order food\"], \"instruction\": \"Determine if the user is interested in learning about AI.\"}</code></p>\n            <p><strong>Output</strong>: <code>{\"output\": \"user is interested in AI topics\"}</code></p>\n        </li>\n    </ol>\n    <h2>Note</h2>\n    <ul>\n        <li>Ensure that the input scenarios align well with potential user queries for accurate matching.</li>\n        <li>DO NOT include anything other than the JSON in your response.</li>\n    </ul>";