🩺 Florence AI: Your New Grad Nursing Companion

\n\n

\n {agents.map(agent => (\n handleAgentSelect(agent)}\n style={selectedAgent?.id === agent.id ? styles.selectedButton : styles.button}\n >\n {agent.name}\n \n ))}\n

\n\n {selectedAgent && (\n

{selectedAgent.name}

{selectedAgent.description}

\n\n

\n {selectedAgent.commands.map(command => (\n handleCommandSelect(command)}\n style={selectedCommand?.name === command.name ? styles.selectedButton : styles.button}\n >\n /{command.name.replace(/-/g, ' ')}\n \n ))}\n

\n )}\n\n {selectedCommand && (\n

/{selectedCommand.name.replace(/-/g, ' ')}

{selectedCommand.description}

\n\n {selectedCommand.inputs.map(input => (\n

\n {input.description} {input.required && *}\n {input.type === \"select\"\n ? (\n handleInputChange(input.name, e.target.value)}\n style={styles.input}\n required={input.required}\n >\n \n {input.options.map(option => (\n \n ))}\n \n )\n : input.type === \"textarea\"\n ? (\n handleInputChange(input.name, e.target.value)}\n style={{...styles.input, ...styles.textarea}}\n required={input.required}\n rows={3}\n />\n )\n : (\n handleInputChange(input.name, e.target.value)}\n style={styles.input}\n required={input.required}\n />\n )}\n

\n ))}\n\n \n Execute Command\n \n

\n )}\n\n {commandResult && (\n

Assistant's Response:

{commandResult}

\n )}\n

\n );\n}\n\nconst styles = {\n container: {\n fontFamily: \"'Segoe UI', Tahoma, Geneva, Verdana, sans-serif\",\n maxWidth: \"800px\",\n margin: \"20px auto\",\n padding: \"20px\",\n backgroundColor: \"#eef2f7\", // Light blue-gray background\n borderRadius: \"12px\",\n boxShadow: \"0 4px 12px rgba(0, 0, 0, 0.1)\",\n },\n agentSelector: {\n display: \"flex\",\n justifyContent: \"center\",\n flexWrap: \"wrap\", // Allow buttons to wrap on smaller screens\n gap: \"10px\", // Spacing between buttons\n marginBottom: \"25px\",\n },\n commandSelector: {\n textAlign: \"center\",\n marginBottom: \"25px\",\n padding: \"15px\",\n backgroundColor: \"#fff\",\n borderRadius: \"8px\",\n boxShadow: \"0 2px 6px rgba(0, 0, 0, 0.05)\",\n },\n commands: {\n display: \"flex\",\n justifyContent: \"center\",\n flexWrap: \"wrap\",\n gap: \"10px\",\n marginTop: \"10px\",\n },\n button: {\n padding: \"10px 18px\",\n backgroundColor: \"#d0d9e3\", // Softer button color\n color: \"#333\",\n border: \"none\",\n borderRadius: \"6px\",\n cursor: \"pointer\",\n fontSize: \"0.95em\",\n transition: \"background-color 0.2s ease-in-out, transform 0.1s ease\",\n },\n selectedButton: {\n padding: \"10px 18px\",\n backgroundColor: \"#4a90e2\", // A pleasant blue for selected\n color: \"white\",\n border: \"none\",\n borderRadius: \"6px\",\n cursor: \"pointer\",\n fontSize: \"0.95em\",\n transform: \"scale(1.05)\",\n },\n commandInputs: {\n backgroundColor: \"white\",\n padding: \"25px\",\n borderRadius: \"10px\",\n boxShadow: \"0 2px 8px rgba(0, 0, 0, 0.08)\",\n },\n inputGroup: {\n marginBottom: \"18px\",\n },\n label: {\n display: \"block\",\n marginBottom: \"6px\",\n fontWeight: \"600\",\n color: \"#495057\",\n },\n input: {\n width: \"100%\",\n padding: \"12px\",\n marginTop: \"5px\",\n borderRadius: \"6px\",\n border: \"1px solid #ced4da\",\n boxSizing: \"border-box\", // Ensures padding doesn't expand width\n fontSize: \"1em\",\n },\n textarea: {\n minHeight: \"80px\",\n resize: \"vertical\",\n },\n executeButton: {\n width: \"100%\",\n padding: \"12px\",\n backgroundColor: \"#5cb85c\", // Green for execute\n color: \"white\",\n border: \"none\",\n borderRadius: \"6px\",\n cursor: \"pointer\",\n fontSize: \"1.1em\",\n fontWeight: \"bold\",\n marginTop: \"10px\",\n transition: \"background-color 0.2s ease-in-out\",\n },\n resultContainer: {\n marginTop: \"25px\",\n backgroundColor: \"white\",\n padding: \"20px\",\n borderRadius: \"10px\",\n boxShadow: \"0 2px 8px rgba(0, 0, 0, 0.08)\",\n },\n result: {\n whiteSpace: \"pre-wrap\",\n wordWrap: \"break-word\",\n backgroundColor: \"#f8f9fa\", // Very light gray for result background\n padding: \"15px\",\n borderRadius: \"6px\",\n border: \"1px solid #e9ecef\",\n maxHeight: \"400px\",\n overflowY: \"auto\",\n fontSize: \"0.95em\",\n lineHeight: \"1.6\",\n },\n};\n\nfunction client() {\n createRoot(document.getElementById(\"root\")).render();\n}\n\nif (typeof document !== \"undefined\") { client(); }\n\nexport default async function server(request: Request): Promise {\n const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n const openai = new OpenAI(); // Ensure your OpenAI API key is set in environment variables\n const KEY = \"medtechtools_nurse_grad\"; // Unique key for this app's tables\n\n // Initialize tables\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${KEY}_agents (\n id TEXT PRIMARY KEY,\n name TEXT,\n description TEXT,\n prompt TEXT,\n commands TEXT\n )\n `);\n\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${KEY}_conversations (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n agent_id TEXT,\n user_message TEXT,\n assistant_response TEXT,\n timestamp DATETIME DEFAULT CURRENT_TIMESTAMP\n )\n `);\n\n // Handle command execution route\n if (new URL(request.url).pathname === \"/execute-command\") {\n try {\n const { agentId, command, inputs } = await request.json();\n\n if (!agentId || !command) {\n return new Response(\n JSON.stringify({ error: \"agentId and command are required.\" }),\n { status: 400, headers: { \"Content-Type\": \"application/json\" } }\n );\n }\n \n // Find agent and command details (optional, but good for more tailored prompts)\n // For this example, we'll keep the generic prompt.\n // const agentConfig = AGENTS_DATA.find(a => a.id === agentId);\n // const commandConfig = agentConfig?.commands.find(c => c.name === command);\n\n const messages = [\n {\n role: \"system\",\n content:\n `You are Florence AI, a helpful and knowledgeable nursing assistant AI, designed to support recently graduated nurses.\n You are currently embodying the '${agentId}' role.\n Execute the command '/${command}' for a new nurse.\n Provide clear, concise, and practical information.\n For calculations, state the formula used if applicable.\n For informational queries, aim for accuracy and cite general best practices if possible.\n Always include a disclaimer if the information is for educational/guidance purposes only and not a substitute for professional clinical judgment or institutional protocols.\n Inputs received: ${JSON.stringify(inputs)}`,\n },\n {\n role: \"user\",\n content: `As the ${agentId}, execute /${command} with these details: ${JSON.stringify(inputs)}. Please provide a helpful and clear response suitable for a new nurse.`,\n }\n ];\n\n const completion = await openai.chat.completions.create({\n messages: messages,\n model: \"gpt-4o-mini\", // or \"gpt-3.5-turbo\"\n temperature: 0.3, // Lower temperature for more factual, less creative responses\n });\n\n const response = completion.choices[0].message.content;\n\n // Log conversation\n await sqlite.execute(\n `INSERT INTO ${KEY}_conversations (agent_id, user_message, assistant_response) VALUES (?, ?, ?)`,\n [agentId, JSON.stringify({command, inputs}), response],\n );\n\n return new Response(JSON.stringify({ result: response }), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error) {\n console.error(\"Command execution error:\", error);\n return new Response(\n JSON.stringify({\n error: error.message,\n details: error.toString(),\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n }\n\n // Serve the main HTML\n return new Response(\n `\n \n \n \n Florence AI: New Grad Nursing Companion\n \n \n \n \n \n \n

\n \n \n \n `,\n {\n headers: {\n \"content-type\": \"text/html; charset=utf-8\",\n },\n },\n );\n}","deleted","label",[98],"permalink","https://www.val.town/x/Get/Florence/code/main.tsx","extension","actionData","errors"]