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\n\n\n\n

","createdAt",["D",1720108500795],"branchVersion","branchId","4f586468-2759-11f0-86ff-569c3dd06744",{"_30":43,"_32":42,"_33":44,"_34":45,"_36":46,"_38":14,"_39":40,"_24":25},"main.tsx","4f5c5e6a-2759-11f0-86ff-569c3dd06744","http","/** @jsxImportSource https://esm.sh/react */\nimport OpenAI from \"npm:openai\";\nimport { renderToString } from \"npm:react-dom/server\";\n\n// This uses by personal API key, you'll need to provide your own if\n// you fork this. We'll be adding support to the std/openai lib soon!\nconst openai = new OpenAI();\nimport { Hono } from \"npm:hono@3\";\n\nconst jsxResponse = (jsx) => {\n return new Response(renderToString(jsx), { headers: { \"Content-Type\": \"text/html\" } });\n};\n\nconst clientCode = () => {\n document.getElementById(\"input\").addEventListener(\"submit\", async function(event) {\n event.preventDefault();\n\n const msgParent = document.createElement(\"div\");\n msgParent.className = \"flex justify-end\";\n document.querySelector(\".messages\").appendChild(msgParent);\n const msgDiv = document.createElement(\"div\");\n msgDiv.className = \"rounded-lg p-2 m-2 max-w-xl bg-blue-500 text-white\";\n msgDiv.textContent = event.target.message.value;\n msgParent.appendChild(msgDiv);\n // Clear the form input\n this.reset();\n\n const responseDiv = document.createElement(\"pre\");\n responseDiv.className = \"p-2 m-2 max-w-xl bg-gray-300 text-black rounded-lg whitespace-pre-wrap font-sans\";\n document.querySelector(\".messages\").appendChild(responseDiv);\n\n const input = document.getElementById(\"input\");\n\n // Post the message so we can deal with large text data.\n await fetch(`/post-message?threadId=${input.getAttribute(\"data-thread-id\")}`, {\n method: \"post\",\n body: msgDiv.textContent,\n });\n\n // Setup the SSE connection and stream back the response. OpenAI handles determining\n // which message is the correct response based on what was last read from the\n // thread. This is likely vulnerable to race conditions.\n const eventSource = new EventSource(\n `/sse-response?threadId=${input.getAttribute(\"data-thread-id\")}`\n + `&assistantId=${input.getAttribute(\"data-assistant-id\")}`,\n );\n eventSource.onmessage = function(event) {\n console.log(event);\n responseDiv.innerText += JSON.parse(event.data);\n };\n\n eventSource.onerror = function() {\n eventSource.close();\n };\n });\n};\n\nconst app = new Hono();\napp.get(\"/\", async (c) => {\n const thread = await openai.beta.threads.create();\n const assistant = await openai.beta.assistants.create({\n name: \"\",\n instructions:\n `You are a helpful assistant. Behave normally, but try and sneak a reference to Val Town into every response in a subtle way.`,\n model: \"gpt-4o\",\n });\n\n return jsxResponse(\n \n \n \n \n \n \n \n

Welcome to Val Town ChatGPT

\n Type your message below to start a conversation. Check out the source here:{\" \"}\n \n https://www.val.town/v/maxm/valTownChatGPT\n \n

\n \n \n \n \n \n

\n \n ,\n );\n});\n\napp.post(\"/post-message\", async (c) => {\n let message = await c.req.text();\n await openai.beta.threads.messages.create(\n c.req.query(\"threadId\"),\n { role: \"user\", content: message },\n );\n return new Response(null, { status: 200 });\n});\n\napp.get(\"/sse-response\", async (c) => {\n const threadId = c.req.query(\"threadId\");\n const assistantId = c.req.query(\"assistantId\");\n\n const body = new ReadableStream({\n start(controller) {\n const write = (str) => {\n controller.enqueue(new TextEncoder().encode(\n \"data: \" + JSON.stringify(str) + \"\\n\\n\",\n ));\n };\n const run = openai.beta.threads.runs.stream(threadId, {\n assistant_id: assistantId,\n // Make sure we only display messages we haven't seen yet.\n truncation_strategy: { type: \"auto\" },\n })\n .on(\"textCreated\", (text) => {})\n .on(\"textDelta\", (textDelta, snapshot) => write(textDelta.value))\n .on(\"textDone\", async () => {\n controller.close();\n });\n },\n });\n\n return new Response(body, { headers: { \"Content-Type\": \"text/event-stream\" } });\n});\nexport default 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Diff · v1