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Specify what you want it to build, the AI asks for clarification, and then builds it. GPT Engineer is made to be easy to adapt, extend, and make your agent learn how you want your code to look. [...] Flexible and easy to add new own "AI steps". Incrementally build towards a user experience of: high level prompting giving feedback to the AI that it will remember over time [...] You can specify the "identity" of the AI agent by editing the files in the identity folder.

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https://github.com/GMYXDS/MstscManager/blob/master/images/remote-desktop-512.png 一个支持MSTSC，Putty，Xshell，Xftp，Radmin，VNC，Winscp，SecureCRT，MobaXterm，Todesk的远程管理器 支持常用的连接软件，如RDP,Putty,Xshell,Xftp,Radmin,VNC,Winscp,SecureCRT 更新说明 https://github.com/GMYXDS/MstscManager/blob/master/Updates.md 如何下载 你可以下载源码，自行编译后使用。 [...] ,MSTSC_win_x64_with_dotnet6.zip，四个版本中前两个不带.NET环境，需要自行安装.NET6 Runtime环境，小白无脑选择后面2个就行。

https://github.com/j178/chatgpt/releases A CLI for ChatGPT, powered by GPT-3.5-turbo and GPT-4 models. Get or create your OpenAI API Key from here: https://platform.openai.com/account/api-keys 💬 Start in chat mode [...] 💻 Use it in a pipeline cat config.yaml | chatgpt -p 'convert this yaml to json' echo "Hello, world" | chatgpt -p translator | say [...] You can add more prompts in the config file, for example: {"api_key": "sk-xxxxxx", "endpoint": "https://api.openai.com/v1", "prompts": {"default": "You are ChatGPT, a large language model trained by OpenAI. [...] "}, "conversation": {"prompt": "default", "context_length": 6, "model": "gpt-3.5-turbo", "stream": true, "max_tokens": 1024 }} then use -p flag to switch prompt: Note The prompt can be a predefined prompt, or come up with one on the fly.

Generative AI support on Vertex AI generally available | Google Cloud Blog

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https://i1.wp.com/a16z.com/wp-content/uploads/2023/05/stacks_of_books_and_GPU.png?ssl=1Source: Midjourney Research in artificial intelligence is increasing at an exponential rate. [...] https://jalammar.github.io/illustrated-stable-diffusion/: Introduction to latent diffusion models, the most common type of generative AI model for images. [...] New models https://arxiv.org/abs/1706.03762 (2017): The original transformer work and research paper from Google Brain that started it all. [...] Code generation https://arxiv.org/abs/2107.03374 (2021): This is OpenAI’s research paper for Codex, the code-generation model behind the GitHub Copilot product.

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The more words you use, the better} else { const sourceLangCode = query.detectFrom const targetLangCode = query.detectTo const sourceLangName = lang.getLangName(sourceLangCode) const targetLangName = lang.getLangName(targetLangCode) console.debug('sourceLang', sourceLangName) console.debug('targetLang', targetLangName) const toChinese = chineseLangCodes.indexOf(targetLangCode) >= 0 const targetLangConfig = getLangConfig(targetLangCode) const sourceLangConfig = getLangConfig(sourceLangCode) console.log('Source language is', sourceLangConfig) rolePrompt = targetLangConfig.rolePrompt switch (query.action.mode) { case null: case undefined: if ((query.action.rolePrompt ?? '').includes('${text}') || (query.action.commandPrompt ?? '').includes('${text}')) { contentPrompt = '' } else { contentPrompt = '"""' + query.text + '"""' } rolePrompt = (query.action.rolePrompt ?? '') .replace('${sourceLang}', sourceLangName) .replace('${targetLang}', targetLangName) .replace('${text}', query.text) commandPrompt = (query.action.commandPrompt ?? '') .replace('${sourceLang}', sourceLangName) .replace('${targetLang}', targetLangName) .replace('${text}', query.text) if (query.action.outputRenderingFormat) { commandPrompt +=. Format: ${query.action.outputRenderingFormat}} break case 'translate': quoteProcessor = new QuoteProcessor() commandPrompt = targetLangConfig.genCommandPrompt( sourceLangConfig, quoteProcessor.quoteStart, quoteProcessor.quoteEnd ) contentPrompt =${quoteProcessor.quoteStart}${query.text}${quoteProcessor.quoteEnd}if (query.text.length [...] Only polish the text between ${quoteProcessor.quoteStart} and ${quoteProcessor.quoteEnd}. contentPrompt = ${quoteProcessor.quoteStart}${query.text}${quoteProcessor.quoteEnd} break case 'summarize': rolePrompt = "You are a professional text summarizer, you can only summarize the text, don't interpret it." [...] (status)}, onMessage: (msg) => { let resp try { resp = JSON.parse(msg) // eslint-disable-next-line no-empty } catch { query.onFinish('stop') return } if (!conversationId) { conversationId = resp.conversation_id } const { finish_details: finishDetails } = resp.message if (finishDetails) { query.onFinish(finishDetails.type) return } const { content, author } = resp.message if (author.role === 'assistant') { const targetTxt = content.parts.join('') let textDelta = targetTxt.slice(length) if (quoteProcessor) { textDelta = quoteProcessor.processText(textDelta)} query.onMessage({ content: textDelta, role: '', isWordMode }) length = targetTxt.length }}, onError: (err) => { if (err instanceof Error) { query.onError(err.message) return } if (typeof err === 'string') { query.onError(err) return } if (typeof err === 'object') { const { detail } = err if (detail) { const { message } = detail if (message) { query.onError(ChatGPT Web: ${message}) return }} query.onError(ChatGPT Web: ${JSON.stringify(err)}) return } const { error } = err if (error instanceof Error) { query.onError(error.message) return } if (typeof error === 'object') { const { message } = error if (message) { query.onError(message) return }} query.onError('Unknown error')}, }) if (conversationId) { await fetcher(${utils.defaultChatGPTWebAPI}/conversation/${conversationId}, { method: 'PATCH', headers, body: JSON.stringify({ is_visible: false }), })} } else { const url = urlJoin(settings.apiURL, settings.apiURLPath) await fetchSSE(url, { method: 'POST', headers, body: JSON.stringify(body), signal: query.signal, onMessage: (msg) => { let resp try { resp = JSON.parse(msg) // eslint-disable-next-line no-empty } catch { query.onFinish('stop') return } const { choices } = resp if (!choices || choices.length === 0) { return { error: 'No result' }} const { finish_reason: finishReason } = choices if (finishReason) { query.onFinish(finishReason) return } let targetTxt = '' if (!isChatAPI) { // It's used for Azure OpenAI Service's legacy parameters. targetTxt = choices.text if (quoteProcessor) { targetTxt = quoteProcessor.processText(targetTxt)} query.onMessage({ content: targetTxt, role: '', isWordMode })} else { const { content = '', role } = choices.delta targetTxt = content if (quoteProcessor) { targetTxt = quoteProcessor.processText(targetTxt)} query.onMessage({ content: targetTxt, role, isWordMode })} }, onError: (err) => { if (err instanceof Error) { query.onError(err.message) return } if (typeof err === 'string') { query.onError(err) return } if (typeof err === 'object') { const { detail } = err if (detail) { query.onError(detail) return }} const { error } = err if (error instanceof Error) { query.onError(error.message) return } if (typeof error === 'object') { const { message } = error if (message) { query.onError(message) return }} query.onError('Unknown error')}, })} }