测试在Ollama中运行gemma-4-E2B模型下载Ollama安装文件。旧的Ollama不支持新模型所以要下载新版的Ollama。wget -c https://modelscope.cn/models/Lixiang/ollama-release/resolve/v0.20.0/OllamaSetup.exe拉取模型并执行命令行界面C:\dollama run gemma4:e2b pulling manifest pulling 4e30e2665218: 100% ▕██████████████████████████████████████████████████████████▏ 7.2 GB pulling 7339fa418c9a: 100% ▕██████████████████████████████████████████████████████████▏ 11 KB pulling 56380ca2ab89: 100% ▕██████████████████████████████████████████████████████████▏ 42 B pulling c6bc3775a3fa: 100% ▕██████████████████████████████████████████████████████████▏ 473 B verifying sha256 digest writing manifest success /? Available Commands: /set Set session variables /show Show model information /load model Load a session or model /save model Save your current session /clear Clear session context /bye Exit /?, /help Help for a command /? shortcuts Help for keyboard shortcuts Use to begin a multi-line message. Use \path\to\file to include .jpg, .png, .webp images, or .wav audio files.OCR一个截图图片如下 识别图片中的文字。c:\d\tlp.png Added image c:\d\tlp.png Thinking... Heres a thinking process to arrive at the desired output: 5. **Analyze the Request:** The user has provided an image containing Chinese text and asked me to identify (recognize) the text within the image. 6. **Examine the Image (OCR/Visual Scan):** I need to read the characters presented in the image. * Line 1: 特朗普终于发现让人 * Line 2: 普可收买 * Line 3: 这个世界非人 * Line 4: 作者: * Line 5: 西班牙・加入什 7. **Transcribe and Verify the Text (Focusing on flow and context):** * 特朗普终于发现让人 * 普可收买 * 这个世界非人 * 作者: * 西班牙・加入什 *(Self-Correction/Refinement based on common OCR issues and context):* The text appears to be a slightly fragmented or perhaps OCR-heavy transcription of a quote or a reference. Lets look at the actual characters again very carefully. * 特朗普终于发现让人 (Trump finally discovered people/that) * 普可收买 (Pu can buy/bribe) * 这个世界非人 (This world is inhuman) * 作者: * 西班牙・加入什 (Spain / join what?) 4. **Final Output Generation (Formatting the recognized text clearly):** Present the recognized Chinese text as the answer. (Since the request is simply recognition, I will provide the transcribed text.) ...done thinking. 根据您提供的图片识别出的文字内容如下 特朗普终于发现让人 普可收买 这个世界非人 作者: 西班牙・加入什将一段英文翻译成中文原文地址https://github.com/ultraworkers/claw-code-parity注意文本文件不适用图像和音频文件的方法。 将 c:\d\backstory.txt 翻译成中文。 Thinking... Thinking Process: 1. **Analyze the Request:** The user wants me to translate the content of a file located at c:\d\backstory.txt into Chinese. 2. **Identify Missing Information:** The user has *requested* a translation but has *not provided* the actual text content. 3. **Check for Tool Access/File Access:** As an LLM, I do not have direct access to the users local file system (like c:\d\backstory.txt). I cannot read local files unless the user explicitly provides the file content. 4. **Formulate the Response Strategy:** I must inform the user that I need the text to perform the translation. 5. **Draft the Response (in Chinese):** State clearly that the file content is missing and ask the user to provide the text. *(Self-Correction/Refinement):* Ensure the tone is helpful and polite. 6. **Final Output Generation.** ...done thinking. 请您提供需要翻译的文本内容。我无法直接访问您电脑上的本地文件如 c:\d\backstory.txt。 请将文本复制并粘贴给我我会为您翻译成中文。 c:\d\backstory.txt Thinking... Thinking Process: 1. **Analyze the Request:** The user has provided a file path (c:\d\backstory.txt) twice, following the initial request to translate it into Chinese. 2. **Identify the Problem:** The user is still asking for the translation of a file, but they have not provided the actual *content* of the file. I, as an LLM, cannot access local files on the users computer. 3. **Determine the Necessary Action:** I must reiterate that I need the text itself to perform the translation. 4. **Formulate the Response:** Be polite, clear, and explain *why* I cannot fulfill the request immediately, and tell the user exactly what they need to do next. *Self-Correction/Refinement:* Avoid sounding dismissive. Focus on the capability gap (cannot access local files) and the required input (the text). 5. **Final Output Generation.** (See response below) ...done thinking. 抱歉我仍然无法直接访问您电脑上的本地文件包括 c:\d\backstory.txt。 **为了翻译文件请您将该文件的内容复制并粘贴到聊天框中给我。** 一旦您提供文本我将立即为您翻译成中文。 At 4 AM on March 31, 2026, I woke up to my phone blowing up with notifications. The Claude Code source had been expo ... sed, and the entire dev community was in a frenzy. My girlfriend in Korea was genuinely worried I might face legal a ... ction from Anthropic just for having the code on my machine — so I did what any engineer would do under pressure: I ... sat down, ported the core features to Python from scratch, and pushed it before the sun came up. ... ... The whole thing was orchestrated end-to-end using oh-my-codex (OmX) by bellman_ych — a workflow layer built on top ... of OpenAIs Codex (OpenAIDevs). I used $team mode for parallel code review and $ralph mode for persistent executio ... n loops with architect-level verification. The entire porting session — from reading the original harness structure ... to producing a working Python tree with tests — was driven through OmX orchestration. ... ... The result is a clean-room Python rewrite that captures the architectural patterns of Claude Codes agent harness wi ... thout copying any proprietary source. Im now actively collaborating with bellman_ych — the creator of OmX himself ... — to push this further. The basic Python foundation is already in place and functional, but were just getting sta ... rted. Stay tuned — a much more capable version is on the way. Thinking... Heres a thinking process for translating the provided text: 1. **Understand the Goal:** The request is to translate a specific English text (a narrative about a coding event) into Chinese. The tone is technical, slightly dramatic, and focused on rapid problem-solving. 2. **Analyze the Source Text (Segment by Segment):** * *Original:* At 4 AM on March 31, 2026, I woke up to my phone blowing up with notifications. (Sets the scene: time, date, urgency, chaos.) * *Original:* The Claude Code source had been exposed, and the entire dev community was in a frenzy. (The problem.) * *Original:* My girlfriend in Korea was genuinely worried I might face legal action from Anthropic just for having the code on my machine — so I did what any engineer would do under pressure: I sat down, ported the core features to Python from scratch, and pushed it before the sun came up. (The motivation and action.) * *Original:* The whole thing was orchestrated end-to-end using oh-my-codex (OmX) by bellman_ych — a workflow layer built on top of OpenAIs Codex (OpenAIDevs). (The method/tools.) * *Original:* I used $team mode for parallel code review and $ralph mode for persistent execution loops with architect-level verification. (Specific technical details.) * *Original:* The entire porting session — from reading the original harness structure to producing a working Python tree with tests — was driven through OmX orchestration. (Detailing the process.) * *Original:* The result is a clean-room Python rewrite that captures the architectural patterns of Claude Codes agent harness without copying any proprietary source. (The outcome/achievement.) * *Original:* Im now actively collaborating with bellman_ych — the creator of OmX himself — to push this further. (Current status/future plan.) * *Original:* The basic Python foundation is already in place and functional, but were just getting started. Stay tuned — a much more capable version is on the way. (Conclusion/hook.) 3. **Draft the Translation (Focusing on Natural Flow and Technical Accuracy):** * *Self-Correction/Refinement Strategy:* Ensure that terms like porting, harness, orchestration, workflow layer, and the specific tool names (OmX, Codex) are translated appropriately, either using established technical equivalents or keeping the proper nouns (like the tool names) while ensuring the surrounding context makes sense. The tone should remain engaging and professional. 4. **Review and Final Polish (Comparing Draft to Original):** (See the final output below. The goal is to make the Chinese sound natural and impactful.) 5. **Final Output Generation.** (This leads to the provided good translation.) ...done thinking. 这是一篇充满技术细节和叙事感的文字。以下是为您翻译的中文版本 *** **中文翻译** 2026年3月31日凌晨4点我被手机的通知声惊醒。Claude 代码的源代码暴露了整个开发社区陷入了疯狂。我韩国的女朋友非常担 心我仅仅因为在我的机器上拥有这段代码可能会面临 Anthropic 的法律诉讼——于是我做了任何工程师在压力下都会做的事 我坐下来从零开始将核心功能移植到了 Python并在太阳升起前就完成了工作。 整个过程是使用 bellman\_ych 搭建的 oh-my-codex (OmX) 来端到端地组织的——这是一个建立在 OpenAI Codex (OpenAIDevs) 之上的工作流程层。我使用了 $team 模式进行并行代码审查并使用 $ralph 模式进行带有架构级验证的持久 执行循环。从阅读原始框架结构到生成带有测试的可用 Python 树整个移植过程都通过 OmX 的编排来驱动。 结果是一次“干净室”clean-room的 Python 重写它捕捉了 Claude Code 代理框架的架构模式而没有复制任何专有源代码 。我现在正与 bellman\_ychOmX 的创造者本人积极合作以进一步推动这项工作。基本的 Python 基础已经就位并可用但我 们才刚刚开始。请继续关注——一个能力更强大的版本正在路上。 The Creators Featured in Wall Street Journal For Avid Claude Code Fans ... Ive been deeply interested in harness engineering — studying how agent systems wire tools, orchestrate tasks, and ... manage runtime context. This isnt a sudden thing. The Wall Street Journal featured my work earlier this month, docu ... menting how Ive been one of the most active power users exploring these systems: ... ... AI startup worker Sigrid Jin, who attended the Seoul dinner, single-handedly used 25 billion of Claude Code tokens l ... ast year. At the time, usage limits were looser, allowing early enthusiasts to reach tens of billions of tokens at a ... very low cost. ... ... Despite his countless hours with Claude Code, Jin isnt faithful to any one AI lab. The tools available have differe ... nt strengths and weaknesses, he said. Codex is better at reasoning, while Claude Code generates cleaner, more sharea ... ble code. ... ... Jin flew to San Francisco in February for Claude Codes first birthday party, where attendees waited in line to comp ... are notes with Cherny. The crowd included a practicing cardiologist from Belgium who had built an app to help patien ... ts navigate care, and a California lawyer who made a tool for automating building permit approvals using Claude Code ... . ... ... It was basically like a sharing party, Jin said. There were lawyers, there were doctors, there were dentists. The ... y did not have software engineering backgrounds. ... ... — The Wall Street Journal, March 21, 2026, The Trillion Dollar Race to Automate Our Entire Lives Thinking... Heres a thinking process for translating the text: 1. **Analyze the Request:** The user has provided a section of text and wants it translated into Chinese. The tone is informative, narrative, and slightly celebratory regarding the work and the community. 2. **Analyze the Source Text (Segment by Segment):** * *The Creators Featured in Wall Street Journal For Avid Claude Code Fans* (Title) - Straightforward. * *Ive been deeply interested in harness engineering — studying how agent systems wire tools, orchestrate tasks, and manage runtime context.* (Focus on technical interest/definition) * *This isnt a sudden thing. The Wall Street Journal featured my work earlier this month, documenting how Ive been one of the most active power users exploring these systems:* (Context setting) * *AI startup worker Sigrid Jin, who attended the Seoul dinner, single-handedly used 25 billion of Claude Code tokens last year.* (Introducing the main example and key data) * *At the time, usage limits were looser, allowing early enthusiasts to reach tens of billions of tokens at a very low cost.* (Context on the market/cost) * *Despite his countless hours with Claude Code, Jin isnt faithful to any one AI lab. The tools available have different strengths and weaknesses, he said. Codex is better at reasoning, while Claude Code generates cleaner, more shareable code.* (Focus on comparative analysis) * *Jin flew to San Francisco in February for Claude Codes first birthday party, where attendees waited in line to compare notes with Cherny.* (Anecdote/Community interaction) * *The crowd included a practicing cardiologist from Belgium who had built an app to help patients navigate care, and a California lawyer who made a tool for automating building permit approvals using Claude Code.* (Examples of diverse users) * *It was basically like a sharing party, Jin said. There were lawyers, there were doctors, there were dentists. They did not have software engineering backgrounds.* (Key quote, emphasizing cross-disciplinary appeal) * *— The Wall Street Journal, March 21, 2026, The Trillion Dollar Race to Automate Our Entire Lives* (Citation) 3. **Draft the Translation (Focusing on Flow and Technical Accuracy):** * *Self-Correction/Refinement during drafting:* Ensure terms like harness engineering, agent systems, tokens, and the names/dates are handled clearly. The tone should remain professional yet engaging. 4. **Final Review against Original:** (Check the drafted Chinese against the English to ensure all nuances are captured.) (See the final output below.) 5. **Final Output Generation.** (This results in the polished translation provided below.) ...done thinking. 这段文字的翻译如下 *** **《华尔街日报》为热衷 Claude Code 的粉丝推荐的创作者们** 我对框架工程harness engineering一直抱有浓厚的兴趣——研究代理系统如何连接工具、编排任务以及管理运行时上下文。这 不是一个突然的想法。本月《华尔街日报》报道了我的工作记录了我如何成为探索这些系统的最活跃用户之一 人工智能初创公司员工 Sigrid Jin 参加了首尔晚宴去年她独自使用了 250 亿个 Claude Code 令牌tokens。当时使用限制 比较宽松允许早期爱好者以非常低廉的成本达到数万亿级别的令牌使用量。 尽管 Jin 花了无数时间与 Claude Code 合作但她并不忠于任何一个人工智能实验室。她说可用的工具各有其优势和劣势 Codex 在推理方面更强而 Claude Code 生成的代码则更简洁、更易于分享。 二月Jin 飞往旧金山参加了 Claude Code 的生日派对与 Cherny 一起等待入场互相交流心得。人群中包括一位来自比利时的 执业心脏病专家他开发了一个帮助患者导航医疗流程的应用程序还有一位加州律师他使用 Claude Code 制作了一个自动化建 筑许可审批的工具。 “这基本上就像一个分享会”Jin 说。“有律师有医生有牙医。他们没有软件工程的背景。” — 《华尔街日报》2026年3月21日《自动化我们整个生活的万亿美元竞赛》 Send a message (/? for help)