[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-ValueCell-ai--valuecell":3,"tool-ValueCell-ai--valuecell":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",150720,2,"2026-04-11T11:33:10",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",108322,"2026-04-10T11:39:34",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[52,13,15,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":32,"last_commit_at":59,"category_tags":60,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":67,"readme_en":68,"readme_zh":69,"quickstart_zh":70,"use_case_zh":71,"hero_image_url":72,"owner_login":73,"owner_name":74,"owner_avatar_url":75,"owner_bio":76,"owner_company":77,"owner_location":77,"owner_email":78,"owner_twitter":64,"owner_website":79,"owner_url":80,"languages":81,"stars":112,"forks":113,"last_commit_at":114,"license":115,"difficulty_score":32,"env_os":116,"env_gpu":117,"env_ram":117,"env_deps":118,"category_tags":122,"github_topics":123,"view_count":32,"oss_zip_url":77,"oss_zip_packed_at":77,"status":17,"created_at":136,"updated_at":137,"faqs":138,"releases":169},6612,"ValueCell-ai\u002Fvaluecell","valuecell","ValueCell is a community-driven, multi-agent platform for financial applications.","ValueCell 是一个由社区驱动的多智能体金融应用平台，旨在构建全球最大的去中心化金融代理社区。它如同一支顶尖的投资专家团队，能够协助用户完成股票筛选、深度研报生成、市场追踪乃至自动化交易等复杂任务。\n\n针对金融数据分析门槛高、信息过载以及个人隐私担忧等痛点，ValueCell 提供了高效的解决方案。其核心亮点在于独特的本地化安全架构，所有敏感数据均存储在用户本地设备中，从源头保障核心数据安全。同时，系统内置了多种专业智能体：DeepResearch Agent 能自动检索并分析基本面文档，生成可解释的深度洞察；Strategy Agent 支持多策略智能交易执行；News Retrieval Agent 则提供个性化的实时新闻推送。此外，平台具备极高的灵活性，兼容 OpenAI、DeepSeek 等多种大模型提供商，并覆盖美股、加密货币、港股及 A 股等全球主要市场数据。\n\nValueCell 既适合希望利用 AI 辅助投资决策的普通投资者，也深受开发者和量化研究人员的青睐。开发者可以基于其开放的多智能体框架进行二次开发与贡献，而研究人员则能借助其强大的数据处理能力探索市场规律。","ValueCell 是一个由社区驱动的多智能体金融应用平台，旨在构建全球最大的去中心化金融代理社区。它如同一支顶尖的投资专家团队，能够协助用户完成股票筛选、深度研报生成、市场追踪乃至自动化交易等复杂任务。\n\n针对金融数据分析门槛高、信息过载以及个人隐私担忧等痛点，ValueCell 提供了高效的解决方案。其核心亮点在于独特的本地化安全架构，所有敏感数据均存储在用户本地设备中，从源头保障核心数据安全。同时，系统内置了多种专业智能体：DeepResearch Agent 能自动检索并分析基本面文档，生成可解释的深度洞察；Strategy Agent 支持多策略智能交易执行；News Retrieval Agent 则提供个性化的实时新闻推送。此外，平台具备极高的灵活性，兼容 OpenAI、DeepSeek 等多种大模型提供商，并覆盖美股、加密货币、港股及 A 股等全球主要市场数据。\n\nValueCell 既适合希望利用 AI 辅助投资决策的普通投资者，也深受开发者和量化研究人员的青睐。开发者可以基于其开放的多智能体框架进行二次开发与贡献，而研究人员则能借助其强大的数据处理能力探索市场规律。无论是寻求自动化交易方案，还是想要深入理解市场动态，ValueCell 都能提供专业且安全的技术支持。","\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_b81f0f213daf.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\u003Cdiv align=\"center\" style=\"line-height: 2;\">\n    \u003Ca href=\"https:\u002F\u002Fwww.python.org\u002Fdownloads\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fpython-3.12+-blue.svg\"\n            alt=\"Python version\">\u003C\u002Fa>\n    \u003Ca href=\"LICENSE\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-Apache2.0-red.svg\"\n            alt=\"License: Apache2.0\">\u003C\u002Fa>  \n    \u003Cbr>\n    \u003Ca href=\"https:\u002F\u002Fdiscord.com\u002Finvite\u002F84Kex3GGAh\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fdiscord\u002F1399603591471435907?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb\"\n            alt=\"chat on Discord\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Fintent\u002Ffollow?screen_name=valuecell\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fvaluecell?logo=X&color=%20%23f5f5f5\"\n            alt=\"follow on X(Twitter)\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fvaluecell\u002F\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_006e5e7b2fbb.png\"\n            alt=\"follow on LinkedIn\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.facebook.com\u002Fpeople\u002FValueCell\u002F61581410516790\u002F\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_230e6192f37b.png\"\n            alt=\"follow on Facebook\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=C3tfHyGY9YE\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FWatch%20on-YouTube-red?logo=youtube\"\n            alt=\"Watch on YouTube\">\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ca href=\"README.md\" style=\"color: gray;\">English\u003C\u002Fa>\n  \u003Ca href=\"README.zh.md\" style=\"color: auto;\">中文（简体）\u003C\u002Fa>\n  \u003Ca href=\"README.zh_Hant.md\" style=\"color: auto;\">中文（繁體）\u003C\u002Fa>\n  \u003Ca href=\"README.ja.md\" style=\"color: auto;\">日本語\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\n# ValueCell\n\n## Our Product Launched 🔥🔥🔥\n\n **ValueCell now provides A-share deep research, market analysis and requires no deployment—access directly at [valuecell.ai](https:\u002F\u002Fvaluecell.ai).**\n\n## Description\n\nValueCell is a community-driven, multi-agent platform for financial applications. Our mission is to build the world's largest decentralized financial agent community.\n\nIt provides a team of TOP investment Agents to help you with stock selection, research, tracking, and even trading.\n\nThe system keeps all your sensitive information stored locally on your device, ensuring core data security.\n\nWelcome to join our Discord community to share feedback and issues you encounter, and invite more developers to contribute 🔥🔥🔥\n\n>Note: ValueCell team members will never proactively contact community participants. This project is for technical exchange only. Investing involves risk. ⚠️\n\n# Screenshot\n\n[![Watch the video](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_eed58ed02bb3.jpg)](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=C3tfHyGY9YE)\n\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_cbce2414f4a6.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_933143a11431.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\n# Key Features\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_00c969c9d280.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\n## Multi-Agent System\n- **DeepResearch Agent**: Automatically retrieve and analyze fundamental documents to generate accurate data insights and interpretable summaries\n- **Strategy Agent**: Supports multiple crypto assets and multi-strategy smart trading, automatically executing your strategies\n- **News Retrieval Agent**: Supports personalized scheduled news delivery to track key information in real time\n- **Others**: More agents are in planning...\n\n## Flexible Integrations\n- **Multiple LLM Providers**: Support OpenRouter, SiliconFlow,Azure,Openai-compatible,Google,OpenAI and DeepSeek\n- **Popular Market Data**: Cover US market, Crypto market, Hong Kong market, China market and more\n- **Multi-Agent Framework Compatible**: Support Langchain, Agno by A2A Protocol for research and development integration\n- **Exchange Connectivity**: Live routing to OKX and Binance, featuring built-in guardrails\n\n# Quick Start\n\n## New Users\n\nTo get started quickly, download the latest ValueCell application for MacOS or Windows from the [Releases page](https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Freleases) on GitHub.\n\nAfter installation, please configure your preferred model provider before using ValueCell for the first time. Refer to the instructions in the application or documentation as needed.\n\n### Live Trading\n\n- Configure AI Models: Add your AI Model API Key through the web interface.\n- Configure Exchanges: Set up Binance\u002FHyperLiquid\u002FOKX\u002FCoinbase... API credentials\n- Create Strategies: Combine AI model with exchange to create custom strategies\n- Monitor & Control: Start\u002Fstop traders and monitor performance in real-time\n- Note: Currently only supports contract trading (spot is implemented as 1X contracts), so please ensure your contract account has sufficient balance\n\n#### Supported Exchanges\n\n| Exchange | Notes | Status |\n| --- | --- | --- |\n| **Binance** | Only supports international site [binance.com](binance.com), not US site. Uses USDT-M futures (USDT-margined contracts). Ensure your futures account has sufficient USDT balance. Trading pair format: `BTC\u002FUSDT`. Note: Ensure perpetual contract account balance is not 0. When applying for API, add IP whitelist by searching `My IP` in search engine | ✅ Tested |\n| **Hyperliquid** | Only supports USDC as margin currency. Uses your main wallet address + API wallet private key authentication (use [API tab](https:\u002F\u002Fapp.hyperliquid.xyz\u002FAPI) to apply). Market orders are automatically converted to IoC limit orders. Trading pair format must be manually adjusted to `SYMBOL\u002FUSDC` (e.g., `WIF\u002FUSDC`). Configure with main wallet address + API wallet private key. Minimum 10U per trade | ✅ Tested |\n| **OKX** | Requires API Key, Secret, and Passphrase (OKX account password) for authentication. Supports USDT-margined contracts. Trading pair format: `BTC\u002FUSDT` | ✅ Tested |\n| Coinbase | Supports USDT-margined contracts. Coinbase International is not yet supported | 🟡 Partially Tested |\n| Gate.io | Supports USDT-margined contracts. Requires API Key and Secret | 🟡 Partially Tested |\n| MEXC | Supports USDT-margined contracts. Requires API Key and Secret | 🟡 Partially Tested |\n| Blockchain | Supports USDT-margined contracts. Requires API Key, Secret | 🟡 Partially Tested |\n\n**Legend**:\n- ✅ **Tested**: Fully tested and verified in production environment\n- 🟡 **Partially Tested**: Code implementation complete but not fully tested, may require debugging\n- **Recommended**: Prioritize using fully tested exchanges (Binance, Hyperliquid, OKX)\n\n### Notice\n- Currently supports leverage trading only, so you need to ensure your Perps account has sufficient balance.\n- You must keep your API secrets secure to avoid losing funds. The app stores secrets locally on your device and will not send them to any third party over the internet.\n- To ensure your account safety, you need to reset your API keys regularly. \n\n---\n\n**Note**: Before running the application, ensure all prerequisites are installed and environment variables are properly configured. If it has been a long time since the last update, you can delete local data stores and start fresh:\n- LanceDB directory (stored in your system application directory, same path as `.env`):\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Flancedb`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002Flancedb`\n  - Windows: `%APPDATA%\\\\ValueCell\\\\lancedb`\n- Knowledge directory (stored in your system application directory, same path as `.env`):\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002F.knowledge`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002F.knowledge`\n  - Windows: `%APPDATA%\\\\ValueCell\\\\.knowledge`\n- SQLite database file (stored in your system application directory, same path as `.env`):\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Fvaluecell.db`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002Fvaluecell.db`\n  - Windows: `%APPDATA%\\\\ValueCell\\\\valuecell.db`\n\n\n## Developers\n\nWe sincerely invite all developers to join our Discord discussion group, where we regularly share the community roadmap and upcoming contributor benefit plans.\n\nDetails on development processes and standards are provided below:[CONTRIBUTING.md](.github\u002FCONTRIBUTING.md)\n\nValueCell is a Python-based application with a comprehensive web interface, supporting multi-platform deployment. Follow the configuration below to get started quickly.\n\n## Clone Repository\n\n   ```bash\n   git clone https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell.git\n   cd valuecell\n   ```\n\n## Running the Application\n\nLaunch the complete application (frontend, backend, and agents):\n\n### Linux \u002F Macos\n```bash\nbash start.sh\n```\n\n### Windows (PowerShell)\n```powershell\n.\\start.ps1\n```\n\n### Accessing the Interface\n\n- **Web UI**: Navigate to [http:\u002F\u002Flocalhost:1420](http:\u002F\u002Flocalhost:1420) in your browser\n- **Logs**: View application logs directly in the terminal for detailed runtime information of backend services and individual agents\n\n### Next Steps\n\nOnce the application is running, you can explore the web interface to interact with ValueCell's features and capabilities.\n\n### Configuration\n\nMore detailed configuration information can be found at [CONFIGURATION_GUIDE](.\u002Fdocs\u002FCONFIGURATION_GUIDE.md)\n\n# Roadmap\n\n## 🤖 Enhanced Agent Capabilities\n### Trading Capabilities\n- **Crypto**: Supports OKX、Binance and Hyperliquid exchanges, with more exchanges planned for integration...\n- **Securities**: Gradually support AI securities trading\n\n### Market Expansion\n- **European Markets**: Add support for FTSE, DAX, CAC 40, and other European exchanges\n- **Asian Markets**: Expand coverage to Nikkei and emerging Asian markets\n- **Commodity Markets**: Oil, Gold, Silver, Agricultural products analysis\n- **Forex Markets**: Major currency pairs and cross-currency analysis\n\n### Asset Diversification\n- **Fixed Income**: Government bonds, corporate bonds, and yield analysis agents\n- **Derivatives**: Options, futures, and complex financial instruments\n- **Alternative Investments**: Private equity, hedge funds, and venture capital analysis\n\n### Advanced Notification & Push Types\n- **Real-time Alerts**: Price movements, volume spikes, and technical breakouts\n- **Scheduled Reports**: Daily\u002Fweekly\u002Fmonthly portfolio summaries\n- **Event-driven Notifications**: Earnings releases, dividend announcements, regulatory changes\n- **Custom Triggers**: User-defined conditions and thresholds\n- **Multi-channel Delivery**: Discord and webhook integrations\n\n## ⚙️ Product Configuration & Personalization\n### Multi-platform Products\n- **Desktop Support**: Gradually support desktop and client capabilities\n- **Database Hot Updates**: Gradually support compatibility upgrades\n\n### Internationalization (i18n)\n- **Multi-language Support**: English, Chinese (Simplified\u002FTraditional), Japanese, Korean, Spanish, French\n- **Localized Market Data**: Region-specific financial terminology and formats\n- **Cultural Adaptation**: Time zones, date formats, and currency preferences\n- **Agent Personality Localization**: Culturally appropriate communication styles\n\n### Token & Authentication Management\n- **API Key Management**: Secure storage and rotation of third-party API keys\n- **OAuth Integration**: Support for major financial data providers\n\n### User Preferences & Customization\n- **Investment Profile**: Risk tolerance, investment horizon, and strategy preferences\n- **UI\u002FUX Customization**: Dark\u002Flight mode, dashboard layouts, and widget preferences\n- **Agent Behavior**: Communication frequency, analysis depth, and reporting style\n- **Portfolio Management**: Custom benchmarks, performance metrics, and allocation targets\n\n### Memory & Learning Systems\n- **Conversation History**: Persistent chat history across sessions\n- **User Learning**: Adaptive recommendations based on user behavior\n- **Market Memory**: Historical context and pattern recognition\n- **Preference Evolution**: Dynamic adjustment of recommendations over time\n\n## 🔧 ValueCell SDK Development\n### Core SDK Features\n- **Python SDK**: Comprehensive library for agent integration and customization\n- **WebSocket Support**: Real-time data streaming and bidirectional communication\n\n### Agent Integration Framework\n- **Plugin Architecture**: Easy integration of third-party agents and tools\n- **Agent Registry**: Marketplace for community-contributed agents\n\n### Developer Tools & Documentation\n- **Interactive API Explorer**: Swagger\u002FOpenAPI documentation with live testing\n- **Code Examples**: Sample implementations in multiple programming languages\n- **Testing Framework**: Unit tests, integration tests, and mock data providers\n\n# LICENSE\n\nThis project is licensed under the **Apache License 2.0** — see the [LICENSE](.\u002FLICENSE) file for details.\n\n> 📌 Note: Apache 2.0 applies **only to original code authored by the ValueCell team and contributors**. Third-party components (e.g., APIs, widgets, libraries) are governed by their own licenses and terms — see below.\n\n## Third-Party Components & Licensing\n\nValueCell integrates external services and embeds third-party widgets. Their usage is **not covered by Apache 2.0**, and compliance with their terms is your responsibility as a user\u002Fdeveloper.\n\n| Component | Type | License \u002F Terms |\n|---------|------|-----------------|\n| **TradingView Advanced Chart** | Embedded iframe widget | [Free Advanced Charts Agreement](https:\u002F\u002Fwww.tradingview.com\u002Fchart-embedding\u002F) (proprietary) |\n| **Exchange APIs** (Binance, OKX, Hyperliquid, etc.) | REST\u002FWebSocket endpoints | Each exchange’s ToS (e.g., [Binance API Terms](https:\u002F\u002Fwww.binance.com\u002Fen\u002Fterms)) |\n| **LLM Providers** (OpenAI, Azure, Google, DeepSeek, etc.) | Inference APIs | Provider-specific ToS (e.g., [OpenAI ToS](https:\u002F\u002Fopenai.com\u002Fpolicies\u002Fterms-of-use)) |\n\n# Star History\n\n\u003Cdiv align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fwww.star-history.com\u002F#ValueCell-ai\u002Fvaluecell&Date\">\n \u003Cpicture>\n   \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png&theme=dark\" \u002F>\n   \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png\" \u002F>\n   \u003Cimg alt=\"TradingAgents Star History\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png\" style=\"width: 80%; height: auto;\" \u002F>\n \u003C\u002Fpicture>\n\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n","\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_b81f0f213daf.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\u003Cdiv align=\"center\" style=\"line-height: 2;\">\n    \u003Ca href=\"https:\u002F\u002Fwww.python.org\u002Fdownloads\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fpython-3.12+-blue.svg\"\n            alt=\"Python版本\">\u003C\u002Fa>\n    \u003Ca href=\"LICENSE\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-Apache2.0-red.svg\"\n            alt=\"许可证：Apache2.0\">\u003C\u002Fa>  \n    \u003Cbr>\n    \u003Ca href=\"https:\u002F\u002Fdiscord.com\u002Finvite\u002F84Kex3GGAh\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fdiscord\u002F1399603591471435907?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb\"\n            alt=\"在Discord上聊天\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Ftwitter.com\u002Fintent\u002Ffollow?screen_name=valuecell\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fvaluecell?logo=X&color=%20%23f5f5f5\"\n            alt=\"在X(Twitter)上关注\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fvaluecell\u002F\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_006e5e7b2fbb.png\"\n            alt=\"在LinkedIn上关注\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.facebook.com\u002Fpeople\u002FValueCell\u002F61581410516790\u002F\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_230e6192f37b.png\"\n            alt=\"在Facebook上关注\">\u003C\u002Fa>\n    \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=C3tfHyGY9YE\" target=\"_blank\">\n        \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F观看-YouTube-红色?logo=youtube\"\n            alt=\"在YouTube上观看\">\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ca href=\"README.md\" style=\"color: gray;\">English\u003C\u002Fa>\n  \u003Ca href=\"README.zh.md\" style=\"color: auto;\">中文（简体）\u003C\u002Fa>\n  \u003Ca href=\"README.zh_Hant.md\" style=\"color: auto;\">中文（繁體）\u003C\u002Fa>\n  \u003Ca href=\"README.ja.md\" style=\"color: auto;\">日本語\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\n# ValueCell\n\n## 我们的产品已上线 🔥🔥🔥\n\n **ValueCell 现已提供A股深度研究、市场分析服务，无需部署——直接访问 [valuecell.ai](https:\u002F\u002Fvaluecell.ai) 即可。**\n\n## 描述\n\nValueCell 是一个由社区驱动的多智能体金融应用平台。我们的使命是构建全球最大的去中心化金融智能体社区。\n\n它提供了一支顶尖的投资智能体团队，帮助您进行股票选择、研究、跟踪，甚至交易。\n\n系统会将您的所有敏感信息本地存储在设备上，确保核心数据的安全性。\n\n欢迎加入我们的 Discord 社区，分享反馈和遇到的问题，并邀请更多开发者参与贡献 🔥🔥🔥\n\n>注：ValueCell 团队成员绝不会主动联系社区参与者。本项目仅用于技术交流。投资有风险。⚠️\n\n# 截图\n\n[![观看视频](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_eed58ed02bb3.jpg)](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=C3tfHyGY9YE)\n\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_cbce2414f4a6.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_933143a11431.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\n# 核心功能\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_00c969c9d280.png\" style=\"width: 100%; height: auto;\">\n\u003C\u002Fp>\n\n\n## 多智能体系统\n- **深度研究智能体**：自动检索并分析基本面文件，生成准确的数据洞察和可解释的摘要\n- **策略智能体**：支持多种加密资产和多策略智能交易，自动执行您的策略\n- **新闻检索智能体**：支持个性化定时推送新闻，实时跟踪关键信息\n- **其他**：更多智能体正在规划中...\n\n## 灵活集成\n- **多种LLM提供商**：支持 OpenRouter、SiliconFlow、Azure、OpenAI兼容、Google、OpenAI 和 DeepSeek\n- **热门市场数据**：覆盖美国市场、加密货币市场、香港市场、中国市场等\n- **多智能体框架兼容**：支持 Langchain、Agno by A2A Protocol，便于研发集成\n- **交易所对接**：实时路由至 OKX 和 Binance，内置护栏机制\n\n# 快速开始\n\n## 新用户\n\n要快速上手，请从 GitHub 的 [Releases 页面](https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Freleases) 下载适用于 MacOS 或 Windows 的最新 ValueCell 应用程序。\n\n安装完成后，请在首次使用 ValueCell 之前配置您首选的模型提供商。如有需要，请参考应用程序或文档中的说明。\n\n### 实时交易\n\n- 配置 AI 模型：通过网页界面添加您的 AI 模型 API 密钥。\n- 配置交易所：设置 Binance\u002FHyperLiquid\u002FOKX\u002FCoinbase... 的 API 凭证\n- 创建策略：将 AI 模型与交易所结合，创建自定义策略\n- 监控与控制：实时启动\u002F停止交易员并监控表现\n- 注意：目前仅支持合约交易（现货以 1 倍合约形式实现），请确保您的合约账户有足够的余额\n\n#### 支持的交易所\n\n| 交易所 | 备注 | 状态 |\n| --- | --- | --- |\n| **Binance** | 仅支持国际站 [binance.com](binance.com)，不支持美国站。使用 USDT-M 期货（USDT保证金合约）。请确保您的期货账户有足够的 USDT 余额。交易对格式：`BTC\u002FUSDT`。注意：永续合约账户余额不得为 0。申请 API 时，请通过搜索引擎搜索“我的 IP”来添加 IP 白名单 | ✅ 已测试 |\n| **Hyperliquid** | 仅支持 USDC 作为保证金货币。使用您的主钱包地址 + API 钱包私钥认证（请使用 [API 选项卡](https:\u002F\u002Fapp.hyperliquid.xyz\u002FAPI) 申请）。市价单会自动转换为限价单 IoC。交易对格式必须手动调整为 `SYMBOL\u002FUSDC`（例如 `WIF\u002FUSDC`）。请使用主钱包地址 + API 钱包私钥进行配置。每笔交易最低 10U | ✅ 已测试 |\n| **OKX** | 需要 API 密钥、密钥和密码短语（OKX 账户密码）进行认证。支持 USDT 保证金合约。交易对格式：`BTC\u002FUSDT` | ✅ 已测试 |\n| Coinbase | 支持 USDT 保证金合约。Coinbase International 尚未支持 | 🟡 部分测试 |\n| Gate.io | 支持 USDT 保证金合约。需要 API 密钥和密钥 | 🟡 部分测试 |\n| MEXC | 支持 USDT 保证金合约。需要 API 密钥和密钥 | 🟡 部分测试 |\n| Blockchain | 支持 USDT 保证金合约。需要 API 密钥、密钥 | 🟡 部分测试 |\n\n**图例**：\n- ✅ **已测试**：已在生产环境中完全测试并验证\n- 🟡 **部分测试**：代码实现已完成但尚未完全测试，可能需要调试\n- **推荐**：优先使用已测试的交易所（Binance、Hyperliquid、OKX）\n\n### 通知\n- 目前仅支持杠杆交易，因此请确保您的永续合约账户有足够的余额。\n- 请务必妥善保管您的 API 密钥，以避免资金损失。该应用会在您设备本地存储密钥，不会通过互联网将其发送给任何第三方。\n- 为保障账户安全，建议您定期重置 API 密钥。\n\n---\n\n**注意**：在运行应用程序之前，请确保已安装所有先决条件，并正确配置环境变量。如果距离上次更新时间较长，您可以删除本地数据存储并重新开始：\n- LanceDB 目录（存储在系统应用程序目录中，与 `.env` 文件路径相同）：\n  - macOS：`~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Flancedb`\n  - Linux：`~\u002F.config\u002Fvaluecell\u002Flancedb`\n  - Windows：`%APPDATA%\\\\ValueCell\\\\lancedb`\n- 知识库目录（存储在系统应用程序目录中，与 `.env` 文件路径相同）：\n  - macOS：`~\u002FLibrary\u002FApplication Support\u002FValueCell\u002F.knowledge`\n  - Linux：`~\u002F.config\u002Fvaluecell\u002F.knowledge`\n  - Windows：`%APPDATA%\\\\ValueCell\\\\.knowledge`\n- SQLite 数据库文件（存储在系统应用程序目录中，与 `.env` 文件路径相同）：\n  - macOS：`~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Fvaluecell.db`\n  - Linux：`~\u002F.config\u002Fvaluecell\u002Fvaluecell.db`\n  - Windows：`%APPDATA%\\\\ValueCell\\\\valuecell.db`\n\n\n## 开发者\n\n我们诚挚邀请各位开发者加入我们的 Discord 讨论群，在那里我们会定期分享社区路线图及即将推出的贡献者福利计划。\n\n开发流程和标准的详细信息如下：[CONTRIBUTING.md](.github\u002FCONTRIBUTING.md)\n\nValueCell 是一款基于 Python 的应用程序，配备完善的 Web 界面，支持多平台部署。请按照以下配置快速上手。\n\n## 克隆仓库\n\n   ```bash\n   git clone https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell.git\n   cd valuecell\n   ```\n\n## 运行应用程序\n\n启动完整应用（前端、后端和智能体）：\n\n### Linux \u002F macOS\n```bash\nbash start.sh\n```\n\n### Windows（PowerShell）\n```powershell\n.\\start.ps1\n```\n\n### 访问界面\n\n- **Web UI**：在浏览器中访问 [http:\u002F\u002Flocalhost:1420](http:\u002F\u002Flocalhost:1420)\n- **日志**：可在终端直接查看应用日志，获取后端服务和各智能体的详细运行信息\n\n### 后续步骤\n\n应用程序启动后，您可以通过 Web 界面探索 ValueCell 的各项功能与特性。\n\n### 配置\n\n更多详细的配置信息请参阅 [CONFIGURATION_GUIDE](.\u002Fdocs\u002FCONFIGURATION_GUIDE.md)\n\n# 路线图\n\n## 🤖 智能体能力增强\n### 交易能力\n- **加密货币**：支持 OKX、Binance 和 Hyperliquid 交易所，未来还将接入更多交易所……\n- **证券**：逐步支持 AI 证券交易\n\n### 市场扩展\n- **欧洲市场**：新增对富时指数、DAX、CAC 40 等欧洲交易所的支持\n- **亚洲市场**：扩大覆盖范围至日经指数及新兴亚洲市场\n- **大宗商品市场**：石油、黄金、白银及农产品分析\n- **外汇市场**：主要货币对及交叉货币对分析\n\n### 资产多元化\n- **固定收益**：政府债券、公司债券及收益率分析智能体\n- **衍生品**：期权、期货及其他复杂金融工具\n- **另类投资**：私募股权、对冲基金及风险投资分析\n\n### 高级通知与推送类型\n- **实时警报**：价格波动、成交量激增及技术突破\n- **定时报告**：每日\u002F每周\u002F每月的投资组合摘要\n- **事件驱动通知**：财报发布、股息公告、监管变化等\n- **自定义触发器**：用户设定的条件和阈值\n- **多渠道推送**：集成 Discord 和 Webhook\n\n## ⚙️ 产品配置与个性化\n### 多平台产品\n- **桌面支持**：逐步支持桌面端及客户端功能\n- **数据库热更新**：逐步实现兼容性升级\n\n### 国际化 (i18n)\n- **多语言支持**：英语、简体中文、繁体中文、日语、韩语、西班牙语、法语\n- **本地化市场数据**：特定地区的金融术语和格式\n- **文化适配**：时区、日期格式和货币偏好\n- **智能体个性本地化**：符合当地文化的沟通风格\n\n### Token 与认证管理\n- **API 密钥管理**：第三方 API 密钥的安全存储与轮换\n- **OAuth 集成**：支持主要的金融数据提供商\n\n### 用户偏好与定制\n- **投资档案**：风险承受能力、投资期限及策略偏好\n- **UI\u002FUX 定制**：深色\u002F浅色模式、仪表盘布局及小部件偏好\n- **智能体行为**：沟通频率、分析深度及报告风格\n- **投资组合管理**：自定义基准、绩效指标及资产配置目标\n\n### 内存与学习系统\n- **对话历史**：跨会话持久化聊天记录\n- **用户学习**：根据用户行为提供自适应推荐\n- **市场记忆**：历史背景与模式识别\n- **偏好演变**：随时间动态调整推荐内容\n\n## 🔧 ValueCell SDK 开发\n### 核心 SDK 功能\n- **Python SDK**：用于智能体集成与定制的全面库\n- **WebSocket 支持**：实时数据流与双向通信\n\n### 智能体集成框架\n- **插件架构**：便于集成第三方智能体和工具\n- **智能体注册中心**：社区贡献智能体的市场平台\n\n### 开发者工具与文档\n- **交互式 API 浏览器**：支持 Swagger\u002FOpenAPI 文档及在线测试\n- **代码示例**：多种编程语言的实现范例\n- **测试框架**：单元测试、集成测试及模拟数据提供者\n\n# 许可证\n\n本项目采用 **Apache License 2.0** 许可——详情请参阅 [LICENSE](.\u002FLICENSE) 文件。\n\n> 📌 注意：Apache 2.0 仅适用于 ValueCell 团队及贡献者编写的原创代码。第三方组件（如 API、小部件、库等）受其各自许可证和条款约束——详情见下文。\n\n## 第三方组件与许可\n\nValueCell 集成了外部服务并嵌入了第三方小部件。这些组件的使用 **不受 Apache 2.0 许可证的覆盖**，遵守其条款是您作为用户或开发者的责任。\n\n| 组件 | 类型 | 许可证 \u002F 条款 |\n|---------|------|-----------------|\n| **TradingView 高级图表** | 嵌入式 iframe 小部件 | [免费高级图表协议](https:\u002F\u002Fwww.tradingview.com\u002Fchart-embedding\u002F)（专有） |\n| **交易所 API**（币安、欧易、Hyperliquid 等） | REST\u002FWebSocket 端点 | 各自交易所的服务条款（例如：[币安 API 条款](https:\u002F\u002Fwww.binance.com\u002Fen\u002Fterms)） |\n| **大语言模型提供商**（OpenAI、Azure、Google、DeepSeek 等） | 推理 API | 提供商特定的服务条款（例如：[OpenAI 服务条款](https:\u002F\u002Fopenai.com\u002Fpolicies\u002Fterms-of-use)） |\n\n# 星标历史\n\n\u003Cdiv align=\"center\">\n\u003Ca href=\"https:\u002F\u002Fwww.star-history.com\u002F#ValueCell-ai\u002Fvaluecell&Date\">\n \u003Cpicture>\n   \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png&theme=dark\" \u002F>\n   \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png\" \u002F>\n   \u003Cimg alt=\"TradingAgents 星标历史\" src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_readme_f8907efc6b8a.png\" style=\"width: 80%; height: auto;\" \u002F>\n \u003C\u002Fpicture>\n\u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">","# ValueCell 快速上手指南\n\nValueCell 是一个社区驱动的多智能体金融应用平台，旨在提供股票选股、深度研究、市场追踪及自动化交易能力。所有敏感数据均本地存储，确保核心数据安全。\n\n## 环境准备\n\n### 系统要求\n- **操作系统**: macOS, Linux, 或 Windows (PowerShell)\n- **Python 版本**: Python 3.12 或更高版本\n- **网络环境**: 需能访问 GitHub 及所选 LLM 提供商接口（如 OpenAI, DeepSeek, SiliconFlow 等）\n\n### 前置依赖\n确保已安装 Git 和 Python 3.12+。\n```bash\npython --version  # 确认版本 >= 3.12\ngit --version\n```\n\n## 安装步骤\n\n### 1. 克隆仓库\n使用 Git 克隆项目代码到本地：\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell.git\ncd valuecell\n```\n\n> **提示**：国内用户若克隆速度慢，可尝试配置 Git 加速或使用镜像源。\n\n### 2. 启动应用\n根据操作系统选择对应的启动脚本，该脚本将自动安装依赖并启动前端、后端及智能体服务。\n\n**Linux \u002F macOS:**\n```bash\nbash start.sh\n```\n\n**Windows (PowerShell):**\n```powershell\n.\\start.ps1\n```\n\n## 基本使用\n\n### 1. 访问界面\n启动成功后，在浏览器中打开以下地址：\n```text\nhttp:\u002F\u002Flocalhost:1420\n```\n终端窗口将实时显示后端服务和各智能体的运行日志。\n\n### 2. 初始配置\n首次使用前，需在 Web 界面完成以下配置：\n- **配置 AI 模型**: 添加您偏好的 LLM 提供商 API Key（支持 OpenRouter, SiliconFlow, Azure, OpenAI, DeepSeek 等）。\n- **配置交易所 (可选)**: 若需进行实盘交易，需设置 Binance, OKX, HyperLiquid 等交易所的 API 凭证。\n  - *注意*: 目前仅支持合约交易（现货以 1 倍合约形式实现），请确保合约账户有足够余额。\n\n### 3. 创建策略\n- 在界面中选择已配置的 AI 模型和交易所。\n- 创建自定义交易策略或启用预设的智能体（如深度研究智能体、新闻检索智能体）。\n- 启动交易员并实时监控表现。\n\n### 4. 数据重置 (可选)\n若长时间未更新或需清除本地缓存数据，可删除以下目录后重新启动：\n- **LanceDB 目录**:\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Flancedb`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002Flancedb`\n  - Windows: `%APPDATA%\\ValueCell\\lancedb`\n- **知识库目录**:\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002F.knowledge`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002F.knowledge`\n  - Windows: `%APPDATA%\\ValueCell\\.knowledge`\n- **SQLite 数据库**:\n  - macOS: `~\u002FLibrary\u002FApplication Support\u002FValueCell\u002Fvaluecell.db`\n  - Linux: `~\u002F.config\u002Fvaluecell\u002Fvaluecell.db`\n  - Windows: `%APPDATA%\\ValueCell\\valuecell.db`\n\n更多详细配置请参考项目文档 `docs\u002FCONFIGURATION_GUIDE.md`。","一位专注于美股与加密货币市场的独立量化交易者，试图在波动剧烈的行情中同时执行基本面深度调研与多策略自动交易，却受限于个人精力与数据整合能力。\n\n### 没有 valuecell 时\n- **信息获取滞后且碎片化**：需要手动在多个新闻源、财报网站和链上数据平台间切换，难以实时捕捉影响股价的关键突发新闻或深层基本面变化。\n- **策略执行依赖人工盯盘**：即使制定了复杂的交易逻辑，也必须时刻守在屏幕前监控信号，一旦错过最佳点位或遇到夜间行情，极易造成亏损。\n- **数据分析深度不足**：面对海量的招股书、年报等非结构化文档，缺乏自动化工具进行快速提取与解读，导致投资判断往往基于表面数据而非深度洞察。\n- **多模型切换成本高**：想要对比不同大模型（如 DeepSeek 与 OpenAI）对同一市场事件的分析差异，需分别调用 API 并整理结果，流程繁琐且易出错。\n\n### 使用 valuecell 后\n- **全渠道情报自动聚合**：News Retrieval Agent 按预设计划实时抓取并推送个性化财经新闻，DeepResearch Agent 自动研读财报生成可解释的深度摘要，确保决策依据全面且及时。\n- **7x24 小时智能策略执行**：Strategy Agent 接管交易环节，支持加密货币与美股的多策略自动运行，无需人工盯盘即可精准执行买卖指令，彻底解放交易者的时间。\n- **深度基本面一键洞察**：利用多智能体协作，自动从冗长的金融文档中提取核心数据并生成分析结论，让独立交易者也能拥有机构级的投研深度。\n- **灵活模型无缝集成**：通过统一接口轻松切换 OpenRouter、SiliconFlow 等多种 LLM 提供商，快速验证不同模型在市场分析中的表现，优化决策算法。\n\nvaluecell 将分散的投研、监控与交易环节整合为自动化闭环，让个人投资者能以极低的部署成本，享受到媲美专业机构的分布式多智能体金融服务。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FValueCell-ai_valuecell_b81f0f21.png","ValueCell-ai","ValueCell.ai","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002FValueCell-ai_87bfbce1.png","",null,"public@valuecell.ai","valuecell.ai","https:\u002F\u002Fgithub.com\u002FValueCell-ai",[82,86,90,94,98,102,106,110],{"name":83,"color":84,"percentage":85},"Python","#3572A5",75.2,{"name":87,"color":88,"percentage":89},"TypeScript","#3178c6",23.1,{"name":91,"color":92,"percentage":93},"Rust","#dea584",0.6,{"name":95,"color":96,"percentage":97},"PowerShell","#012456",0.5,{"name":99,"color":100,"percentage":101},"Shell","#89e051",0.3,{"name":103,"color":104,"percentage":105},"CSS","#663399",0.2,{"name":107,"color":108,"percentage":109},"Makefile","#427819",0,{"name":111,"color":77,"percentage":109},"NSIS",10292,1749,"2026-04-11T09:09:00","Apache-2.0","Linux, macOS, Windows","未说明",{"notes":119,"python":120,"dependencies":121},"该项目提供预编译的桌面应用程序（MacOS\u002FWindows）供普通用户使用，开发者可通过脚本启动包含前后端的多代理系统。主要依赖外部 LLM 提供商（如 OpenAI, DeepSeek 等）和交易所 API。数据存储于本地（使用 LanceDB 和 SQLite），首次运行或更新后可能需要清理本地数据目录。目前仅支持合约交易，需确保账户有足够余额。","3.12+",[117],[14,13,15],[124,125,126,127,128,129,130,131,132,133,134,135],"agentic-ai","agents","ai","assitant","crypto","equity","finance","investment","mcp","python","react","stock-market","2026-03-27T02:49:30.150509","2026-04-11T22:06:38.705798",[139,144,149,154,159,164],{"id":140,"question_zh":141,"answer_zh":142,"source_url":143},29868,"如何从不同 IP 或云服务器外部访问 ValueCell？","若部署在云服务器上无法通过 IP 访问，需进行以下配置：\n1. 在项目根目录的 `.env` 文件中设置：`API_HOST=0.0.0.0`\n2. 在 `frontend\u002F.env` 文件中设置前端地址（将 IP 替换为你自己的服务器 IP）：\n   `TAURI_DEV_HOST=你的服务器 IP`\n   `VITE_API_BASE_URL=\"http:\u002F\u002F你的服务器 IP:8000\u002Fapi\u002Fv1\"`\n3. 确保云服务器的安全组已开放相应端口（如 1420 和 8000）。\n另外，也可以修改 `frontend\u002Fpackage.json` 中的 dev 脚本为 `\"dev\": \"react-router dev --host 0.0.0.0\"`，但建议优先修改 `.env` 文件以避免代码更新时被重置。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F279",{"id":145,"question_zh":146,"answer_zh":147,"source_url":148},29869,"为什么首页显示股票历史价格数据不可用（如 SSE:000001, HKEX:HSI, NASDAQ:IXIC）？","该问题通常与网络环境或数据源配置有关。目前官方尚未完全复现此问题，但社区反馈表明：\n1. 检查网络连接，确保能访问 Yahoo Finance 或 AKShare 数据源。\n2. 尝试使用 `git pull` 更新代码到最新版本。\n3. 删除项目目录下的 `valuecell.db` 文件并重启应用。\n4. 部分用户反馈仅能通过 AKShare API 获取 NASDAQ 数据，Yahoo Finance 可能受限。若使用雪球（Xueqiu）Token 仍无效，可能需要等待官方修复或切换数据适配器配置。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F196",{"id":150,"question_zh":151,"answer_zh":152,"source_url":153},29870,"Agent 一直运行但没有输出，且持续扣除 OpenRouter 额度怎么办？","如果 ResearchAgent 等智能体长时间运行无输出且日志中只有重复的 HTTP 请求，可能是模型配置或循环调用问题。解决方案：\n1. 项目已引入新的配置系统，请参考官方 [配置指南](https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fblob\u002Fmain\u002Fdocs\u002FCONFIGURATION_GUIDE.md)。\n2. 保留 `SILICONFLOW_API_KEY` 和 `OPENROUTER_API_KEY`，但在 yaml 或 `.env` 文件中调整 Agent 的模型配置，避免无限循环。\n3. 检查是否因提示词过长或模型参数设置不当导致死循环，必要时限制最大 token 数或更换模型。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F184",{"id":155,"question_zh":156,"answer_zh":157,"source_url":158},29871,"Mac 用户按照文档配置环境变量后仍无法打开网址（页面空白）如何解决？","Mac 用户遇到页面空白问题时，建议：\n1. 确认 `.env` 文件已正确配置且无语法错误。\n2. 检查前端服务是否正常启动，尝试访问 `http:\u002F\u002Flocalhost:1420` 或指定端口。\n3. 若问题依旧，请加入官方 Discord 社区获取交互式支持，或在 GitHub 新建 Issue 并提供详细的系统环境、启动日志和 `.env` 配置（注意脱敏敏感信息），以便维护者定位问题。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F350",{"id":160,"question_zh":161,"answer_zh":162,"source_url":163},29872,"部署到服务器后页面查询结果为空白且一直报错，如何处理？","服务器部署后页面空白通常是因为前端未绑定到外部 IP。解决方法：\n1. 修改根目录 `.env` 文件，设置 `API_HOST=0.0.0.0`。\n2. 若修改 `frontend\u002Fpackage.json` 中的 scripts 添加 `--host 0.0.0.0`，请注意该文件在 git pull 更新时会被还原，因此推荐直接修改 `.env` 文件。\n3. 确认服务器防火墙和安全组已开放所需端口（如 8000 和 1420）。\n4. 重启前后端服务使配置生效。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F304",{"id":165,"question_zh":166,"answer_zh":167,"source_url":168},29873,"无法添加股票数据是否与 FINNHUB_API_KEY 或其他 API Key 有关？","股票数据获取失败可能与多个因素有关：\n1. 检查是否正确配置了 `FINNHUB_API_KEY`、`OPENROUTER_API_KEY` 等环境变量。\n2. 确认 API Key 是否有足够额度或未过期。\n3. 部分数据源（如 Yahoo Finance）可能存在区域限制，可尝试切换至 AKShare 等其他适配器。\n4. 参考最新配置指南调整模型和数据源设置，确保各组件兼容。若问题持续，建议提供完整错误日志以便进一步排查。","https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fissues\u002F216",[170,175,180,185,190,195,200,205,210,215,220,225,230,235,240,245,250,255,260,265],{"id":171,"version":172,"summary_zh":173,"released_at":174},206454,"v0.1.20","## 变更内容\n* chore：更新前端依赖，并按一致性重新排序 Tailwind CSS 类。由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F581 中完成。\n* feat(前端)：在“通用”设置中新增主题选项：浅色 \u002F 深色 \u002F 系统默认。由 @byronwang2005 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F580 中完成。\n* fix：引入 LLM 等待时间。由 @lukecold 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F577 中完成。\n* feat(i18n)：增强国际化覆盖范围。由 @byronwang2005 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F582 中完成。\n* feat(模型)：添加 Ollama 本地模型支持。由 @talkenigs 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F575 中完成。\n* docs：为提高清晰度，从 README 中移除下载链接。由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F592 中完成。\n* refactor(前端)：注释掉未使用的路由。由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F593 中完成。\n* release：v0.1.20 版本发布。由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F594 中完成。\n\n## 新贡献者\n* @talkenigs 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F575 中完成了首次贡献。\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.19...v0.1.20","2026-01-10T10:31:59",{"id":176,"version":177,"summary_zh":178,"released_at":179},206455,"v0.1.19","我们很高兴推出 0.1.19 版本，新增全面国际化支持、TradingView 集成、增强的投资组合管理功能以及完善的分析跟踪系统。  \n## 核心特性  \n🌍 **国际化 (i18n)**  \n- **多语言全面支持**：在应用中实现了完整的国际化功能，用户可选择自己偏好的语言使用 ValueCell。  \n\n📊 **TradingView 集成**  \n- **专业级图表**：集成 TradingView 插件，用于展示指数和股票数据，并提供高级图表工具。  \n- **统一数据渲染**：暂时将所有股票数据的渲染切换至 TradingView，以减少股票数据获取过程中的错误。  \n- **首页布局优化**：重新设计了首页，加入 TradingView 指数小部件，并改进了参数显示方式。  \n\n🎨 **UI\u002FUX 优化**  \n- **视觉更新**：新增品牌 Logo，并实现了带有健康检查功能的加载进度条。  \n- **界面改进**：优化了模型验证界面及 API 密钥输入区域，使配置流程更加顺畅。  \n- **自定义保存路径**：支持通过系统对话框将投资组合图片保存到自定义位置。  \n- **窗口与滚动优化**：调整了窗口最小尺寸，移除了侧边栏滚动条，并统一了投资组合和聊天界面的滚动行为。  \n- **更清晰的错误提示**：优化了 API 连接失败时的提示信息，使其更加明确且易于理解。  \n\n📈 **策略管理**  \n- **策略操作简化**：为策略提示添加了删除按钮，并实现了策略名称的自动生成。  \n- **设置公开化**：在创建策略时，决策间隔设置项现可直接查看。  \n- **模态框升级**：优化了策略模态框，改进了默认值、错误处理机制，并增加了用于导航的回调功能。  \n- **工具提示与洞察**：新增工具提示，用于解释已停止运行的策略。  \n\n💼 **投资组合功能**  \n- **无缝初始化**：投资组合现在可以基于现有持仓进行初始化，从而提升数据可靠性。  \n- **投资组合分享**：引入了新的模态框，支持投资组合分享功能。  \n- **发布功能升级**：优化了发布流程，新增虚拟交易所图标支持。  \n- **盈亏整合**：在策略摘要中加入了总盈亏及盈亏百分比信息。  \n\n📊 **分析与跟踪**  \n- **全面跟踪**：为桌面应用新增了客户端侧跟踪功能，并与后端分析系统实现联动。  \n- **用户洞察增强**：在登录和登出事件中加入了 user_id 跟踪。  \n- **客户端 ID 分析**：实现了客户端 ID 创建事件的跟踪功能。  \n\n🤖 **智能体改进**  \n- **超级智能体推理能力**：引入了更先进的推理能力，以实现更智能的决策制定。  \n- **预加载优化**：改进了 preload_local_agent_classes 函数，增加了按名称过滤、优化了执行时机并引入了缓存机制。  \n- **Windows 兼容性**：新增超时处理逻辑，防止在本地…","2025-12-15T11:06:22",{"id":181,"version":182,"summary_zh":183,"released_at":184},206456,"v0.1.18","## 变更内容\n* 样式：调整窗口最小尺寸，并移除侧边栏中的滚动条，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F555 中完成\n* 功能：通过系统对话框启用投资组合图片的自定义保存路径，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F554 中完成\n* 功能（UI）：实现进度条和带有健康检查的新Logo，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F556 中完成\n* 发布：添加 0.1.18 标签，由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F560 中完成\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.17...v0.1.18","2025-12-09T10:55:50",{"id":186,"version":187,"summary_zh":188,"released_at":189},206457,"v0.1.17","## 变更内容\n* 功能：新增策略提示的删除按钮，由 @PotatoZhou 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F542 中实现。\n* 功能：使用现有持仓初始化投资组合，并提升数据获取的可靠性，由 @lukecold 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F463 中实现。\n* 修复（API）：为对话、自选列表和策略的 API 端点 URL 添加尾部斜杠，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F547 中完成。\n* 重构（滚动）：统一滚动样式并清理投资组合\u002F聊天界面，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F548 中完成。\n* 修复：调整 `DialogFooter` 的外边距，并为虚拟交易所修正 `exchange_id` 的赋值，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F550 中完成。\n* 修复（策略）：在虚拟交易模式下，为非预期的 `exchange_id` 添加警告提示，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F549 中实现。\n* 杂项（图标）：替换侧边栏中的市场图标，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F551 中完成。\n* 发布：发布 v0.1.17 版本，由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F552 中完成。\n\n## 新贡献者\n* @PotatoZhou 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F542 中完成了首次贡献。\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.16...v0.1.17","2025-12-08T11:21:15",{"id":191,"version":192,"summary_zh":193,"released_at":194},206458,"v0.1.16","## 变更内容\n* 功能（策略）：在策略创建模态框中添加错误处理，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F529 中实现\n* 杂项：移除未使用的代码，由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F528 中实现\n* 修复（策略）：处理投资组合摘要计算中的除零错误，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F530 中实现\n* 功能（分析）：在创建时实现客户端 ID 分析事件跟踪，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F535 中实现\n* 功能：标准化交易所 API 凭证的占位符文本，由 @MXD66 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F536 中实现\n* 功能（投资组合）：增强发布功能并添加虚拟交易所图标，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F537 中实现\n* 功能（策略）：为 CopyStrategyModal 添加回调功能以支持导航，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F538 中实现\n* 修复（代理）：为本地代理类解析添加超时处理，以防止 Windows 系统上的死锁，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F533 中实现\n* 优化：调整代理类预加载时机及缓存机制，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F540 中实现\n* 修复（模态框）：调整 CreateStrategyModal 和 CopyStrategyModal 中的 DialogFooter 对齐方式，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F539 中实现\n* 杂项：将版本号升级至 v0.1.16，由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F541 中实现\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.15...v0.1.16","2025-12-05T11:06:34",{"id":196,"version":197,"summary_zh":198,"released_at":199},206459,"v0.1.15","## 变更内容\n* 功能（策略）：优化策略模态框的默认配置和文案处理，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F521 中完成\n* 杂项：将版本号升级至 v0.1.15，由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F524 中完成\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.14...v0.1.15","2025-12-04T10:41:46",{"id":201,"version":202,"summary_zh":203,"released_at":204},206460,"v0.1.14","## 变更内容\n* feat: 由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F513 中添加策略详情的额外字段\n* chore: 由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F512 中将表格标题从“交易组合”更新为“模型”，以提高清晰度\n* fix: 由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F507 中创建策略响应\n* fix: 由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F515 中修复创建策略代理的问题\n* chore: 由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F518 中将版本号升级至 v0.1.14\n\n\n**完整变更日志**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.13...v0.1.14","2025-12-04T09:20:11",{"id":206,"version":207,"summary_zh":208,"released_at":209},206461,"v0.1.13","## 变更内容\n* 功能（跟踪）：通过在登录和登出事件中包含 user_id，增强用户跟踪功能，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F504 中实现。\n* 杂项：在 Research 代理中启用 search_crypto 功能，由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F508 中完成。\n* 杂项：将版本号升级至 v0.1.13，由 @su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F509 中完成。\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.12...v0.1.13","2025-12-03T10:41:41",{"id":211,"version":212,"summary_zh":213,"released_at":214},206462,"v0.1.12","## 变更内容\n* 修复(后端)：为本地开发环境禁用控制线程，由 vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F494 中完成\n* 杂项：将 edgartools 更新至 4.34.0 版本，由 vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F496 中完成\n* 重构(策略)：更新策略属性以使用 Strategy 类型，并增强投资组合共享功能，由 DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F492 中完成\n* 重构(排名)：在 RankBoard 组件中将“Return”重命名为“P&L”，并简化策略详情的展示，由 DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F498 中完成\n* 杂项(首页)：注释掉 HomeLayout 和 Home 文件中未使用的组件及 API 调用，由 DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F500 中完成\n* 新特性：在策略创建中公开决策间隔，由 byronwang2005 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F499 中完成\n* 新特性(跟踪)：为桌面应用添加客户端侧跟踪及后端分析集成，由 DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F501 中完成\n* 杂项：版本号升级至 v0.1.12，由 su8su 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F503 中完成\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.11...v0.1.12","2025-12-02T09:24:33",{"id":216,"version":217,"summary_zh":218,"released_at":219},206463,"v0.1.11","## 变更内容\n* 功能（策略）：添加已停止策略的提示信息及原因，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F478 中实现\n* 功能（策略）：在策略摘要中集成总盈亏和百分比数据，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F481 中实现\n* 修复（Tauri）：通过深度链接实现登录时自动聚焦，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F485 中实现\n* 功能（策略）：根据配置状态对 AI 模型进行排序，由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F486 中实现\n* 修复（排名）：将默认天数更新为 7 天，并调整 RankBoard 组件中的标签，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F487 中实现\n* 功能：新增 SharePortfolioModal 组件，用于投资组合分享功能，由 @DigHuang 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F483 中实现\n* 功能：引入超级代理推理机制，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F477 中实现\n* 修复（交易所）：为 Hyperliquid 增加参数，用于交易所连接测试，由 @hazeone 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F488 中实现\n* 修复（策略）：在投资组合摘要中正确计算总盈亏百分比，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F489 中实现\n* 杂项：版本号升级至 v0.1.11，由 @vcfgv 在 https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F490 中完成\n\n\n**完整变更日志**：https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.10...v0.1.11","2025-12-01T10:53:23",{"id":221,"version":222,"summary_zh":223,"released_at":224},206464,"v0.1.10","Version 0.1.10 is a hotfix release that resolves the virtual trading bug.\r\n\r\n## What's Changed\r\n* fix(trading): paper trading factory init error by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F480\r\n* release: hot fix release  v0.1.10 by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F482\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.9...v0.1.10","2025-12-01T06:36:17",{"id":226,"version":227,"summary_zh":228,"released_at":229},206465,"v0.1.9","## What's Changed\r\n* fix: fix initial_capital in live mode by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F474\r\n* release: 0.1.9 version by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F475\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.8...v0.1.9","2025-11-30T12:33:48",{"id":231,"version":232,"summary_zh":233,"released_at":234},206466,"v0.1.8","We're excited to release version 0.1.8, introducing enhanced exchange management tools and a more streamlined strategy creation workflow.\r\n\r\n\r\n## What's Changed\r\n* fix: fix invalid strategy report by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F468\r\n* feat(strategy): support auto generate strategy name by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F471\r\n* feat: add exchange test connection by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F472\r\n* release: 0.1.8 version by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F473\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.7...v0.1.8","2025-11-30T09:34:30",{"id":236,"version":237,"summary_zh":238,"released_at":239},206467,"v0.1.7","We're excited to release version 0.1.7, featuring significant performance improvements, new strategy ranking features, and expanded Chinese market data support.\r\n\r\n**Key Features**\r\n\r\n**🚀 Performance Optimization**  \r\n- **Parallel Data Fetching**: Market data and candles for each symbol\u002Fgranularity are now fetched simultaneously, drastically cutting down data retrieval time.  \r\n- **LLM Agent Pre-initialization**: The LLM agent is pre-initialized during build time with the system prompt, removing redundant setup costs in every decision cycle.  \r\n\r\n**🏆 Ranking & Leaderboard**  \r\n- **Leaderboard View**: New UI to showcase strategy rankings.  \r\n- **Publishing Flow**: Users can now publish their strategies directly to the leaderboard.  \r\n- **Strategy Details API**: Added API endpoint to access detailed strategy information.  \r\n\r\n**🔐 User Authentication Enhancements**  \r\n- **Deep Link Login**: Integrated support for deep link login in the Tauri desktop app.  \r\n- **Google OAuth**: Enabled Google OAuth for a smoother authentication experience.  \r\n- **Token Management**: Improved authentication token handling with persistent state storage.  \r\n\r\n**📈 Chinese Market Data Support**  \r\n- **BaoStock Adapter**: Seamless integration with BaoStock for Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) data.  \r\n  - Free and reliable data source for the Chinese A-share market.  \r\n  - Supports both stock and index data.  \r\n  - *Note*: Real-time price data is unavailable due to BaoStock limitations.  \r\n- **Default Ticker Update**: Enhanced default ticker for China mainland users to improve the out-of-box experience.  \r\n\r\n**🎨 UI\u002FUX Improvements**  \r\n- **Tool Call Display**: Super agent and planner procedures are now shown as tool calls for better transparency.  \r\n- **Task Status Updates**: Introduced a 'pending' state for task status to provide clearer progress tracking.  \r\n\r\n**🔧 Infrastructure & Reliability**  \r\n- **UV Index URL Logic**: Smart URL logic implemented for UV sync to enhance package installation across regions.  \r\n- **Python Compatibility**: Adjusted validation exception message formatting for Python versions below 3.12.  \r\n\r\n**🛠️ Bug Fixes**  \r\n- Resolved the `return_rate_pct` calculation issue.  \r\n- Fixed logout API call to send a null payload correctly.  \r\n- Updated task status renderer to properly handle the 'pending' state.  \r\n\r\n**📚 Documentation**  \r\n- Added a YouTube video tutorial to the documentation for better user guidance.\r\n\r\n## What's Changed\r\n* feat: Parallelize Data Fetching and Pre-initialize LLM Agent to Reduce Decision Latency by @lukecold in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F438\r\n* feat(user): Implements user authentication system with deep link login support for Tauri desktop app by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F455\r\n* feat: add get strategy details api by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F452\r\n* fix: refactor validation exception message formatting for Python under 3.12 by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F454\r\n* fix(renderer): update task status handling to include 'pending' state by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F456\r\n* feat(rank): add ranking leaderboard view and publishing flow by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F458\r\n* fix(api): update logout API call to send null payload by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F459\r\n* fix: fix return_rate_pct by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F460\r\n* refactor: display super agent and planner procedures as tool call by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F461\r\n* feat(adapter):  implement BaoStockAdapter for SSE & SZSE by @PatrickStar125 in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F420\r\n* opt: change default ticker for China mainland user by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F464\r\n* feat(backend): implement index URL decision logic for uv sync by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F465\r\n* doc: upload Youtube video by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F466\r\n* release 0.1.7 by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F467\r\n\r\n## New Contributors\r\n* @PatrickStar125 made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F420\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.6...v0.1.7","2025-11-29T09:32:10",{"id":241,"version":242,"summary_zh":243,"released_at":244},206468,"v0.1.6","We're excited to release version 0.1.6, featuring improved authentication, enhanced provider support, and refined UI\u002FUX.\r\nKey Features  \r\n\r\n🤖 **Advanced Provider Support**  \r\n- **DashScope Provider**: Full support for Alibaba Cloud Bailian's Qwen3 models.  \r\n- **Supported Models**: Qwen3 Max, Qwen3 Max Preview, Qwen Plus, Qwen Flash.  \r\n- **Embedding Features**: Supports Text Embedding V4 and V3 models.  \r\n- **Configuration**: OpenAI-compatible base URL with API key authentication for streamlined integration.  \r\n\r\n🎨 **UI\u002FUX Enhancements**  \r\n- **Updated Icons**: Refreshed application icon assets for visual consistency.  \r\n- **Window Size Adjustment**: Default window size increased from 1280x720 to 1400x900 for better usability.  \r\n- **Settings UI Overhaul**: Refactored general settings UI with new Field components for improved navigation.  \r\n- **Component Refinement**: Enhanced icon and sidebar component structure for easier maintainability.  \r\n- **URL Handling**: Improved Tauri URL opening logic for smoother operations.  \r\n\r\n🔧 **Infrastructure & Reliability**  \r\n- **Graceful Shutdown**: Backend processes now support graceful shutdown using stdin (SIGINT signal).  \r\n- **Process Stability**: Refactored descendant process termination logic for enhanced reliability.  \r\n- **Auto-Update**: Integrated Tauri auto-update functionality for seamless version upgrades.  \r\n- **Windows Build Workflow**: Optimized Windows build support via GitHub Actions.  \r\n\r\n🔐 **User Authentication & Session Management**  \r\n- **Deep Link Login Support**: Integrated deep link login modal with Tauri deep link functionality for seamless authentication.  \r\n- **Enhanced Login Modal**: Improved timeout handling and cleanup for a smoother login experience.  \r\n- **Sign Out Capability**: Added sign-out functionality in the settings page.  \r\n- **Auth Token Security**: Refactored auth token handling and system info types to enhance security.  \r\n- **Persistent State Management**: Implemented Tauri store integration for reliable system state management.  \r\n- **User Info Optimization**: Enhanced user info retrieval and Tauri store initialization for improved performance.  \r\n\r\n🛠️ **Bug Fixes & Refinements**  \r\n- **Provider Error Handling**: Resolved DashScope provider-specific errors.  \r\n- **App Info Hook**: Refactored Tauri app info retrieval into a custom hook.  \r\n- **Model Validation**: Added validator for TradeDecisionItem instruments.  \r\n- **Deep Link Enhancements**: Improved deep link functionality for a better login experience.  \r\n\r\n\r\n## What's Changed\r\n* chore: Increase default window size in Tauri config by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F446\r\n* feat: Add DashScope provider support for Qwen3 models by @byronwang2005 in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F441\r\n* chore(icon): update application icon assets by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F447\r\n* fix(windows): win app kill process error by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F448\r\n* feat: implement graceful shutdown for backend processes via stdin by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F449\r\n* fix(model): DashScope provider error by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F451\r\n* release: update version to 0.1.6 by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F453\r\n\r\n## New Contributors\r\n* @byronwang2005 made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F441\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.5...v0.1.6","2025-11-27T10:14:57",{"id":246,"version":247,"summary_zh":248,"released_at":249},206469,"v0.1.5","We're pleased to release version 0.1.5 focusing on stability improvements, bug fixes, and enhanced documentation for our users.\r\n\r\n## What's Changed\r\n* fix: refactor cycle index handling and initialize from persisted snapshot and close_all_positions market_snapshots by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F443\r\n* fix: prevent redundant fee deduction from account balance by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F442\r\n* feat:  update db file path by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F432\r\n* feature: resume scheduled task automatically by @vcfgv in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F433\r\n* fix(tauri): improve Tauri URL opening by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F445\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.4...v0.1.5","2025-11-26T09:39:14",{"id":251,"version":252,"summary_zh":253,"released_at":254},206470,"v0.1.4","We're pleased to release version 0.1.4, focusing on stability improvements, bug fixes, and enhanced documentation for our users.\r\n## What's Changed\r\n* fix: super agent update config by @su8su in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F435\r\n* docs(readme): add instructions for regular users by @hazeone in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F436\r\n* chore: bump app version to 0.1.4 in Tauri config by @DigHuang in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F437\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.3...v0.1.4","2025-11-25T12:10:40",{"id":256,"version":257,"summary_zh":258,"released_at":259},206471,"v0.1.3","We're thrilled to announce version 0.1.3, packed with Tauri auto-update capabilities, enhanced strategy features, and improved CI\u002FCD workflows. Another exciting update: The Win APP beta version is now live with this release! 🔥🔥🔥\r\n\r\n## Key Features  \r\n\r\n🚀 **Tauri Auto Update Support**  \r\n- **Auto Update**: Introduced Tauri auto-update functionality for seamless application updates (#417).  \r\n- **App Info Hook**: Refactored Tauri app info retrieval into a custom hook for improved maintainability (#428).  \r\n- **Graceful Process Termination**: Enhanced descendant process termination logic with SIGINT for smoother handling (#426).  \r\n\r\n📈 **Strategy Agent Enhancements**  \r\n- **Strategy Status Updates**: Upgraded strategy agent to include stop reasons and detailed status updates (#427).  \r\n- **Graceful Exit & Auto-Resume**: Optimized strategy agent for graceful exit and auto-resume functionality (#421).  \r\n- **Grid Strategy Refinement**: Improved grid strategy implementation for enhanced performance (#425).  \r\n- **GridStrategy Symbols**: Updated strategy form to support GridStrategy symbols (#430).  \r\n\r\n⚡ **Performance & Optimization**  \r\n- **Prompt Composer Validation**: Enhanced validation for prompt-based composer output schemas (#423).  \r\n- **Strategy API Refetch**: Reduced strategy API refetch interval to 5 seconds for quicker updates (#431).  \r\n\r\n**Bug Fixes**  \r\n- **DeepSeek Provider**: Resolved configuration issues with the DeepSeek provider (#418).  \r\n- **Trade Decision Validation**: Added model validation for instruments in TradeDecisionItem (#424).  \r\n- **Database Initialization**: Implemented a smart sys.path fallback for the init_db entry point (#344).  \r\n\r\n**CI\u002FCD & Build Improvements**  \r\n- **Windows Build Workflow**: Introduced Windows build workflow via GitHub Actions (#415).  \r\n- **Tag-Based Releases**: Enhanced build workflows to support tag-based releases (#434).  \r\n- **Workflow Dispatch**: Enabled workflow triggering via dispatch (#419).  \r\n\r\n**Documentation**  \r\n- **README Updates**: Refreshed and updated project README documentation (#414).  \r\n\r\n**Contributors**  \r\nA huge thanks to all contributors who made this release possible:  \r\n@DigHuang , @vcfgv,  @hazeone , @MXD66 , @su8su , @Wee7   \r\n\r\n🚀 We've also launched our developer program! Check out the Contributing section for details on how to get involved.\r\n\r\n\r\n## New Contributors\r\n* @Wee7 made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F344\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.2...v0.1.3","2025-11-25T09:33:46",{"id":261,"version":262,"summary_zh":263,"released_at":264},206472,"v0.1.2","Version 0.1.2 is here, bringing major enhancements to trading functionalities, configuration options, and overall platform stability. In this release, we are launching the beta version of the ValueCell APP, currently available for MacOS only. We welcome your feedback—feel free to share your thoughts in Discord or report issues directly.\r\n\r\nKey Features:\r\n\r\n**Strategy Agent (New!)**\r\n- **Grid Strategy Agent**: Enables automated market-making with grid trading strategies.\r\n- **Prompt-Based Strategy Agent**: Design custom trading strategies using AI-driven prompts.\r\n- **Strategy Management**: Full lifecycle support for creating, monitoring, deleting, and canceling strategies.\r\n- **Strategy Prompts Library**: Access reusable templates for rapid strategy deployment.\r\n- **Enhanced Trading Context**: Includes Funding Rate, Open Interest, and Sharpe Ratio metrics.\r\n- **Portfolio Summary**: Provides structured trade history, position snapshots, and P&L tracking.\r\n\r\n**Multi-Exchange Support**\r\n- **OKX, Binance, Hyperliquid Integration**: Complete support for OKX exchange.\r\n- **Expanded Exchange Coverage**: Added compatibility with MEXC, Coinbase, Blockchain.com, and Gate.io.\r\n- **Live Trading Mode**: Production-ready capabilities for real exchange integration.\r\n- **Virtual Trading Mode**: A risk-free testing environment for strategy validation.\r\n\r\n**Additional LLM Providers**  \r\n- **User-Friendly Interface**: Configure your API key effortlessly through a GUI, no coding required.  \r\n- **Comprehensive Integration**: Fully compatible with Azure OpenAI, SiliconFlow, Gemini, and OpenAI services.  \r\n- **Flexible Setup**: Supports OpenAI-compatible APIs seamlessly.  \r\n\r\n**Configuration & Model Management**\r\n- **Dynamic Model Configuration UI**: Allows AI model provider setup directly from the frontend.\r\n- **System Environment File**: Centralized management of environment configurations.\r\n- **Model Interface Enhancements**: Improved model selection with provider-specific validations.\r\n- **Backend Health Checks**: Tools to monitor system health and status.\r\n\r\n**Enhanced Agent Capabilities**\r\n- **Research Agent No-Knowledge Mode**: Operate without requiring a knowledge database.\r\n- **RootData Integration**: Beta support for crypto market data from RootData.\r\n- **Discord Integration**: Seamlessly send trading plans to Discord.\r\n- **Super Agent Lazy Initialization**: Optimized startup with on-demand agent loading.\r\n\r\n**Platform & Developer Experience**\r\n- **macOS Application Bundle**: Native macOS app support with Tauri.\r\n- **Cross-Platform Enhancements**: Improved launch scripts for Windows and macOS.\r\n- **Backend Process Management**: Enhanced agent lifecycle management.\r\n- **Comprehensive Python Guidelines**: Detailed Python best practices added to AGENTS.md.\r\n- **UI\u002FUX Refinements**: Includes hover cards, loading states, empty placeholders, and improved navigation.\r\n\r\n**Bug Fixes & Stability**\r\n- Resolved agent display and port conflict issues.\r\n- Improved environment variable handling and form validation.\r\n- Fixed trading execution and buy power management.\r\n- Addressed agent state synchronization problems.\r\n- Enhanced scrollbar behavior and UI overflow handling.\r\n\r\n## New Contributors\r\n* @SanGuiChen made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F294\r\n* @yah01 made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F296\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.1...v0.1.2","2025-11-21T11:09:45",{"id":266,"version":267,"summary_zh":268,"released_at":269},206473,"v0.1.1","We’re excited to release version 0.1.1, introducing new capabilities that improve agent interactions and enable advanced use cases.\r\n\r\n## Key Features\r\n\r\n**Multi-Provider Model Support**\r\n- Siliconflow Provider: Added support for Siliconflow model provider\r\n- Google Gemini Provider: Integrated Google Gemini for enhanced AI capabilities\r\n- OpenAI Provider: Direct OpenAI API integration for flexible model selection\r\n- OpenAI-Compatible Providers: Support for any OpenAI-compatible API providers\r\n\r\n**Enhanced Agent Capabilities**\r\n- **Research Agent** A-Share Support: Expanded research capabilities to support Chinese A-Share market analysis\r\n- **News Agent**: Introduced dedicated news agent for real-time news monitoring and analysis\r\n- **AutoTradingAgent** Multi-Provider Support: Enhanced trading agent to work with diverse model providers\r\n- Schedule recurring task to invoke agents periodically\r\n\r\n**Developer Experience & Documentation**\r\n- Configuration Guide: Comprehensive guide for model configuration\r\n- Developer's Guide: Detailed documentation for developers\r\n- Agent Development Guide: Step-by-step guide for contributing new agents\r\n\r\n## New Contributors\r\n* @chihtengma made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F182\r\n* @MXD66 made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F176\r\n* @lukecold made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F185\r\n* @eltociear made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F205\r\n* @Mirza-Samad-Ahmed-Baig made their first contribution in https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fpull\u002F226\r\n\r\n🚀 We’ve launched our developer program. Refer to [Contributing](https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fblob\u002Fmain\u002F.github\u002FCONTRIBUTING.md) for participation details..\r\n\r\n---\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002FValueCell-ai\u002Fvaluecell\u002Fcompare\u002Fv0.1.0...v0.1.1","2025-10-31T09:02:37"]