u14app/deep-research

• highreadme#1

  Clarify the project's purpose and active status at the very start of the README

  原因：

  当前

  The README starts with a `div align="center"` block containing many badges and links, followed by 'Lightning-Fast Deep Research Report'.

  复制粘贴的修复

  复制

  # Deep Research: Lightning-Fast AI-Powered Research Report Generation
  
  Deep Research is an active, open-source application that leverages various powerful AI models (including Gemini, OpenAI, Anthropic, Deepseek, Grok, and more) to generate comprehensive, privacy-focused research reports rapidly. It supports multi-platform deployment and processes all data locally in your browser, ensuring your privacy is paramount.
  
  <div align="center">
  
  [](https://opensource.org/licenses/MIT)
  
  [](https://ai.google.dev/)
  [](https://nextjs.org/)
  [](https://tailwindcss.com/)
  [](https://ui.shadcn.com/)
  
  [](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Fu14app%2Fdeep-research&project-name=deep-research&repository-name=deep-research)
  [](./docs/How-to-deploy-to-Cloudflare-Pages.md)
  [](https://research.u14.app/)
  
  [](https://deepwiki.com/u14app/deep-research)
  
  </div>
  
  **Lightning-Fast Deep Research Report**
  
  Deep Research uses a variety of powerful AI models to generate in-depth research reports in just a few minutes. It leverages advanced "Thinking" and "Task" models, combined with an internet connection, to provide fast and insightful analysis on a variety of topics. **Your privacy is paramount - all data is processed and stored locally.**
  
  ## ✨ Features
  
  Rapid Deep Research:** Generates comprehensive research reports in about 2 minutes, significantly accelerating your research process.
  Multi-platform Support:** Supports rapid deployment to Vercel, Cloudflare and other platforms.
  Powered by AI:** Utilizes the advanced AI models for accurate and insightful analysis.
  Privacy-Focused:** Your data remains private and secure, as all data is stored locally on your browser.
  Support for Multi-LLM:** Supports a variety of mainstream large language models, including Gemini, OpenAI, Anthropic, Deepseek, Atlas Cloud, Grok, Mistral, Azure OpenAI, any OpenAI Compatible LLMs, Op

  待办完成忽略
• mediumabout#2

  Ensure the repository description accurately reflects its current function and active status

  原因：

  当前

  Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.

  复制粘贴的修复

  复制

  Generate comprehensive, privacy-focused deep research reports rapidly using various LLMs (Gemini, OpenAI, Anthropic, Deepseek, Grok, etc.) with local data processing. Supports SSE API and MCP server for multi-platform deployment.

  待办完成忽略
• mediumtopics#3

  Add broader, user-centric topics to improve category visibility

  原因：

  当前

  anthropic, deep-research, deep-research-api, deepresearch, deepseek, gemini, grok, mcp-server, ollama, openai

  复制粘贴的修复

  复制

  anthropic, deep-research, deep-research-api, deepresearch, deepseek, gemini, grok, mcp-server, ollama, openai, ai-research-tool, report-generation, llm-agent, privacy-focused, local-llm, research-assistant, knowledge-synthesis

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to quickly generate comprehensive research reports using various AI models?

  你：未被推荐
  AI 推荐顺序：

  1. Elicit
  2. ChatGPT
  3. Scite.ai
  4. Notion AI
  5. Perplexity AI
  6. Jasper AI
  7. Humata AI

  AI 推荐了 7 个替代方案，却始终没点名 u14app/deep-research。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What tools allow deep research using multiple LLMs with local data processing?

  你：未被推荐
  AI 推荐顺序：

  1. LlamaIndex
  2. LangChain
  3. Haystack
  4. OpenWebUI
  5. PrivateGPT
  6. Hugging Face Transformers
  7. LiteLLM

  AI 推荐了 7 个替代方案，却始终没点名 u14app/deep-research。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of u14app/deep-research?

  pass
  ⚠AI 未点名 u14app/deep-research —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts u14app/deep-research in production, what risks or prerequisites should they evaluate first?

  pass
  ⚠AI 未点名 u14app/deep-research —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo u14app/deep-research solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 u14app/deep-research

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？