[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74771":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":8,"language":10,"languages":8,"totalLinesOfCode":8,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":8,"rankLanguage":8,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":8,"pushedAt":8,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":15,"starSnapshotCount":15,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},74771,"feynman","companion-inc\u002Ffeynman","companion-inc",null,"https:\u002F\u002Ffeynman.is","TypeScript",7795,940,33,7,0,50,180,758,150,39.92,"MIT License",false,"main",true,[],"2026-06-12 02:03:27","\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Ffeynman.is\">\n    \u003Cimg src=\"assets\u002Fhero.png\" alt=\"Feynman CLI\" width=\"800\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\u003Cp align=\"center\">The open source AI research agent.\u003C\u002Fp>\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Ffeynman.is\u002Fdocs\">\u003Cimg alt=\"Docs\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fdocs-feynman.is-0d9668?style=flat-square\" \u002F>\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fcompanion-inc\u002Ffeynman\u002Fblob\u002Fmain\u002FLICENSE\">\u003Cimg alt=\"License\" src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fcompanion-inc\u002Ffeynman?style=flat-square\" \u002F>\u003C\u002Fa>\n\u003C\u002Fp>\n\n---\n\n### Installation\n\n**macOS \u002F Linux:**\n\n```bash\ncurl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall | bash\n```\n\n**Windows (PowerShell):**\n\n```powershell\nirm https:\u002F\u002Ffeynman.is\u002Finstall.ps1 | iex\n```\n\nThe one-line installer fetches the latest tagged release. To pin a version, pass it explicitly, for example `curl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall | bash -s -- 0.2.35`.\n\nThe installer downloads a standalone native bundle with its own Node.js runtime.\n\nTo upgrade the standalone app later, rerun the installer. `feynman update` only refreshes installed Pi packages inside Feynman's environment; it does not replace the standalone runtime bundle itself.\n\nTo uninstall the standalone app, remove the launcher and runtime bundle, then optionally remove `~\u002F.feynman` if you also want to delete settings, sessions, and installed package state. If you also want to delete alphaXiv login state, remove `~\u002F.ahub`. See the installation guide for platform-specific paths.\n\nLocal models are supported through the setup flow. For LM Studio, run `feynman setup`, choose `LM Studio`, and keep the default `http:\u002F\u002Flocalhost:1234\u002Fv1` unless you changed the server port. For LiteLLM, choose `LiteLLM Proxy` and keep the default `http:\u002F\u002Flocalhost:4000\u002Fv1`. For Ollama or vLLM, choose `Custom provider (baseUrl + API key)`, use `openai-completions`, and point it at the local `\u002Fv1` endpoint.\n\n### Skills Only\n\nIf you want just the research skills without the full terminal app:\n\n**macOS \u002F Linux:**\n\n```bash\ncurl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall-skills | bash\n```\n\n**Windows (PowerShell):**\n\n```powershell\nirm https:\u002F\u002Ffeynman.is\u002Finstall-skills.ps1 | iex\n```\n\nThat installs the skill library into `~\u002F.codex\u002Fskills\u002Ffeynman` for Codex. You can also name the Codex target explicitly:\n\n**macOS \u002F Linux:**\n\n```bash\ncurl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall-skills | bash -s -- --codex\n```\n\n**Windows (PowerShell):**\n\n```powershell\n& ([scriptblock]::Create((irm https:\u002F\u002Ffeynman.is\u002Finstall-skills.ps1))) -Scope Codex\n```\n\nFor a repo-local Claude\u002Fagent install instead:\n\n**macOS \u002F Linux:**\n\n```bash\ncurl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall-skills | bash -s -- --repo\n```\n\n**Windows (PowerShell):**\n\n```powershell\n& ([scriptblock]::Create((irm https:\u002F\u002Ffeynman.is\u002Finstall-skills.ps1))) -Scope Repo\n```\n\nThat installs into `.agents\u002Fskills\u002Ffeynman` under the current repository.\n\nFor an OpenCode project-local install instead:\n\n**macOS \u002F Linux:**\n\n```bash\ncurl -fsSL https:\u002F\u002Ffeynman.is\u002Finstall-skills | bash -s -- --opencode\n```\n\n**Windows (PowerShell):**\n\n```powershell\n& ([scriptblock]::Create((irm https:\u002F\u002Ffeynman.is\u002Finstall-skills.ps1))) -Scope OpenCode\n```\n\nThat installs into `.opencode\u002Fskills\u002Ffeynman` under the current repository.\n\nThese installers download the bundled `skills\u002F` and `prompts\u002F` trees plus the repo guidance files referenced by those skills. They do not install the Feynman terminal, bundled Node runtime, auth storage, or Pi packages.\n\n---\n\n### What you type → what happens\n\n```\n$ feynman \"what do we know about scaling laws\"\n→ Searches papers and web, produces a cited research brief\n\n$ feynman deepresearch \"mechanistic interpretability\"\n→ Multi-agent investigation with parallel researchers, synthesis, verification\n\n$ feynman lit \"RLHF alternatives\"\n→ Literature review with consensus, disagreements, open questions\n\n$ feynman audit 2401.12345\n→ Compares paper claims against the public codebase\n\n$ feynman replicate \"chain-of-thought improves math\"\n→ Replicates experiments on local or cloud GPUs\n\n$ feynman recipe \"fine-tune a small model for math reasoning\"\n→ Finds ranked, implementable ML training recipes from papers, datasets, docs, and code\n```\n\n---\n\n### Workflows\n\nAsk naturally or use slash commands as shortcuts.\n\n| Command | What it does |\n| --- | --- |\n| `\u002Fdeepresearch \u003Ctopic>` | Source-heavy multi-agent investigation |\n| `\u002Flit \u003Ctopic>` | Literature review from paper search and primary sources |\n| `\u002Freview \u003Cartifact>` | Simulated peer review with severity and revision plan |\n| `\u002Faudit \u003Citem>` | Paper vs. codebase mismatch audit |\n| `\u002Freplicate \u003Cpaper>` | Replicate experiments on local or cloud GPUs |\n| `\u002Frecipe \u003Ctask-or-paper>` | Ranked ML training recipes with dataset, method, code, and verification status |\n| `\u002Fcompare \u003Ctopic>` | Source comparison matrix |\n| `\u002Fdraft \u003Ctopic>` | Paper-style draft from research findings |\n| `\u002Fautoresearch \u003Cidea>` | Autonomous experiment loop |\n| `\u002Fwatch \u003Ctopic>` | Recurring research watch |\n| `\u002Foutputs` | Browse all research artifacts |\n\n---\n\n### Agents\n\nFour bundled research agents, dispatched automatically.\n\n- **Researcher** — gather evidence across papers, web, repos, docs\n- **Reviewer** — simulated peer review with severity-graded feedback\n- **Writer** — structured drafts from research notes\n- **Verifier** — inline citations, source URL verification, dead link cleanup\n\n---\n\n### Skills & Tools\n\n- **[AlphaXiv](https:\u002F\u002Fwww.alphaxiv.org\u002F)** — paper search, Q&A, code reading, annotations (via `alpha` CLI)\n- **[Hugging Face Hub](https:\u002F\u002Fhuggingface.co\u002Fdocs\u002Fhub\u002Fapi)** — dataset metadata, split\u002Fschema inspection, and small file reads from model, dataset, and Space repos\n- **Docker** — isolated container execution for safe experiments on your machine\n- **Web search** — Exa, Perplexity, or Gemini API; no Chromium cookie access by default\n- **Session search** — indexed recall across prior research sessions\n- **Preview** — browser and PDF export of generated artifacts\n- **Modal** — serverless GPU compute for burst training and inference\n- **RunPod** — persistent GPU pods with SSH access for long-running experiments\n\n---\n\n### How it works\n\nBuilt on [Pi](https:\u002F\u002Fgithub.com\u002Fbadlogic\u002Fpi-mono) for the agent runtime, [alphaXiv](https:\u002F\u002Fwww.alphaxiv.org\u002F) for paper search and analysis, and CLI tools for compute and execution. Runtime resources follow Pi's documented package model for [packages](https:\u002F\u002Fgithub.com\u002Fbadlogic\u002Fpi-mono\u002Fblob\u002Fmain\u002Fpackages\u002Fcoding-agent\u002Fdocs\u002Fpackages.md), [extensions](https:\u002F\u002Fgithub.com\u002Fbadlogic\u002Fpi-mono\u002Fblob\u002Fmain\u002Fpackages\u002Fcoding-agent\u002Fdocs\u002Fextensions.md), and [skills](https:\u002F\u002Fgithub.com\u002Fbadlogic\u002Fpi-mono\u002Fblob\u002Fmain\u002Fpackages\u002Fcoding-agent\u002Fdocs\u002Fskills.md). Hugging Face inspection uses the public [Hub API endpoints](https:\u002F\u002Fhuggingface.co\u002Fdocs\u002Fhub\u002Fapi) and `HF_TOKEN` \u002F `HUGGINGFACE_HUB_TOKEN` environment variables documented by [`huggingface_hub`](https:\u002F\u002Fhuggingface.co\u002Fdocs\u002Fhuggingface_hub\u002Fmain\u002Fen\u002Fpackage_reference\u002Fenvironment_variables). The ML recipe workflow was informed by the open-source [Hugging Face `ml-intern`](https:\u002F\u002Fgithub.com\u002Fhuggingface\u002Fml-intern) research-agent repo, but is implemented as native Feynman prompts, skills, and read-only tools. Every output is source-grounded — claims link to papers, docs, or repos with direct URLs.\n\n---\n\n### Star History\n\n\u003Ca href=\"https:\u002F\u002Fwww.star-history.com\u002F?repos=companion-inc%2Ffeynman&type=date&legend=top-left\">\n  \u003Cpicture>\n    \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"https:\u002F\u002Fapi.star-history.com\u002Fchart?repos=companion-inc\u002Ffeynman&type=date&theme=dark&legend=top-left\" \u002F>\n    \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Fapi.star-history.com\u002Fchart?repos=companion-inc\u002Ffeynman&type=date&legend=top-left\" \u002F>\n    \u003Cimg alt=\"Star History Chart\" src=\"https:\u002F\u002Fapi.star-history.com\u002Fchart?repos=companion-inc\u002Ffeynman&type=date&legend=top-left\" \u002F>\n  \u003C\u002Fpicture>\n\u003C\u002Fa>\n\n---\n\n### Contributing\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) for the full contributor guide.\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fcompanion-inc\u002Ffeynman.git\ncd feynman\nnvm use || nvm install\nnpm install\nnpm test\nnpm run typecheck\nnpm run build\n```\n\n[Docs](https:\u002F\u002Ffeynman.is\u002Fdocs) · [Release Notes](RELEASES.md) · [MIT License](LICENSE)\n","Feynman 是一个开源的人工智能研究助手。它通过命令行界面提供了一套强大的研究技能，支持多种本地模型集成，如LM Studio、LiteLLM、Ollama和vLLM等，用户可以通过简单的配置将这些模型接入到Feynman中使用。此外，该项目允许单独安装其核心技能库，以便于与其他工具或项目整合，增加了灵活性。适用于需要利用AI辅助进行深度学习研究、数据分析或是自动化处理文本信息的场景。",2,"2026-06-11 03:50:45","high_star"]