Name: fastapi-to-langgraph
Author: yuxiu1212

Imported from yuxiu1212/To-langGraph-converter (.claude/skills/fastapi-to-langgraph/SKILL.md). Install upstream with npx skills add yuxiu1212/To-langGraph-converter --skill fastapi-to-langgraph. Copyright stays with the author.

FastAPI（情境路由）→ LangGraph

把「意圖分類 + if/elif 多情境分派」的 FastAPI 專案，轉換為 LangGraph StateGraph 架構。轉換本質：把函式呼叫關係，改寫成圖的節點與邊——分類函式→router 節點、if/elif→條件邊、各情境處理函式→各自的節點。

核心原則

對外介面維持不變：路徑、Request/Response（Pydantic）格式一致，呼叫端無感。
業務邏輯原封不動：LLM 分類邏輯、各 handler（含 TODO 佔位）整段搬移，只改輸入輸出形狀（讀寫 state）。
局部更新原則：每個節點只回傳自己變更的欄位。
驗證不能省略：每個情境各一筆輸入實際跑過 compiled_graph.invoke()。

參考資料

節點對照表 — FastAPI → LangGraph 概念映射
轉換步驟 — state → router → 各節點 → graph → main
新增情境 — 五步驟擴充指南
範例專案 — before/＝原 FastAPI（MultiContextChatbot/）、after/＝轉換後（MultiContextChatbot_langgraph/）

💡 觸發命令範例

"請幫我將這個 FastAPI 專案，轉換成 LangGraph Python 架構。"

自動載入此 Skill，依對照表逐步完成轉換並驗證。

# after Install: the listing is in your workspace's routing pool - a plan picks it for its slot curl -s -X POST https://api.opensmartroute.ai/api/v1/route -H 'Authorization: Bearer $OSR_API_KEY' -H 'Content-Type: application/json' -d '{"text": "...", "plan": true}'

Install fastapi-to-langgraph and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

{ "ocm": "1", "id": "yuxiu1212-to-langgraph-converter-fastapi-to-langgraph", "kind": "skill", "name": "fastapi-to-langgraph", "description": "將「意圖分類 + if/elif 分派情境處理」的 FastAPI 應用程式，一步轉換為 LangGraph（StateGraph）架構。當使用者要求把 FastAPI 專案改成 LangGraph、加情境節點、用 graph 架構重構時，主動使用本技能。", "publisher": "yuxiu1212", "version": "1.0.0", "capabilities": { "domains": [ "general" ], "tags": [ "skill-md", "github" ], "languages": [ "en" ] }, "quality_prior": 0.6, "examples": [ "將「意圖分類 + if/elif 分派情境處理」的 FastAPI 應用程式，一步轉換為 LangGraph（StateGraph）架構。當使用者要求把 FastAPI 專案改成 LangGraph、加情境節點、用 graph 架構重構時，主動使用本技能。" ], "primary": false, "metadata": { "source": { "provider": "github", "repository": "https://github.com/yuxiu1212/To-langGraph-converter", "path": ".claude/skills/fastapi-to-langgraph/SKILL.md", "ref": "9b8966b8efcf20ea4f9005d84adb79da665f9d55", "url": "https://github.com/yuxiu1212/To-langGraph-converter/blob/9b8966b8efcf20ea4f9005d84adb79da665f9d55/.claude/skills/fastapi-to-langgraph/SKILL.md", "key": "yuxiu1212/To-langGraph-converter/.claude/skills/fastapi-to-langgraph/SKILL.md" } }, "instructions": "# FastAPI（情境路由）→ LangGraph\n\n把「意圖分類 + if/elif 多情境分派」的 FastAPI 專案，轉換為 LangGraph StateGraph 架構。\n轉換本質：**把函式呼叫關係，改寫成圖的節點與邊**——分類函式→router 節點、if/elif→條件邊、各情境處理函式→各自的節點。\n\n## 核心原則\n\n- **對外介面維持不變**：路徑、Request/Response（Pydantic）格式一致，呼叫端無感。\n- **業務邏輯原封不動**：LLM 分類邏輯、各 handler（含 TODO 佔位）整段搬移，只改輸入輸出形狀（讀寫 state）。\n- **局部更新原則**：每個節點只回傳自己變更的欄位。\n- **驗證不能省略**：每個情境各一筆輸入實際跑過 `compiled_graph.invoke()`。\n\n## 參考資料\n\n- **[節點對照表](./references/mapping_rules.md)** — FastAPI → LangGraph 概念映射\n- **[轉換步驟](./references/conversion_steps.md)** — state → router → 各節點 → graph → main\n- **[新增情境](./references/add_scenario.md)** — 五步驟擴充指南", "cost": { "context_tokens": 198 } }

fastapi-to-langgraph

About

FastAPI（情境路由）→ LangGraph

核心原則

參考資料

💡 觸發命令範例

Use it

Install fastapi-to-langgraph and it becomes one more candidate the router can pick - when it fits.

Manifest

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