openui-forge-python

Name: openui-forge-python
Author: OthmanAdi

10installs0forks

How to install openui-forge-python?

othmanadi/openui-forge/openui-forge-python

$npx -y skills add OthmanAdi/openui-forge --skill openui-forge-python

Installs into the current project.

Summary

OpenUI generative UI with Python FastAPI backend. OpenAI and Anthropic SDK variants.

Files · 1

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SKILL.md

1	# OpenUI Forge — Python
2
3	Build generative UI apps with a React frontend + Python FastAPI backend. Streams OpenAI-compatible NDJSON.
4
5	## Activation Triggers
6
7	- "openui python", "openui fastapi", "openui flask"
8	- "generative ui python", "python streaming ui backend"
9
10	## Prerequisites
11
12	- Node.js >= 22 (24 LTS recommended) + React >= 18.3.1 (19+ recommended) (frontend)
13	- Python >= 3.10 (backend)
14	- `OPENAI_API_KEY` or `ANTHROPIC_API_KEY` set
15
16	## Quick Start
17
18	1. Create the React frontend and install OpenUI deps:
19	```bash
20	npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod
21	```
22	2. Generate the system prompt from your component library:
23	```bash
24	npx @openuidev/cli generate ./src/lib/library.ts --out backend/system-prompt.txt
25	```
26	3. Set up the Python backend (see Full Code below)
27	4. Run both: frontend on `:3000`, backend on `:8000`
28
29	## Full Code
30
31	### Backend: `backend/requirements.txt`
32
33	```
34	fastapi>=0.115.0
35	uvicorn>=0.24.0
36	openai>=2.0
37	anthropic>=0.111.0
38	python-dotenv>=1.0.0
39	```
40
41	> The Python >= 3.10 floor comes from fastapi/uvicorn/python-dotenv; openai and anthropic themselves need only Python 3.9.
42
43	### Backend (OpenAI): `backend/main.py`
44
45	```python
46	import os
47	from pathlib import Path
48	from dotenv import load_dotenv
49	from fastapi import FastAPI, Request
50	from fastapi.middleware.cors import CORSMiddleware
51	from fastapi.responses import StreamingResponse
52	from openai import AsyncOpenAI
53
54	load_dotenv()
55	app = FastAPI()
56	app.add_middleware(
57	CORSMiddleware,
58	allow_origins=["http://localhost:3000"],
59	allow_methods=["POST"],
60	allow_headers=["*"],
61	)
62
63	# AsyncOpenAI keeps the request from blocking the event loop during streaming.
64	client = AsyncOpenAI()
65	SYSTEM_PROMPT = Path("system-prompt.txt").read_text()
66
67	@app.post("/api/chat")
68	async def chat(request: Request):
69	body = await request.json()
70	messages = [{"role": "system", "content": SYSTEM_PROMPT}] + body["messages"]
71
72	async def generate():
73	response = await client.chat.completions.create(
74	model=os.getenv("OPENAI_MODEL", "gpt-5.5"),
75	stream=True,
76	messages=messages,
77	)
78	async for chunk in response:
79	data = chunk.model_dump_json()
80	yield f"data: {data}\n\n"
81	yield "data: [DONE]\n\n"
82
83	return StreamingResponse(generate(), media_type="text/event-stream")
84	```
85
86	### Backend (Anthropic variant): `backend/main_anthropic.py`
87
88	```python
89	import os, json, time
90	from pathlib import Path
91	from dotenv import load_dotenv
92	from fastapi import FastAPI, Request
93	from fastapi.middleware.cors import CORSMiddleware
94	from fastapi.responses import StreamingResponse
95	from anthropic import AsyncAnthropic
96
97	load_dotenv()
98	app = FastAPI()
99	app.add_middleware(
100	CORSMiddleware,
101	allow_origins=["http://localhost:3000"],
102	allow_methods=["POST"],
103	allow_headers=["*"],
104	)
105
106	# AsyncAnthropic mirrors AsyncOpenAI so the stream does not block the loop.
107	client = AsyncAnthropic()
108	SYSTEM_PROMPT = Path("system-prompt.txt").read_text()
109
110	@app.post("/api/chat")
111	async def chat(request: Request):
112	body = await request.json()
113	stream_id = f"chatcmpl-{int(time.time())}"
114
115	async def generate():
116	async with client.messages.stream(
117	model=os.getenv("ANTHROPIC_MODEL", "claude-sonnet-4-6"),
118	max_tokens=4096,
119	system=SYSTEM_PROMPT,
120	messages=body["messages"],
121	) as stream:
122	async for text in stream.text_stream:
123	chunk = {"id": stream_id, "object": "chat.completion.chunk",
124	"choices": [{"index": 0, "delta": {"content": text}, "finish_reason": None}]}
125	yield f"data: {json.dumps(chunk)}\n\n"
126	done = {"id": stream_id, "object": "chat.completion.chunk",
127	"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]}
128	yield f"data: {json.dumps(done)}\n\n"
129	yield "data: [DONE]\n\n"
130
131	return StreamingResponse(generate(), media_type="text/event-stream")
132	```
133
134	### Frontend: `app/chat/page.tsx` (or `src/Chat.tsx` for Vite)
135
136	```tsx
137	"use client";
138	import { FullScreen } from "@openuidev/react-ui";
139	import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
140	import {
141	openAIAdapter,
142	openAIMessageFormat,
143	} from "@openuidev/react-headless";
144
145	export default function ChatPage() {
146	return (
147	<FullScreen
148	componentLibrary={openuiChatLibrary}
149	streamProtocol={openAIAdapter()}
150	messageFormat={openAIMessageFormat}
151	apiUrl="http://localhost:8000/api/chat"
152	/>
153	);
154	}
155	```
156
157	> The Python backend emits SSE (`data: {json}\n\n`). Pair it with `openAIAdapter()` on the frontend. `openAIReadableStreamAdapter()` is for NDJSON (no `data:` prefix) and will silently produce no output here.
158
159	## System Prompt Generation
160
161	Generate once, copy to backend directory:

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openui-forge-python

10installs0forks

View on GitHub

How to install openui-forge-python?

othmanadi/openui-forge/openui-forge-python

$npx -y skills add OthmanAdi/openui-forge --skill openui-forge-python

Installs into the current project.

Summary

OpenUI generative UI with Python FastAPI backend. OpenAI and Anthropic SDK variants.

Files · 1

View on GitHub

SKILL.md

1	# OpenUI Forge — Python
2
3	Build generative UI apps with a React frontend + Python FastAPI backend. Streams OpenAI-compatible NDJSON.
4
5	## Activation Triggers
6
7	- "openui python", "openui fastapi", "openui flask"
8	- "generative ui python", "python streaming ui backend"
9
10	## Prerequisites
11
12	- Node.js >= 22 (24 LTS recommended) + React >= 18.3.1 (19+ recommended) (frontend)
13	- Python >= 3.10 (backend)
14	- `OPENAI_API_KEY` or `ANTHROPIC_API_KEY` set
15
16	## Quick Start
17
18	1. Create the React frontend and install OpenUI deps:
19	```bash
20	npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod
21	```
22	2. Generate the system prompt from your component library:
23	```bash
24	npx @openuidev/cli generate ./src/lib/library.ts --out backend/system-prompt.txt
25	```
26	3. Set up the Python backend (see Full Code below)
27	4. Run both: frontend on `:3000`, backend on `:8000`
28
29	## Full Code
30
31	### Backend: `backend/requirements.txt`
32
33	```
34	fastapi>=0.115.0
35	uvicorn>=0.24.0
36	openai>=2.0
37	anthropic>=0.111.0
38	python-dotenv>=1.0.0
39	```
40
41	> The Python >= 3.10 floor comes from fastapi/uvicorn/python-dotenv; openai and anthropic themselves need only Python 3.9.
42
43	### Backend (OpenAI): `backend/main.py`
44
45	```python
46	import os
47	from pathlib import Path
48	from dotenv import load_dotenv
49	from fastapi import FastAPI, Request
50	from fastapi.middleware.cors import CORSMiddleware
51	from fastapi.responses import StreamingResponse
52	from openai import AsyncOpenAI
53
54	load_dotenv()
55	app = FastAPI()
56	app.add_middleware(
57	CORSMiddleware,
58	allow_origins=["http://localhost:3000"],
59	allow_methods=["POST"],
60	allow_headers=["*"],
61	)
62
63	# AsyncOpenAI keeps the request from blocking the event loop during streaming.
64	client = AsyncOpenAI()
65	SYSTEM_PROMPT = Path("system-prompt.txt").read_text()
66
67	@app.post("/api/chat")
68	async def chat(request: Request):
69	body = await request.json()
70	messages = [{"role": "system", "content": SYSTEM_PROMPT}] + body["messages"]
71
72	async def generate():
73	response = await client.chat.completions.create(
74	model=os.getenv("OPENAI_MODEL", "gpt-5.5"),
75	stream=True,
76	messages=messages,
77	)
78	async for chunk in response:
79	data = chunk.model_dump_json()
80	yield f"data: {data}\n\n"
81	yield "data: [DONE]\n\n"
82
83	return StreamingResponse(generate(), media_type="text/event-stream")
84	```
85
86	### Backend (Anthropic variant): `backend/main_anthropic.py`
87
88	```python
89	import os, json, time
90	from pathlib import Path
91	from dotenv import load_dotenv
92	from fastapi import FastAPI, Request
93	from fastapi.middleware.cors import CORSMiddleware
94	from fastapi.responses import StreamingResponse
95	from anthropic import AsyncAnthropic
96
97	load_dotenv()
98	app = FastAPI()
99	app.add_middleware(
100	CORSMiddleware,
101	allow_origins=["http://localhost:3000"],
102	allow_methods=["POST"],
103	allow_headers=["*"],
104	)
105
106	# AsyncAnthropic mirrors AsyncOpenAI so the stream does not block the loop.
107	client = AsyncAnthropic()
108	SYSTEM_PROMPT = Path("system-prompt.txt").read_text()
109
110	@app.post("/api/chat")
111	async def chat(request: Request):
112	body = await request.json()
113	stream_id = f"chatcmpl-{int(time.time())}"
114
115	async def generate():
116	async with client.messages.stream(
117	model=os.getenv("ANTHROPIC_MODEL", "claude-sonnet-4-6"),
118	max_tokens=4096,
119	system=SYSTEM_PROMPT,
120	messages=body["messages"],
121	) as stream:
122	async for text in stream.text_stream:
123	chunk = {"id": stream_id, "object": "chat.completion.chunk",
124	"choices": [{"index": 0, "delta": {"content": text}, "finish_reason": None}]}
125	yield f"data: {json.dumps(chunk)}\n\n"
126	done = {"id": stream_id, "object": "chat.completion.chunk",
127	"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]}
128	yield f"data: {json.dumps(done)}\n\n"
129	yield "data: [DONE]\n\n"
130
131	return StreamingResponse(generate(), media_type="text/event-stream")
132	```
133
134	### Frontend: `app/chat/page.tsx` (or `src/Chat.tsx` for Vite)
135
136	```tsx
137	"use client";
138	import { FullScreen } from "@openuidev/react-ui";
139	import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
140	import {
141	openAIAdapter,
142	openAIMessageFormat,
143	} from "@openuidev/react-headless";
144
145	export default function ChatPage() {
146	return (
147	<FullScreen
148	componentLibrary={openuiChatLibrary}
149	streamProtocol={openAIAdapter()}
150	messageFormat={openAIMessageFormat}
151	apiUrl="http://localhost:8000/api/chat"
152	/>
153	);
154	}
155	```
156
157	> The Python backend emits SSE (`data: {json}\n\n`). Pair it with `openAIAdapter()` on the frontend. `openAIReadableStreamAdapter()` is for NDJSON (no `data:` prefix) and will silently produce no output here.
158
159	## System Prompt Generation
160
161	Generate once, copy to backend directory:

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6 picks

Type