99 lines
3.9 KiB
Python
99 lines
3.9 KiB
Python
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"""
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Excalidraw AI 代理服务
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接收 Excalidraw 的 text-to-diagram 请求，转发给 deepseek-v3 生成 Mermaid 语法
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"""
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from fastapi import FastAPI, Request
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from fastapi.middleware.cors import CORSMiddleware
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import requests
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import json
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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LLM_API = "http://10.102.24.75:3000/v1/chat/completions"
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LLM_KEY = "sk-BlQIGRrotbVDWE5mXCPBFjVWIvJ83hldzz67xInNwzVo7pPb"
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SYSTEM_PROMPT = """You are an expert at creating Mermaid diagrams.
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When the user describes a diagram, workflow, flowchart, or similar,
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generate ONLY valid Mermaid syntax. Do not include any explanation,
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just the Mermaid code. Do not wrap it in markdown code blocks.
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Always start with a diagram type declaration like: graph TD, flowchart LR, sequenceDiagram, classDiagram, etc."""
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@app.post("/v1/ai/text-to-diagram/generate")
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async def text_to_diagram(request: Request):
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body = await request.json()
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print(f"[AI] Received request: {json.dumps(body, ensure_ascii=False)[:500]}")
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prompt = body.get("prompt", body.get("text", body.get("message", "")))
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try:
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resp = requests.post(LLM_API, json={
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"model": "deepseek-v3",
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.3,
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"max_tokens": 2048
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}, headers={"Authorization": f"Bearer {LLM_KEY}"}, timeout=60)
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result = resp.json()
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print(f"[AI] LLM response status: {resp.status_code}")
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mermaid_code = result["choices"][0]["message"]["content"].strip()
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# 清理可能的 markdown 包裹
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if mermaid_code.startswith("```"):
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mermaid_code = mermaid_code.split("\n", 1)[1] if "\n" in mermaid_code else mermaid_code[3:]
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if mermaid_code.endswith("```"):
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mermaid_code = mermaid_code[:-3].strip()
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print(f"[AI] Mermaid output: {mermaid_code[:200]}")
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return {"generatedResponse": mermaid_code}
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except Exception as e:
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print(f"[AI] Error: {e}")
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return {"generatedResponse": f"graph TD\n A[Error: {str(e)[:50]}]"}
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@app.post("/v1/ai/diagram-to-code/generate")
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async def diagram_to_code(request: Request):
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body = await request.json()
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texts = body.get("texts", [])
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theme = body.get("theme", "light")
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print(f"[AI] diagram-to-code request, texts: {texts[:5]}, theme: {theme}")
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prompt = f"Based on these UI element labels: {', '.join(texts) if texts else 'empty wireframe'}. Theme: {theme}. Generate a complete, beautiful HTML page with inline CSS that represents this wireframe layout. Only output the HTML code, nothing else."
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try:
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resp = requests.post(LLM_API, json={
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"model": "deepseek-v3",
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"messages": [
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{"role": "system", "content": "You are an expert web developer. Generate complete HTML with inline CSS based on wireframe descriptions. Output ONLY the HTML code, no explanation, no markdown code blocks."},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.3,
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"max_tokens": 4096
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}, headers={"Authorization": f"Bearer {LLM_KEY}"}, timeout=60)
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result = resp.json()
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html_code = result["choices"][0]["message"]["content"].strip()
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if html_code.startswith("```"):
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html_code = html_code.split("\n", 1)[1] if "\n" in html_code else html_code[3:]
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if html_code.endswith("```"):
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html_code = html_code[:-3].strip()
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print(f"[AI] HTML output length: {len(html_code)}")
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return html_code
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except Exception as e:
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print(f"[AI] diagram-to-code error: {e}")
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return f"<html><body><h1>Generation Error</h1><p>{str(e)[:100]}</p></body></html>"
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=18082)
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