feat(integrations): add NextJS LLM/Grafana integration + enable dashboard embedding

integrations/nextjs/llm-client.ts

@@ -0,0 +1,131 @@
+/**
+ * LLM Client for api.riotpiao.com
+ *
+ * Usage:
+ *   import { chat, streamChat } from './llm-client';
+ *
+ *   // Non-streaming
+ *   const response = await chat({ model: 'reasoning', messages: [...] });
+ *
+ *   // Streaming
+ *   for await (const chunk of streamChat({ model: 'reasoning', messages: [...] })) {
+ *     process.stdout.write(chunk);
+ *   }
+ */
+
+export type Model = 'reasoning' | 'ornith:35b' | 'qwen2.5:3b-instruct';
+
+export interface Message {
+  role: 'system' | 'user' | 'assistant';
+  content: string;
+}
+
+export interface ChatRequest {
+  model: Model;
+  messages: Message[];
+  max_tokens?: number;
+  temperature?: number;
+  stream?: boolean;
+}
+
+export interface ChatResponse {
+  id: string;
+  object: string;
+  created: number;
+  model: string;
+  choices: {
+    index: number;
+    message: Message;
+    finish_reason: string;
+  }[];
+  usage?: {
+    prompt_tokens: number;
+    completion_tokens: number;
+    total_tokens: number;
+  };
+}
+
+const LLM_BASE_URL = process.env.LLM_BASE_URL || 'https://api.riotpiao.com/v1';
+
+/**
+ * Non-streaming chat completion
+ */
+export async function chat(request: ChatRequest): Promise<ChatResponse> {
+  const response = await fetch(`${LLM_BASE_URL}/chat/completions`, {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ ...request, stream: false }),
+  });
+
+  if (!response.ok) {
+    throw new Error(`LLM API error: ${response.status} ${await response.text()}`);
+  }
+
+  return response.json();
+}
+
+/**
+ * Streaming chat completion - yields content chunks
+ */
+export async function* streamChat(request: ChatRequest): AsyncGenerator<string> {
+  const response = await fetch(`${LLM_BASE_URL}/chat/completions`, {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ ...request, stream: true }),
+  });
+
+  if (!response.ok) {
+    throw new Error(`LLM API error: ${response.status} ${await response.text()}`);
+  }
+
+  const reader = response.body?.getReader();
+  if (!reader) throw new Error('No response body');
+
+  const decoder = new TextDecoder();
+  let buffer = '';
+
+  while (true) {
+    const { done, value } = await reader.read();
+    if (done) break;
+
+    buffer += decoder.decode(value, { stream: true });
+    const lines = buffer.split('\n');
+    buffer = lines.pop() || '';
+
+    for (const line of lines) {
+      if (line.startsWith('data: ')) {
+        const data = line.slice(6);
+        if (data === '[DONE]') return;
+        try {
+          const parsed = JSON.parse(data);
+          const content = parsed.choices?.[0]?.delta?.content;
+          if (content) yield content;
+        } catch {
+          // Skip malformed chunks
+        }
+      }
+    }
+  }
+}
+
+/**
+ * React hook compatible streaming (returns ReadableStream for Response)
+ */
+export function createStreamResponse(request: ChatRequest): Response {
+  const stream = new ReadableStream({
+    async start(controller) {
+      try {
+        for await (const chunk of streamChat(request)) {
+          controller.enqueue(new TextEncoder().encode(chunk));
+        }
+        controller.close();
+      } catch (err) {
+        controller.error(err);
+      }
+    },
+  });
+
+  return new Response(stream, {
+    headers: { 'Content-Type': 'text/plain; charset=utf-8' },
+  });
+}