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templates/cloudflare-workers/worker-backend.ts

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+/**
+ * Cloudflare Worker Backend with Hono + TheSys C1
+ *
+ * File: backend/src/index.ts
+ *
+ * Features:
+ * - Hono routing
+ * - TheSys C1 API proxy
+ * - Streaming support
+ * - Static assets serving
+ * - CORS handling
+ */
+
+import { Hono } from "hono";
+import { cors } from "hono/cors";
+import { serveStatic } from "hono/cloudflare-workers";
+
+type Bindings = {
+  THESYS_API_KEY: string;
+  ASSETS: Fetcher;
+};
+
+const app = new Hono<{ Bindings: Bindings }>();
+
+// CORS middleware
+app.use("/*", cors({
+  origin: "*",
+  allowMethods: ["GET", "POST", "OPTIONS"],
+  allowHeaders: ["Content-Type", "Authorization"],
+}));
+
+// ============================================================================
+// Chat API Endpoint
+// ============================================================================
+
+app.post("/api/chat", async (c) => {
+  try {
+    const { prompt, previousC1Response } = await c.req.json();
+
+    if (!prompt || typeof prompt !== "string") {
+      return c.json({ error: "Invalid prompt" }, 400);
+    }
+
+    // Check API key binding
+    if (!c.env.THESYS_API_KEY) {
+      console.error("THESYS_API_KEY binding not found");
+      return c.json({ error: "Server configuration error" }, 500);
+    }
+
+    // Build messages
+    const messages = [
+      {
+        role: "system",
+        content: "You are a helpful AI assistant that generates interactive UI.",
+      },
+      {
+        role: "user",
+        content: prompt,
+      },
+    ];
+
+    if (previousC1Response) {
+      messages.splice(1, 0, {
+        role: "assistant",
+        content: previousC1Response,
+      });
+    }
+
+    // Call TheSys C1 API
+    const response = await fetch(
+      "https://api.thesys.dev/v1/embed/chat/completions",
+      {
+        method: "POST",
+        headers: {
+          "Authorization": `Bearer ${c.env.THESYS_API_KEY}`,
+          "Content-Type": "application/json",
+        },
+        body: JSON.stringify({
+          model: "c1/openai/gpt-5/v-20250930",
+          messages,
+          stream: false, // Or handle streaming
+          temperature: 0.7,
+          max_tokens: 2000,
+        }),
+      }
+    );
+
+    if (!response.ok) {
+      const error = await response.text();
+      console.error("TheSys API Error:", error);
+      return c.json(
+        { error: "Failed to get AI response" },
+        response.status
+      );
+    }
+
+    const data = await response.json();
+
+    return c.json({
+      response: data.choices[0]?.message?.content || "",
+      usage: data.usage,
+    });
+  } catch (error) {
+    console.error("Chat endpoint error:", error);
+    return c.json(
+      { error: error instanceof Error ? error.message : "Internal error" },
+      500
+    );
+  }
+});
+
+// ============================================================================
+// Streaming Chat Endpoint
+// ============================================================================
+
+app.post("/api/chat/stream", async (c) => {
+  try {
+    const { prompt } = await c.req.json();
+
+    const response = await fetch(
+      "https://api.thesys.dev/v1/embed/chat/completions",
+      {
+        method: "POST",
+        headers: {
+          "Authorization": `Bearer ${c.env.THESYS_API_KEY}`,
+          "Content-Type": "application/json",
+        },
+        body: JSON.stringify({
+          model: "c1/openai/gpt-5/v-20250930",
+          messages: [
+            { role: "system", content: "You are a helpful assistant." },
+            { role: "user", content: prompt },
+          ],
+          stream: true,
+        }),
+      }
+    );
+
+    if (!response.ok) {
+      return c.json({ error: "Stream failed" }, response.status);
+    }
+
+    // Return the stream directly
+    return new Response(response.body, {
+      headers: {
+        "Content-Type": "text/event-stream",
+        "Cache-Control": "no-cache",
+        "Connection": "keep-alive",
+      },
+    });
+  } catch (error) {
+    console.error("Stream error:", error);
+    return c.json({ error: "Stream failed" }, 500);
+  }
+});
+
+// ============================================================================
+// Health Check
+// ============================================================================
+
+app.get("/api/health", (c) => {
+  return c.json({
+    status: "ok",
+    timestamp: new Date().toISOString(),
+  });
+});
+
+// ============================================================================
+// Serve Static Assets (Vite build output)
+// ============================================================================
+
+app.get("/*", serveStatic({ root: "./", mimes: {} }));
+
+export default app;
+
+/**
+ * Alternative: Using Workers AI directly (cheaper for some models)
+ *
+ * type Bindings = {
+ *   AI: any; // Cloudflare AI binding
+ * };
+ *
+ * app.post("/api/chat", async (c) => {
+ *   const { prompt } = await c.req.json();
+ *
+ *   const aiResponse = await c.env.AI.run('@cf/meta/llama-3-8b-instruct', {
+ *     messages: [
+ *       { role: "system", content: "You are a helpful assistant." },
+ *       { role: "user", content: prompt },
+ *     ],
+ *   });
+ *
+ *   // Then optionally send to TheSys C1 for UI generation
+ *   const c1Response = await fetch("https://api.thesys.dev/v1/embed/chat/completions", {
+ *     method: "POST",
+ *     headers: {
+ *       "Authorization": `Bearer ${c.env.THESYS_API_KEY}`,
+ *       "Content-Type": "application/json",
+ *     },
+ *     body: JSON.stringify({
+ *       model: "c1/openai/gpt-5/v-20250930",
+ *       messages: [
+ *         {
+ *           role: "system",
+ *           content: "Generate a UI for this content: " + aiResponse.response,
+ *         },
+ *       ],
+ *     }),
+ *   });
+ *
+ *   // ... return c1Response
+ * });
+ */
+
+/**
+ * Alternative: With D1 Database for message persistence
+ *
+ * type Bindings = {
+ *   THESYS_API_KEY: string;
+ *   DB: D1Database; // D1 binding
+ * };
+ *
+ * app.post("/api/chat", async (c) => {
+ *   const { userId, threadId, prompt } = await c.req.json();
+ *
+ *   // Save user message
+ *   await c.env.DB.prepare(
+ *     "INSERT INTO messages (thread_id, user_id, role, content) VALUES (?, ?, ?, ?)"
+ *   )
+ *     .bind(threadId, userId, "user", prompt)
+ *     .run();
+ *
+ *   // Get conversation history
+ *   const { results } = await c.env.DB.prepare(
+ *     "SELECT role, content FROM messages WHERE thread_id = ? ORDER BY created_at"
+ *   )
+ *     .bind(threadId)
+ *     .all();
+ *
+ *   const messages = [
+ *     { role: "system", content: "You are a helpful assistant." },
+ *     ...results,
+ *   ];
+ *
+ *   // Call TheSys API with full history...
+ * });
+ */