refactor: Modularize proxy and add tool_use support

- Split monolithic messages.js (223 lines) into 5 focused modules
- Add full tool_use/tool_result round-trip translation
- Add x-api-key header authentication (Anthropic SDK default)
- Fix SSE Content-Type via Hono streamSSE helper
- Fix streaming usage tracking with stream_options.include_usage
- Add stop_reason mapping (end_turn, max_tokens, tool_use, stop_sequence)
- Forward stop_sequences to OpenAI stop parameter
- Handle system message as string or array of content blocks
- Use timing-safe XOR comparison for auth tokens
- Cache OpenAI client and model map across requests
- Sanitize error responses to prevent upstream detail leakage
- Use crypto.randomUUID() for unique message IDs
- Remove non-existent build/dev commands from vercel.json

src/auth-middleware.js

@@ -0,0 +1,39 @@
+// Constant-time string comparison using byte-level XOR
+// Works cross-platform: Cloudflare Workers, Node 18+, Deno, Bun
+function timingSafeEqual(a, b) {
+  const encoder = new TextEncoder();
+  const bufA = encoder.encode(a);
+  const bufB = encoder.encode(b);
+  if (bufA.byteLength !== bufB.byteLength) return false;
+  let result = 0;
+  for (let i = 0; i < bufA.byteLength; i++) {
+    result |= bufA[i] ^ bufB[i];
+  }
+  return result === 0;
+}
+
+// Auth middleware supporting both x-api-key (Anthropic SDK) and Authorization Bearer
+export function authMiddleware() {
+  return async (c, next) => {
+    const gatewayToken = c.env.GATEWAY_TOKEN;
+    if (!gatewayToken) {
+      return c.json({
+        type: 'error',
+        error: { type: 'api_error', message: 'GATEWAY_TOKEN not configured' },
+      }, 500);
+    }
+
+    const apiKey = c.req.header('x-api-key') || '';
+    const authHeader = c.req.header('Authorization') || '';
+    const token = apiKey || (authHeader.startsWith('Bearer ') ? authHeader.slice(7) : authHeader);
+
+    if (!token || !timingSafeEqual(token, gatewayToken)) {
+      return c.json({
+        type: 'error',
+        error: { type: 'authentication_error', message: 'Unauthorized' },
+      }, 401);
+    }
+
+    await next();
+  };
+}

src/index.js

@@ -1,6 +1,7 @@
 import { Hono } from 'hono';
 import { logger } from 'hono/logger';
 import { cors } from 'hono/cors';
+import { authMiddleware } from './auth-middleware.js';
 import messages from './routes/messages.js';
 
 const app = new Hono();
@@ -9,9 +10,12 @@ const app = new Hono();
 app.use('*', logger());
 app.use('*', cors());
 
-// Health check
+// Health check (unauthenticated)
 app.get('/', (c) => c.json({ status: 'ok', name: 'Claude Central Gateway' }));
 
+// Auth middleware for API routes
+app.use('/v1/*', authMiddleware());
+
 // Routes
 app.route('/v1', messages);
 

src/openai-client.js

@@ -0,0 +1,31 @@
+import OpenAI from 'openai';
+
+// Cache OpenAI client and parsed model map to avoid re-creation per request
+let cachedClient = null;
+let cachedApiKey = null;
+let cachedModelMap = null;
+let cachedModelMapRaw = null;
+
+export function getOpenAIClient(env) {
+  if (cachedClient && cachedApiKey === env.OPENAI_API_KEY) {
+    return cachedClient;
+  }
+  cachedApiKey = env.OPENAI_API_KEY;
+  cachedClient = new OpenAI({ apiKey: env.OPENAI_API_KEY });
+  return cachedClient;
+}
+
+export function mapModel(claudeModel, env) {
+  const raw = env.MODEL_MAP || '';
+  if (raw !== cachedModelMapRaw) {
+    cachedModelMapRaw = raw;
+    cachedModelMap = Object.fromEntries(
+      raw.split(',').filter(Boolean).map((p) => {
+        const trimmed = p.trim();
+        const idx = trimmed.indexOf(':');
+        return idx > 0 ? [trimmed.slice(0, idx), trimmed.slice(idx + 1)] : [trimmed, trimmed];
+      })
+    );
+  }
+  return cachedModelMap[claudeModel] || claudeModel;
+}

src/routes/messages.js

@@ -1,222 +1,45 @@
 import { Hono } from 'hono';
-import { stream } from 'hono/streaming';
-import OpenAI from 'openai';
+import { getOpenAIClient, mapModel } from '../openai-client.js';
+import { buildOpenAIRequest } from '../transform-request.js';
+import { transformResponse, streamAnthropicResponse } from '../transform-response.js';
 
 const app = new Hono();
 
-// Parse model mapping from env var
-function parseModelMap(envVar) {
-  if (!envVar) return {};
-  return Object.fromEntries(
-    envVar.split(',').map(pair => {
-      const [claude, provider] = pair.trim().split(':');
-      return [claude, provider];
-    })
-  );
-}
-
-// Map Claude model to provider model
-function mapModel(claudeModel, env) {
-  const modelMap = parseModelMap(env.MODEL_MAP);
-  return modelMap[claudeModel] || claudeModel;
-}
-
-// Transform Anthropic messages to OpenAI format
-function transformMessages(request) {
-  const messages = [];
-
-  // Add system message if present
-  if (request.system) {
-    messages.push({ role: 'system', content: request.system });
-  }
-
-  // Transform messages array
-  for (const msg of request.messages || []) {
-    if (typeof msg.content === 'string') {
-      messages.push({ role: msg.role, content: msg.content });
-    } else if (Array.isArray(msg.content)) {
-      // Handle multi-part content
-      const content = [];
-
-      for (const part of msg.content) {
-        if (part.type === 'text') {
-          content.push({ type: 'text', text: part.text });
-        } else if (part.type === 'image') {
-          if (part.source?.type === 'base64') {
-            content.push({
-              type: 'image_url',
-              image_url: {
-                url: `data:${part.source.media_type};base64,${part.source.data}`
-              }
-            });
-          } else if (part.source?.type === 'url') {
-            content.push({
-              type: 'image_url',
-              image_url: { url: part.source.url }
-            });
-          }
-        }
-      }
-
-      messages.push({ role: msg.role, content });
-    }
-  }
-
-  return messages;
-}
-
-// Format Anthropic SSE event
-function formatSSE(event, data) {
-  return `event: ${event}\ndata: ${JSON.stringify(data)}\n\n`;
-}
-
-// Auth middleware
-app.use('*', async (c, next) => {
-  const authHeader = c.req.header('Authorization') || '';
-  const token = authHeader.startsWith('Bearer ')
-    ? authHeader.slice(7)
-    : authHeader;
-
-  if (token !== c.env.GATEWAY_TOKEN) {
-    return c.json({ type: 'error', error: { type: 'authentication_error', message: 'Unauthorized' } }, 401);
-  }
-
-  await next();
-});
-
-// POST /v1/messages
+// POST /v1/messages — proxy Anthropic Messages API to OpenAI Chat Completions
 app.post('/messages', async (c) => {
   const env = c.env;
 
-  // Validate OpenAI API key
   if (!env.OPENAI_API_KEY) {
-    return c.json({ type: 'error', error: { type: 'api_error', message: 'OPENAI_API_KEY not configured' } }, 500);
+    return c.json({
+      type: 'error',
+      error: { type: 'api_error', message: 'Provider API key not configured' },
+    }, 500);
   }
 
   try {
     const anthropicRequest = await c.req.json();
-    const openai = new OpenAI({
-      apiKey: env.OPENAI_API_KEY
-    });
-
-    const messages = transformMessages(anthropicRequest);
+    const openai = getOpenAIClient(env);
     const model = mapModel(anthropicRequest.model, env);
-    const streamResponse = anthropicRequest.stream !== false;
+    const isStreaming = anthropicRequest.stream === true;
+    const openaiPayload = buildOpenAIRequest(anthropicRequest, model);
 
-    if (streamResponse) {
-      // Streaming response
-      const streamResponse = await openai.chat.completions.create({
-        model,
-        messages,
-        stream: true,
-        max_tokens: anthropicRequest.max_tokens,
-        temperature: anthropicRequest.temperature,
-        top_p: anthropicRequest.top_p
-      });
-
-      let messageId = `msg_${Date.now()}`;
-      let outputTokens = 0;
-
-      return stream(c, async (s) => {
-        // Send message_start event
-        s.write(formatSSE('message_start', {
-          type: 'message_start',
-          message: {
-            id: messageId,
-            type: 'message',
-            role: 'assistant',
-            content: [],
-            model: anthropicRequest.model,
-            stop_reason: null,
-            usage: { input_tokens: 0, output_tokens: 0 }
-          }
-        }));
-
-        // Send content_block_start
-        s.write(formatSSE('content_block_start', {
-          type: 'content_block_start',
-          index: 0,
-          content_block: { type: 'text', text: '' }
-        }));
-
-        for await (const chunk of streamResponse) {
-          const delta = chunk.choices[0]?.delta;
-
-          if (delta?.content) {
-            s.write(formatSSE('content_block_delta', {
-              type: 'content_block_delta',
-              index: 0,
-              delta: { type: 'text_delta', text: delta.content }
-            }));
-          }
-
-          if (chunk.usage) {
-            outputTokens = chunk.usage.completion_tokens || outputTokens;
-          }
-        }
-
-        // Send content_block_stop
-        s.write(formatSSE('content_block_stop', {
-          type: 'content_block_stop',
-          index: 0
-        }));
-
-        // Send message_delta with final usage
-        s.write(formatSSE('message_delta', {
-          type: 'message_delta',
-          delta: { stop_reason: 'end_turn' },
-          usage: { output_tokens: outputTokens }
-        }));
-
-        // Send message_stop
-        s.write(formatSSE('message_stop', { type: 'message_stop' }));
-      });
-    } else {
-      // Non-streaming response
-      const response = await openai.chat.completions.create({
-        model,
-        messages,
-        stream: false,
-        max_tokens: anthropicRequest.max_tokens,
-        temperature: anthropicRequest.temperature,
-        top_p: anthropicRequest.top_p
-      });
-
-      const content = response.choices[0]?.message?.content || '';
-
-      return c.json({
-        id: `msg_${Date.now()}`,
-        type: 'message',
-        role: 'assistant',
-        content: [{ type: 'text', text: content }],
-        model: anthropicRequest.model,
-        stop_reason: 'end_turn',
-        usage: {
-          input_tokens: response.usage?.prompt_tokens || 0,
-          output_tokens: response.usage?.completion_tokens || 0
-        }
-      });
+    if (isStreaming) {
+      const openaiStream = await openai.chat.completions.create(openaiPayload);
+      return streamAnthropicResponse(c, openaiStream, anthropicRequest);
     }
+
+    const response = await openai.chat.completions.create(openaiPayload);
+    return c.json(transformResponse(response, anthropicRequest));
   } catch (error) {
     console.error('Proxy error:', error);
-
-    if (error.status) {
-      return c.json({
-        type: 'error',
-        error: {
-          type: 'api_error',
-          message: error.message
-        }
-      }, error.status);
-    }
-
+    const status = error.status || 500;
     return c.json({
       type: 'error',
       error: {
-        type: 'internal_error',
-        message: 'Internal server error'
-      }
-    }, 500);
+        type: status >= 500 ? 'api_error' : 'invalid_request_error',
+        message: 'Request failed',
+      },
+    }, status);
   }
 });
 

src/transform-request.js

@@ -0,0 +1,163 @@
+// Transform Anthropic Messages API request → OpenAI Chat Completions API request
+
+// Build complete OpenAI request payload from Anthropic request
+export function buildOpenAIRequest(anthropicRequest, model) {
+  const payload = {
+    model,
+    messages: transformMessages(anthropicRequest),
+    max_tokens: anthropicRequest.max_tokens,
+    temperature: anthropicRequest.temperature,
+    top_p: anthropicRequest.top_p,
+  };
+
+  if (anthropicRequest.stream === true) {
+    payload.stream = true;
+    payload.stream_options = { include_usage: true };
+  }
+
+  if (anthropicRequest.stop_sequences?.length) {
+    payload.stop = anthropicRequest.stop_sequences;
+  }
+
+  if (anthropicRequest.tools?.length) {
+    payload.tools = anthropicRequest.tools.map((t) => ({
+      type: 'function',
+      function: { name: t.name, description: t.description, parameters: t.input_schema },
+    }));
+  }
+
+  if (anthropicRequest.tool_choice) {
+    payload.tool_choice = mapToolChoice(anthropicRequest.tool_choice);
+  }
+
+  return payload;
+}
+
+// Map Anthropic tool_choice → OpenAI tool_choice
+function mapToolChoice(tc) {
+  if (tc.type === 'auto') return 'auto';
+  if (tc.type === 'any') return 'required';
+  if (tc.type === 'none') return 'none';
+  if (tc.type === 'tool') return { type: 'function', function: { name: tc.name } };
+  return 'auto';
+}
+
+// Transform Anthropic messages array → OpenAI messages array
+function transformMessages(request) {
+  const messages = [];
+
+  // System message: string or array of text blocks
+  if (request.system) {
+    const systemText = typeof request.system === 'string'
+      ? request.system
+      : request.system.filter((b) => b.type === 'text').map((b) => b.text).join('\n\n');
+    if (systemText) {
+      messages.push({ role: 'system', content: systemText });
+    }
+  }
+
+  for (const msg of request.messages || []) {
+    if (typeof msg.content === 'string') {
+      messages.push({ role: msg.role, content: msg.content });
+      continue;
+    }
+
+    if (!Array.isArray(msg.content)) continue;
+
+    if (msg.role === 'assistant') {
+      transformAssistantMessage(msg, messages);
+    } else {
+      transformUserMessage(msg, messages);
+    }
+  }
+
+  return messages;
+}
+
+// Transform assistant message with potential tool_use blocks
+function transformAssistantMessage(msg, messages) {
+  const content = [];
+  const toolCalls = [];
+
+  for (const part of msg.content) {
+    if (part.type === 'text') {
+      content.push({ type: 'text', text: part.text });
+    } else if (part.type === 'tool_use') {
+      toolCalls.push({
+        id: part.id,
+        type: 'function',
+        function: { name: part.name, arguments: JSON.stringify(part.input) },
+      });
+    }
+    // Skip thinking, cache_control, and other unsupported blocks
+  }
+
+  const openaiMsg = { role: 'assistant' };
+
+  // Set content: string for text-only, null if only tool_calls
+  if (content.length === 1 && content[0].type === 'text') {
+    openaiMsg.content = content[0].text;
+  } else if (content.length > 1) {
+    openaiMsg.content = content;
+  } else {
+    openaiMsg.content = null;
+  }
+
+  if (toolCalls.length) {
+    openaiMsg.tool_calls = toolCalls;
+  }
+
+  messages.push(openaiMsg);
+}
+
+// Transform user message with potential tool_result and mixed content blocks
+function transformUserMessage(msg, messages) {
+  const content = [];
+  const toolResults = [];
+
+  for (const part of msg.content) {
+    if (part.type === 'text') {
+      content.push({ type: 'text', text: part.text });
+    } else if (part.type === 'image') {
+      if (part.source?.type === 'base64') {
+        content.push({
+          type: 'image_url',
+          image_url: { url: `data:${part.source.media_type};base64,${part.source.data}` },
+        });
+      } else if (part.source?.type === 'url') {
+        content.push({ type: 'image_url', image_url: { url: part.source.url } });
+      }
+    } else if (part.type === 'tool_result') {
+      const resultContent = extractToolResultContent(part);
+      toolResults.push({
+        role: 'tool',
+        tool_call_id: part.tool_use_id,
+        content: resultContent,
+      });
+    }
+  }
+
+  // Each tool_result becomes a separate OpenAI tool message
+  for (const tr of toolResults) {
+    messages.push(tr);
+  }
+
+  // Non-tool content becomes a user message
+  if (content.length === 1 && content[0].type === 'text') {
+    messages.push({ role: 'user', content: content[0].text });
+  } else if (content.length > 0) {
+    messages.push({ role: 'user', content });
+  }
+}
+
+// Extract text content from tool_result (string, array, or undefined)
+function extractToolResultContent(part) {
+  const prefix = part.is_error ? '[ERROR] ' : '';
+  if (typeof part.content === 'string') return prefix + part.content;
+  if (!part.content) return prefix || '';
+  const text = part.content
+    .filter((b) => b.type === 'text')
+    .map((b) => b.text)
+    .join('\n');
+  return prefix + text;
+}

src/transform-response.js

@@ -0,0 +1,172 @@
+import { streamSSE } from 'hono/streaming';
+
+// Map OpenAI finish_reason → Anthropic stop_reason
+function mapStopReason(finishReason, hadStopSequences) {
+  if (finishReason === 'stop' && hadStopSequences) return 'stop_sequence';
+  const map = {
+    stop: 'end_turn',
+    length: 'max_tokens',
+    tool_calls: 'tool_use',
+    content_filter: 'end_turn',
+  };
+  return map[finishReason] || 'end_turn';
+}
+
+// Build Anthropic content array from OpenAI response message
+function buildContentBlocks(message) {
+  const content = [];
+  if (message?.content) {
+    content.push({ type: 'text', text: message.content });
+  }
+  if (message?.tool_calls) {
+    for (const tc of message.tool_calls) {
+      let input = {};
+      try {
+        input = JSON.parse(tc.function.arguments || '{}');
+      } catch {
+        input = {};
+      }
+      content.push({ type: 'tool_use', id: tc.id, name: tc.function.name, input });
+    }
+  }
+  return content.length ? content : [{ type: 'text', text: '' }];
+}
+
+// Transform non-streaming OpenAI response → Anthropic response
+export function transformResponse(openaiResponse, anthropicRequest) {
+  const choice = openaiResponse.choices[0];
+  const hadStopSequences = Boolean(anthropicRequest.stop_sequences?.length);
+
+  return {
+    id: `msg_${crypto.randomUUID()}`,
+    type: 'message',
+    role: 'assistant',
+    content: buildContentBlocks(choice?.message),
+    model: anthropicRequest.model,
+    stop_reason: mapStopReason(choice?.finish_reason, hadStopSequences),
+    usage: {
+      input_tokens: openaiResponse.usage?.prompt_tokens || 0,
+      output_tokens: openaiResponse.usage?.completion_tokens || 0,
+    },
+  };
+}
+
+// Write a single SSE event
+async function writeEvent(stream, event, data) {
+  await stream.writeSSE({ event, data: JSON.stringify(data) });
+}
+
+// Stream OpenAI response → Anthropic SSE events
+export function streamAnthropicResponse(c, openaiStream, anthropicRequest) {
+  const hadStopSequences = Boolean(anthropicRequest.stop_sequences?.length);
+
+  return streamSSE(c, async (stream) => {
+    const messageId = `msg_${crypto.randomUUID()}`;
+    let inputTokens = 0;
+    let outputTokens = 0;
+    let finishReason = null;
+
+    // Streaming state for content blocks
+    let blockIndex = 0;
+    let textBlockStarted = false;
+    const toolCallBuffers = {}; // index → { id, name, arguments }
+
+    // Send message_start
+    await writeEvent(stream, 'message_start', {
+      type: 'message_start',
+      message: {
+        id: messageId, type: 'message', role: 'assistant',
+        content: [], model: anthropicRequest.model,
+        stop_reason: null, usage: { input_tokens: 0, output_tokens: 0 },
+      },
+    });
+
+    for await (const chunk of openaiStream) {
+      const choice = chunk.choices[0];
+      const delta = choice?.delta;
+
+      // Track finish_reason from final chunk
+      if (choice?.finish_reason) {
+        finishReason = choice.finish_reason;
+      }
+
+      // Handle text content delta
+      if (delta?.content) {
+        if (!textBlockStarted) {
+          await writeEvent(stream, 'content_block_start', {
+            type: 'content_block_start', index: blockIndex,
+            content_block: { type: 'text', text: '' },
+          });
+          textBlockStarted = true;
+        }
+        await writeEvent(stream, 'content_block_delta', {
+          type: 'content_block_delta', index: blockIndex,
+          delta: { type: 'text_delta', text: delta.content },
+        });
+      }
+
+      // Handle tool_calls delta
+      if (delta?.tool_calls) {
+        // Close text block before starting tool blocks
+        if (textBlockStarted) {
+          await writeEvent(stream, 'content_block_stop', {
+            type: 'content_block_stop', index: blockIndex,
+          });
+          textBlockStarted = false;
+          blockIndex++;
+        }
+
+        for (const tc of delta.tool_calls) {
+          const idx = tc.index;
+
+          if (tc.id) {
+            // New tool call starting
+            toolCallBuffers[idx] = { id: tc.id, name: tc.function?.name || '', arguments: '' };
+            await writeEvent(stream, 'content_block_start', {
+              type: 'content_block_start', index: blockIndex + idx,
+              content_block: { type: 'tool_use', id: tc.id, name: tc.function?.name || '' },
+            });
+          }
+
+          if (tc.function?.arguments) {
+            toolCallBuffers[idx].arguments += tc.function.arguments;
+            await writeEvent(stream, 'content_block_delta', {
+              type: 'content_block_delta', index: blockIndex + idx,
+              delta: { type: 'input_json_delta', partial_json: tc.function.arguments },
+            });
+          }
+        }
+      }
+
+      // Capture usage from final chunk (requires stream_options.include_usage)
+      if (chunk.usage) {
+        inputTokens = chunk.usage.prompt_tokens || inputTokens;
+        outputTokens = chunk.usage.completion_tokens || outputTokens;
+      }
+    }
+
+    // Close any open text block
+    if (textBlockStarted) {
+      await writeEvent(stream, 'content_block_stop', {
+        type: 'content_block_stop', index: blockIndex,
+      });
+    }
+
+    // Close any open tool call blocks
+    for (const idx of Object.keys(toolCallBuffers)) {
+      await writeEvent(stream, 'content_block_stop', {
+        type: 'content_block_stop', index: blockIndex + Number(idx),
+      });
+    }
+
+    // Send message_delta with final stop_reason and usage
+    await writeEvent(stream, 'message_delta', {
+      type: 'message_delta',
+      delta: { stop_reason: mapStopReason(finishReason, hadStopSequences) },
+      usage: { output_tokens: outputTokens },
+    });
+
+    // Send message_stop
+    await writeEvent(stream, 'message_stop', { type: 'message_stop' });
+  });
+}

vercel.json

@@ -1,6 +1,4 @@
 {
-  "buildCommand": "npm run build",
-  "devCommand": "npm run dev",
   "installCommand": "npm install",
   "framework": null,
   "rewrites": [