initiale version

2026-05-10 10:46:41 +02:00
commit deb0d5de9d
10 changed files with 2049 additions and 0 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+node_modules/
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -0,0 +1,30 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+A single-file Express.js proxy (`app.js`) that translates Anthropic API (`/v1/messages`) requests to an Ollama API backend. It enables Claude SDK clients to route through this proxy to a local/remote Ollama instance at `https://ollama.aquantico.de`.
+
+## Running
+
+```bash
+node app.js
+```
+
+The proxy listens on port **11435**. No build step, lint, or test infrastructure exists.
+
+## Key Architecture
+
+- **`app.js`** — Single entry point. All logic is in one file.
+- **`convertAnthropicToOllama()`** — Transforms Anthropic request body into Ollama format: maps system messages, converts content blocks (text + tool_results), sanitizes tool schemas, sets `num_ctx: 131072` and `think: false`.
+- **`handleResponse()`** — Reads Ollama's SSE stream and re-emits it as Anthropic-compatible SSE events (`message_start`, `content_block_start`, `content_block_delta`, `content_block_stop`, `message_delta`, `message_stop`).
+- **`convertAnthropicTools()`** — Strips invalid fields from Anthropic tool schemas and normalizes them to Ollama's function-call format.
+- Model names starting with `claude-` are silently replaced with `qwen3.6:35b-a3b-q4_K_M`.
+
+## Notable Details
+
+- The proxy strips `think` from Ollama requests (hardcoded `false`).
+- Tool call arguments are parsed and sent as a single `partial_json` delta.
+- Request IDs use `Date.now()` for logging correlation.
+- A backup of the previous version is saved as `app.js.v10`.
--- a/app.js
+++ b/app.js
@@ -0,0 +1,451 @@
+// proxy.js - KOMPLETT, mit Tool-Call-Deduplizierung
+
+const express = require('express');
+const app = express();
+
+const colors = {
+  reset: '\x1b[0m',
+  cyan: '\x1b[36m',
+  green: '\x1b[32m',
+  magenta: '\x1b[35m',
+  yellow: '\x1b[33m',
+  blue: '\x1b[34m',
+  red: '\x1b[31m'
+};
+
+app.use(express.json({ limit: '50mb' }));
+
+function sanitizeToolSchema(schema) {
+  if (!schema || typeof schema !== 'object') {
+    return { type: 'object', properties: {} };
+  }
+
+  const clean = JSON.parse(JSON.stringify(schema));
+
+  if (!clean.type) clean.type = 'object';
+  if (!clean.properties) clean.properties = {};
+
+  return clean;
+}
+
+function convertAnthropicTools(anthropicTools) {
+  if (!anthropicTools || anthropicTools.length === 0) return [];
+
+  const validTools = [];
+
+  for (const tool of anthropicTools) {
+    try {
+      const ollamaTool = {
+        type: 'function',
+        function: {
+          name: tool.name,
+          description: (tool.description || '').substring(0, 500),
+          parameters: sanitizeToolSchema(tool.input_schema)
+        }
+      };
+
+      JSON.stringify(ollamaTool);
+      validTools.push(ollamaTool);
+    } catch (e) {
+      console.error(`${colors.red}[Tool Schema Error] ${e.message}${colors.reset}`);
+    }
+  }
+
+  return validTools;
+}
+
+function stringifyToolResultContent(content) {
+  if (Array.isArray(content)) {
+    return content
+      .map(c => {
+        if (typeof c === 'string') return c;
+        if (c?.text) return c.text;
+        return JSON.stringify(c);
+      })
+      .join('\n');
+  }
+
+  if (typeof content === 'string') return content;
+
+  return JSON.stringify(content);
+}
+
+// BUG 3 FIX: tool_use → Ollama tool_calls, tool_result → role:tool
+function convertAnthropicToOllama(anthropicBody) {
+  const ollamaMessages = [];
+
+  if (anthropicBody.system) {
+    ollamaMessages.push({
+      role: 'system',
+      content:
+        typeof anthropicBody.system === 'string'
+          ? anthropicBody.system
+          : JSON.stringify(anthropicBody.system)
+    });
+  }
+
+  for (const msg of anthropicBody.messages || []) {
+    if (typeof msg.content === 'string') {
+      ollamaMessages.push({ role: msg.role, content: msg.content });
+      continue;
+    }
+
+    if (!Array.isArray(msg.content)) continue;
+
+    if (msg.role === 'assistant') {
+      const textParts = [];
+      const toolCalls = [];
+
+      for (const item of msg.content) {
+        if (item.type === 'text') {
+          textParts.push(item.text || '');
+        } else if (item.type === 'tool_use') {
+          toolCalls.push({
+            function: {
+              name: item.name,
+              arguments: item.input || {}
+            }
+          });
+        }
+      }
+
+      const assistantMsg = { role: 'assistant', content: textParts.join('\n\n') };
+      if (toolCalls.length > 0) {
+        assistantMsg.tool_calls = toolCalls;
+      }
+      ollamaMessages.push(assistantMsg);
+
+    } else {
+      // user messages: text bleibt als user, tool_result wird zu role:tool
+      const pendingText = [];
+
+      for (const item of msg.content) {
+        if (item.type === 'text') {
+          pendingText.push(item.text || '');
+        } else if (item.type === 'tool_result') {
+          if (pendingText.length > 0) {
+            ollamaMessages.push({ role: 'user', content: pendingText.join('\n\n') });
+            pendingText.length = 0;
+          }
+
+          const resultText = stringifyToolResultContent(item.content);
+          console.log(`${colors.blue}📥 Tool Result ${item.tool_use_id}:${colors.reset}`);
+          console.log(`${colors.blue}${resultText}${colors.reset}`);
+          console.log('');
+
+          ollamaMessages.push({ role: 'tool', content: resultText });
+        }
+      }
+
+      if (pendingText.length > 0) {
+        ollamaMessages.push({ role: 'user', content: pendingText.join('\n\n') });
+      }
+    }
+  }
+
+  const ollamaBody = {
+    model: anthropicBody.model,
+    messages: ollamaMessages,
+    stream: anthropicBody.stream !== false,
+    think: false,
+    options: {
+      temperature: 0.7,
+      num_predict: anthropicBody.max_tokens || 4096,
+      num_ctx: 262144
+    }
+  };
+
+  if (anthropicBody.tools && anthropicBody.tools.length > 0) {
+    const validTools = convertAnthropicTools(anthropicBody.tools);
+
+    if (validTools.length > 0) {
+      ollamaBody.tools = validTools;
+    }
+  }
+
+  return ollamaBody;
+}
+
+function parseToolArguments(args) {
+  if (!args) return {};
+
+  if (typeof args === 'string') {
+    try {
+      return JSON.parse(args);
+    } catch (e) {
+      console.error(`${colors.red}[Tool Args Parse Error] ${e.message}${colors.reset}`);
+      return {};
+    }
+  }
+
+  if (typeof args === 'object') {
+    return args;
+  }
+
+  return {};
+}
+
+function makeToolDedupeKey(tc) {
+  const name = tc.function?.name || '';
+  const args = tc.function?.arguments || {};
+  const argsString = typeof args === 'string' ? args : JSON.stringify(args);
+
+  return `${name}:${argsString}`;
+}
+
+async function handleResponse(response, anthropicBody, res, requestNum) {
+  res.setHeader('Content-Type', 'text/event-stream');
+  res.setHeader('Cache-Control', 'no-cache');
+  res.setHeader('Connection', 'keep-alive');
+
+  const messageId = 'msg_' + requestNum;
+
+  // BUG 2 FIX: usage.input_tokens und stop_reason hinzugefügt
+  res.write(`event: message_start\ndata: ${JSON.stringify({
+    type: 'message_start',
+    message: {
+      id: messageId,
+      type: 'message',
+      role: 'assistant',
+      content: [],
+      model: anthropicBody.model,
+      stop_reason: null,
+      stop_sequence: null,
+      usage: { input_tokens: 0, output_tokens: 0 }
+    }
+  })}\n\n`);
+
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder();
+
+  let contentBlocks = [];
+  let currentBlockIndex = 0;
+
+  const seenToolCalls = new Set();
+  let emittedToolUse = false;
+  let messageFinished = false;
+  let buffer = '';
+
+  // BUG 1 FIX: Chunk-Verarbeitung als Funktion, damit final buffer ebenfalls verarbeitet wird
+  function processChunk(data) {
+    if (messageFinished) return;
+
+    if (data.message?.tool_calls && data.message.tool_calls.length > 0) {
+      for (const tc of data.message.tool_calls) {
+        const dedupeKey = makeToolDedupeKey(tc);
+
+        if (seenToolCalls.has(dedupeKey)) {
+          console.log(`${colors.yellow}[Duplicate Tool Call skipped] ${dedupeKey}${colors.reset}`);
+          continue;
+        }
+
+        seenToolCalls.add(dedupeKey);
+        emittedToolUse = true;
+
+        const toolName = tc.function?.name;
+        const toolInput = parseToolArguments(tc.function?.arguments);
+        const toolUseId = `toolu_${requestNum}_${currentBlockIndex}`;
+
+        console.log(`${colors.yellow}[Raw Tool Call] ${JSON.stringify(tc)}${colors.reset}`);
+        console.log(`${colors.magenta}[Sending Tool Use: ${toolName}]${colors.reset}`);
+        console.log(`${colors.magenta}Input: ${JSON.stringify(toolInput)}${colors.reset}`);
+
+        res.write(`event: content_block_start\ndata: ${JSON.stringify({
+          type: 'content_block_start',
+          index: currentBlockIndex,
+          content_block: {
+            type: 'tool_use',
+            id: toolUseId,
+            name: toolName,
+            input: {}
+          }
+        })}\n\n`);
+
+        res.write(`event: content_block_delta\ndata: ${JSON.stringify({
+          type: 'content_block_delta',
+          index: currentBlockIndex,
+          delta: {
+            type: 'input_json_delta',
+            partial_json: JSON.stringify(toolInput)
+          }
+        })}\n\n`);
+
+        res.write(`event: content_block_stop\ndata: ${JSON.stringify({
+          type: 'content_block_stop',
+          index: currentBlockIndex
+        })}\n\n`);
+
+        currentBlockIndex++;
+      }
+    }
+
+    if (data.message?.content) {
+      const text = data.message.content;
+
+      if (contentBlocks[currentBlockIndex] === undefined) {
+        res.write(`event: content_block_start\ndata: ${JSON.stringify({
+          type: 'content_block_start',
+          index: currentBlockIndex,
+          content_block: {
+            type: 'text',
+            text: ''
+          }
+        })}\n\n`);
+
+        contentBlocks[currentBlockIndex] = '';
+      }
+
+      process.stdout.write(`${colors.green}${text}${colors.reset}`);
+
+      res.write(`event: content_block_delta\ndata: ${JSON.stringify({
+        type: 'content_block_delta',
+        index: currentBlockIndex,
+        delta: {
+          type: 'text_delta',
+          text
+        }
+      })}\n\n`);
+
+      contentBlocks[currentBlockIndex] += text;
+    }
+
+    if (data.done) {
+      messageFinished = true;
+
+      if (contentBlocks[currentBlockIndex] !== undefined) {
+        res.write(`event: content_block_stop\ndata: ${JSON.stringify({
+          type: 'content_block_stop',
+          index: currentBlockIndex
+        })}\n\n`);
+      }
+
+      res.write(`event: message_delta\ndata: ${JSON.stringify({
+        type: 'message_delta',
+        delta: {
+          stop_reason: emittedToolUse ? 'tool_use' : 'end_turn'
+        },
+        usage: {
+          output_tokens: data.eval_count || 0
+        }
+      })}\n\n`);
+
+      res.write(`event: message_stop\ndata: ${JSON.stringify({
+        type: 'message_stop'
+      })}\n\n`);
+
+      console.log(`${colors.green}✓${colors.reset}\n`);
+    }
+  }
+
+  while (true) {
+    const { done, value } = await reader.read();
+    if (done) break;
+
+    buffer += decoder.decode(value, { stream: true });
+
+    const lines = buffer.split('\n');
+    buffer = lines.pop() || '';
+
+    for (const line of lines) {
+      const trimmed = line.trim();
+      if (!trimmed) continue;
+
+      try {
+        processChunk(JSON.parse(trimmed));
+      } catch (e) {
+        console.error(`${colors.red}[Stream Parse Error] ${e.message}${colors.reset}`);
+        console.error(`${colors.red}${line}${colors.reset}`);
+      }
+    }
+  }
+
+  // BUG 1 FIX: letzten gepufferten Chunk verarbeiten (kein \n am Ende)
+  if (buffer.trim()) {
+    try {
+      processChunk(JSON.parse(buffer.trim()));
+    } catch (e) {
+      console.error(`${colors.red}[Final Buffer Parse Error] ${e.message}${colors.reset}`);
+      console.error(buffer);
+    }
+  }
+
+  if (!messageFinished) {
+    if (contentBlocks[currentBlockIndex] !== undefined) {
+      res.write(`event: content_block_stop\ndata: ${JSON.stringify({
+        type: 'content_block_stop',
+        index: currentBlockIndex
+      })}\n\n`);
+    }
+
+    res.write(`event: message_delta\ndata: ${JSON.stringify({
+      type: 'message_delta',
+      delta: {
+        stop_reason: emittedToolUse ? 'tool_use' : 'end_turn'
+      },
+      usage: {
+        output_tokens: 0
+      }
+    })}\n\n`);
+
+    res.write(`event: message_stop\ndata: ${JSON.stringify({
+      type: 'message_stop'
+    })}\n\n`);
+  }
+
+  res.end();
+}
+
+app.post('/v1/messages', async (req, res) => {
+  const requestNum = Date.now();
+
+  console.log(`${colors.magenta}━━━ #${requestNum} ━━━${colors.reset}`);
+
+  try {
+    const anthropicBody = req.body;
+
+    if (anthropicBody.model?.startsWith('claude-')) {
+      anthropicBody.model = 'qwen3.6:35b-a3b-q4_K_M';
+    }
+
+    const ollamaBody = convertAnthropicToOllama(anthropicBody);
+
+    console.log(
+      `${colors.magenta}[msgs=${ollamaBody.messages.length}, tools=${ollamaBody.tools?.length || 0}, ctx=256k, think=false]${colors.reset}`
+    );
+
+    const response = await fetch('https://ollama.aquantico.de/api/chat', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        'Authorization': 'Bearer 324GF44-50AA-4B57-9386-K435DLJ764DFR'
+      },
+      body: JSON.stringify(ollamaBody)
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      console.error(`${colors.red}${errorText}${colors.reset}`);
+      throw new Error(`Ollama: ${response.status}`);
+    }
+
+    return handleResponse(response, anthropicBody, res, requestNum);
+  } catch (error) {
+    console.error(`${colors.red}${error.message}${colors.reset}`);
+
+    if (!res.headersSent) {
+      res.status(500).json({
+        type: 'error',
+        error: {
+          type: 'api_error',
+          message: error.message
+        }
+      });
+    } else {
+      res.end();
+    }
+  }
+});
+
+app.listen(11435, () => {
+  console.log(`${colors.magenta}Proxy: localhost:11435 (256k ctx, think=false)${colors.reset}\n`);
+});
--- a/app.js.v10
+++ b/app.js.v10
@@ -0,0 +1,290 @@
+// proxy.js - KOMPLETT
+const express = require('express');
+const app = express();
+
+const colors = {
+  reset: '\x1b[0m',
+  cyan: '\x1b[36m',
+  green: '\x1b[32m',
+  magenta: '\x1b[35m',
+  yellow: '\x1b[33m',
+  blue: '\x1b[34m',
+  red: '\x1b[31m'
+};
+
+app.use(express.json({ limit: '50mb' }));
+
+function sanitizeToolSchema(schema) {
+  if (!schema || typeof schema !== 'object') {
+    return { type: 'object', properties: {} };
+  }
+  const clean = JSON.parse(JSON.stringify(schema));
+  if (!clean.type) clean.type = 'object';
+  if (!clean.properties) clean.properties = {};
+  return clean;
+}
+
+function convertAnthropicTools(anthropicTools) {
+  if (!anthropicTools || anthropicTools.length === 0) return [];
+  
+  const validTools = [];
+  for (const tool of anthropicTools) {
+    try {
+      const ollamaTool = {
+        type: 'function',
+        function: {
+          name: tool.name,
+          description: (tool.description || '').substring(0, 500),
+          parameters: sanitizeToolSchema(tool.input_schema)
+        }
+      };
+      JSON.stringify(ollamaTool);
+      validTools.push(ollamaTool);
+    } catch (e) {}
+  }
+  
+  console.log(`${colors.yellow}Tools: ${validTools.length}${colors.reset}`);
+  return validTools;
+}
+
+function convertAnthropicToOllama(anthropicBody) {
+  const ollamaMessages = [];
+  
+  if (anthropicBody.system) {
+    ollamaMessages.push({
+      role: 'system',
+      content: typeof anthropicBody.system === 'string' 
+        ? anthropicBody.system 
+        : JSON.stringify(anthropicBody.system)
+    });
+  }
+  
+  for (const msg of anthropicBody.messages) {
+    if (typeof msg.content === 'string') {
+      ollamaMessages.push({ role: msg.role, content: msg.content });
+    } else if (Array.isArray(msg.content)) {
+      const parts = [];
+      
+      for (const item of msg.content) {
+        if (item.type === 'text') {
+          parts.push(item.text);
+        } else if (item.type === 'tool_result') {
+          const resultText = Array.isArray(item.content) 
+            ? item.content.map(c => c.text || JSON.stringify(c)).join('\n')
+            : typeof item.content === 'string' ? item.content : JSON.stringify(item.content);
+          
+          console.log(`${colors.blue}📥 ${item.tool_use_id}:${colors.reset}`);
+          console.log(`${colors.blue}${resultText}${colors.reset}`);
+          console.log('');
+          
+          parts.push(`Tool Result (${item.tool_use_id}):\n${resultText}`);
+        }
+      }
+      
+      if (parts.length > 0) {
+        ollamaMessages.push({ role: msg.role, content: parts.join('\n\n') });
+      }
+    }
+  }
+  
+  const ollamaBody = {
+    model: anthropicBody.model,
+    messages: ollamaMessages,
+    stream: anthropicBody.stream !== false,
+    think: false,  // AUF TOP-LEVEL!
+    options: { 
+      temperature: 0.7,
+      num_predict: anthropicBody.max_tokens || 4096,
+      num_ctx: 131072
+    }
+  };
+  
+  if (anthropicBody.tools && anthropicBody.tools.length > 0) {
+    const validTools = convertAnthropicTools(anthropicBody.tools);
+    if (validTools.length > 0) {
+      ollamaBody.tools = validTools;
+    }
+  }
+  
+  return ollamaBody;
+}
+
+async function handleResponse(response, anthropicBody, res, requestNum) {
+  res.setHeader('Content-Type', 'text/event-stream');
+  
+  const messageId = 'msg_' + requestNum;
+  
+  res.write(`event: message_start\ndata: ${JSON.stringify({
+    type: 'message_start',
+    message: { id: messageId, type: 'message', role: 'assistant', content: [], model: anthropicBody.model }
+  })}\n\n`);
+  
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder();
+  
+  let contentBlocks = [];
+  let currentBlockIndex = 0;
+  
+  while (true) {
+    const { done, value } = await reader.read();
+    if (done) break;
+    
+    const chunk = decoder.decode(value, { stream: true });
+    const lines = chunk.split('\n').filter(line => line.trim());
+    
+    for (const line of lines) {
+      try {
+        const data = JSON.parse(line);
+        
+        console.log(`${colors.cyan}[Ollama Response] ${JSON.stringify(data).substring(0, 200)}${colors.reset}`);
+        
+        if (data.message?.tool_calls && data.message.tool_calls.length > 0) {
+  for (const tc of data.message.tool_calls) {
+    console.log(`${colors.yellow}[Raw Tool Call] ${JSON.stringify(tc)}${colors.reset}`);
+    
+    let toolInput = {};
+    
+    if (typeof tc.function.arguments === 'string') {
+      try {
+        toolInput = JSON.parse(tc.function.arguments);
+      } catch (e) {
+        console.error(`${colors.red}Parse error: ${e.message}${colors.reset}`);
+      }
+    } else if (typeof tc.function.arguments === 'object') {
+      toolInput = tc.function.arguments;
+    }
+    
+    const toolUseId = `toolu_${requestNum}_${currentBlockIndex}`;
+    
+    console.log(`${colors.magenta}[Sending Tool Use: ${tc.function.name}]${colors.reset}`);
+    console.log(`${colors.magenta}Input: ${JSON.stringify(toolInput)}${colors.reset}`);
+    
+    // 1. content_block_start mit LEEREM Input
+    res.write(`event: content_block_start\ndata: ${JSON.stringify({
+      type: 'content_block_start',
+      index: currentBlockIndex,
+      content_block: {
+        type: 'tool_use',
+        id: toolUseId,
+        name: tc.function.name,
+        input: {}  // LEER - wird über Delta gesendet!
+      }
+    })}\n\n`);
+    
+    // 2. Input als Delta senden
+    const inputJson = JSON.stringify(toolInput);
+    res.write(`event: content_block_delta\ndata: ${JSON.stringify({
+      type: 'content_block_delta',
+      index: currentBlockIndex,
+      delta: {
+        type: 'input_json_delta',
+        partial_json: inputJson
+      }
+    })}\n\n`);
+    
+    // 3. content_block_stop
+    res.write(`event: content_block_stop\ndata: ${JSON.stringify({
+      type: 'content_block_stop',
+      index: currentBlockIndex
+    })}\n\n`);
+    
+    currentBlockIndex++;
+  }
+}
+        
+        if (data.message?.content) {
+          const text = data.message.content;
+          
+          if (contentBlocks[currentBlockIndex] === undefined) {
+            res.write(`event: content_block_start\ndata: ${JSON.stringify({
+              type: 'content_block_start',
+              index: currentBlockIndex,
+              content_block: { type: 'text', text: '' }
+            })}\n\n`);
+            contentBlocks[currentBlockIndex] = '';
+          }
+          
+          process.stdout.write(`${colors.green}${text}${colors.reset}`);
+          
+          res.write(`event: content_block_delta\ndata: ${JSON.stringify({
+            type: 'content_block_delta',
+            index: currentBlockIndex,
+            delta: { type: 'text_delta', text: text }
+          })}\n\n`);
+          
+          contentBlocks[currentBlockIndex] += text;
+        }
+        
+        if (data.done) {
+          if (contentBlocks[currentBlockIndex] !== undefined) {
+            res.write(`event: content_block_stop\ndata: ${JSON.stringify({
+              type: 'content_block_stop',
+              index: currentBlockIndex
+            })}\n\n`);
+          }
+          
+          res.write(`event: message_delta\ndata: ${JSON.stringify({
+            type: 'message_delta',
+            delta: { stop_reason: 'end_turn' },
+            usage: { output_tokens: data.eval_count || 0 }
+          })}\n\n`);
+          
+          res.write(`event: message_stop\ndata: ${JSON.stringify({
+            type: 'message_stop'
+          })}\n\n`);
+          
+          console.log(`${colors.green}✓${colors.reset}\n`);
+        }
+      } catch (e) {
+        console.error(`${colors.red}Error: ${e.message}${colors.reset}`);
+      }
+    }
+  }
+  
+  res.end();
+}
+
+app.post('/v1/messages', async (req, res) => {
+  const requestNum = Date.now();
+  console.log(`${colors.magenta}━━━ #${requestNum} ━━━${colors.reset}`);
+  
+  try {
+    const anthropicBody = req.body;
+    
+    if (anthropicBody.model?.startsWith('claude-')) {
+      anthropicBody.model = 'qwen3.6:35b-a3b-q4_K_M';
+    }
+    
+    const ollamaBody = convertAnthropicToOllama(anthropicBody);
+    
+    console.log(`${colors.magenta}[msgs=${ollamaBody.messages.length}, tools=${ollamaBody.tools?.length || 0}, ctx=128k, think=false]${colors.reset}`);
+    
+    const response = await fetch('https://ollama.aquantico.de/api/chat', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        'Authorization': 'Bearer 324GF44-50AA-4B57-9386-K435DLJ764DFR'
+      },
+      body: JSON.stringify(ollamaBody)
+    });
+    
+    if (!response.ok) {
+      const errorText = await response.text();
+      console.error(`${colors.red}${errorText}${colors.reset}`);
+      throw new Error(`Ollama: ${response.status}`);
+    }
+    
+    return handleResponse(response, anthropicBody, res, requestNum);
+    
+  } catch (error) {
+    console.error(`${colors.red}${error.message}${colors.reset}`);
+    res.status(500).json({
+      type: 'error',
+      error: { type: 'api_error', message: error.message }
+    });
+  }
+});
+
+app.listen(11435, () => {
+  console.log(`${colors.magenta}Proxy: localhost:11435 (128k ctx, think=false)${colors.reset}\n`);
+});
--- a/claude-via-proxy.sh
+++ b/claude-via-proxy.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+# Claude Code über lokalen noThinkProxy starten
+# Voraussetzung: Proxy läuft bereits auf localhost:11435
+
+export ANTHROPIC_BASE_URL=http://localhost:11435
+
+exec claude "$@"
--- a/doc/anthropic-api.md
+++ b/doc/anthropic-api.md
@@ -0,0 +1,164 @@
+# Anthropic Messages API
+
+Endpoint: `POST /v1/messages`
+Docs: https://docs.anthropic.com/en/api/messages
+
+## Request
+
+```json
+{
+  "model":         "claude-opus-4-7",
+  "max_tokens":    4096,
+  "messages": [
+    {
+      "role": "user",
+      "content": "string  OR  array of content blocks"
+    }
+  ],
+  "system":        "string  OR  array of system blocks",
+  "temperature":   0.7,
+  "stop_sequences": ["---"],
+  "tools": [
+    {
+      "name":        "tool_name",
+      "description": "What this tool does",
+      "input_schema": {
+        "type": "object",
+        "properties": {
+          "param": { "type": "string", "description": "..." }
+        },
+        "required": ["param"]
+      }
+    }
+  ],
+  "tool_choice": { "type": "auto" },
+  "stream": true
+}
+```
+
+### Fields
+
+| Field            | Type         | Required | Notes                                             |
+|------------------|--------------|----------|---------------------------------------------------|
+| `model`          | string       | Yes      | e.g. `claude-opus-4-7`, `claude-sonnet-4-6`       |
+| `max_tokens`     | number       | Yes      | Max output tokens                                 |
+| `messages`       | array        | Yes      | `role: user|assistant`                            |
+| `system`         | string/array | No       | System prompt (separate from messages)            |
+| `temperature`    | number       | No       | 0.0–1.0                                           |
+| `stop_sequences` | array        | No       | Strings that stop generation                      |
+| `tools`          | array        | No       | Tool definitions with `input_schema` (JSON Schema)|
+| `tool_choice`    | object       | No       | `{ type: "auto|any|tool", name?: "..." }`         |
+| `stream`         | boolean      | No       | Enable SSE streaming                              |
+
+## Message Content Types
+
+```json
+{ "type": "text",        "text": "string" }
+{ "type": "image",       "source": { "type": "base64", "media_type": "image/jpeg", "data": "..." } }
+{ "type": "tool_use",    "id": "toolu_abc", "name": "tool_name", "input": {} }
+{ "type": "tool_result", "tool_use_id": "toolu_abc", "content": "result string or array" }
+```
+
+## Streaming SSE Events
+
+SSE format: each event is two lines `event: <type>\ndata: <json>` followed by blank line.
+
+### Event Order
+
+1. `message_start`
+2. For each content block: `content_block_start` → N× `content_block_delta` → `content_block_stop`
+3. `message_delta`
+4. `message_stop`
+
+Interspersed `ping` events may appear at any time.
+
+### message_start
+
+```json
+{
+  "type": "message_start",
+  "message": {
+    "id":    "msg_01XFDUDYJgAACzvnptvVoYEL",
+    "type":  "message",
+    "role":  "assistant",
+    "model": "claude-opus-4-7",
+    "content": [],
+    "stop_reason":   null,
+    "stop_sequence": null,
+    "usage": { "input_tokens": 25, "output_tokens": 1 }
+  }
+}
+```
+
+### content_block_start
+
+```json
+{ "type": "content_block_start", "index": 0,
+  "content_block": { "type": "text", "text": "" } }
+
+{ "type": "content_block_start", "index": 1,
+  "content_block": { "type": "tool_use", "id": "toolu_abc", "name": "get_weather", "input": {} } }
+```
+
+### content_block_delta
+
+```json
+{ "type": "content_block_delta", "index": 0,
+  "delta": { "type": "text_delta",       "text": "Hello" } }
+
+{ "type": "content_block_delta", "index": 1,
+  "delta": { "type": "input_json_delta", "partial_json": "{\"loc" } }
+```
+
+### content_block_stop
+
+```json
+{ "type": "content_block_stop", "index": 0 }
+```
+
+### message_delta
+
+```json
+{
+  "type": "message_delta",
+  "delta": {
+    "stop_reason":   "end_turn",
+    "stop_sequence": null
+  },
+  "usage": { "output_tokens": 15 }
+}
+```
+
+`stop_reason` values: `end_turn` | `stop_sequence` | `max_tokens` | `tool_use`
+
+### message_stop
+
+```json
+{ "type": "message_stop" }
+```
+
+## Non-Streaming Response
+
+```json
+{
+  "id":   "msg_abc",
+  "type": "message",
+  "role": "assistant",
+  "model": "claude-opus-4-7",
+  "content": [
+    { "type": "text", "text": "Hello!" },
+    { "type": "tool_use", "id": "toolu_abc", "name": "get_weather", "input": { "location": "Berlin" } }
+  ],
+  "stop_reason":   "tool_use",
+  "stop_sequence": null,
+  "usage": { "input_tokens": 100, "output_tokens": 50 }
+}
+```
+
+## Tool Flow
+
+1. Send request with `tools` array
+2. Model responds with `stop_reason: "tool_use"` and `content` block of `type: "tool_use"`
+3. Execute the tool locally
+4. Send next user message with `type: "tool_result"` content block referencing `tool_use_id`
+5. Continue until `stop_reason: "end_turn"`
--- a/doc/ollama-api.md
+++ b/doc/ollama-api.md
@@ -0,0 +1,125 @@
+# Ollama Chat API
+
+Endpoint: `POST /api/chat`
+
+## Request
+
+```json
+{
+  "model": "llama3.2",
+  "messages": [
+    { "role": "system",    "content": "string" },
+    { "role": "user",      "content": "string" },
+    { "role": "assistant", "content": "string" },
+    { "role": "tool",      "content": "string" }
+  ],
+  "tools": [
+    {
+      "type": "function",
+      "function": {
+        "name": "string",
+        "description": "string",
+        "parameters": {
+          "type": "object",
+          "properties": { "param": { "type": "string", "description": "..." } },
+          "required": ["param"]
+        }
+      }
+    }
+  ],
+  "think":     false,
+  "format":    "json",
+  "stream":    true,
+  "keep_alive": "5m",
+  "options": {
+    "temperature": 0.7,
+    "num_ctx":     131072,
+    "num_predict": 4096
+  }
+}
+```
+
+### Fields
+
+| Field        | Type    | Required | Notes                                          |
+|--------------|---------|----------|------------------------------------------------|
+| `model`      | string  | Yes      | Model name (e.g. `qwen3.6:35b-a3b-q4_K_M`)   |
+| `messages`   | array   | Yes      | Conversation history                           |
+| `tools`      | array   | No       | Function definitions (OpenAI-compatible format)|
+| `think`      | boolean | No       | Enable chain-of-thought (thinking models only) |
+| `format`     | string  | No       | `"json"` or JSON schema for structured output  |
+| `stream`     | boolean | No       | Default: `true`                                |
+| `keep_alive` | string  | No       | How long to keep model loaded. Default: `5m`   |
+| `options`    | object  | No       | Model runtime parameters                       |
+
+## Streaming Response (NDJSON)
+
+Each line is a standalone JSON object:
+
+```json
+{ "model": "...", "message": { "role": "assistant", "content": "partial text" }, "done": false }
+```
+
+Final line (done):
+```json
+{
+  "model": "...",
+  "message": { "role": "assistant", "content": "" },
+  "done": true,
+  "done_reason": "stop",
+  "total_duration":      1234567890,
+  "load_duration":       987654321,
+  "prompt_eval_count":   50,
+  "eval_count":          200,
+  "eval_duration":       12345678
+}
+```
+
+### Tool Call Response
+
+When the model decides to use a tool, `message.tool_calls` is set (content is empty/null):
+
+```json
+{
+  "model": "...",
+  "message": {
+    "role": "assistant",
+    "content": "",
+    "tool_calls": [
+      {
+        "function": {
+          "name": "get_weather",
+          "arguments": { "location": "Berlin", "unit": "celsius" }
+        }
+      }
+    ]
+  },
+  "done": false
+}
+```
+
+Note: `tool_calls[].function.arguments` is an **object** (already parsed JSON), not a string.
+
+### done_reason Values
+
+| Value         | Meaning                          |
+|---------------|----------------------------------|
+| `stop`        | Natural end of generation        |
+| `tool_calls`  | Model triggered a tool call      |
+| `load`        | Model was loaded                 |
+| `unload`      | Model was unloaded               |
+
+## Tool Result Message
+
+After receiving a tool call, send result as role `tool`:
+
+```json
+{
+  "role": "tool",
+  "content": "result text or JSON string"
+}
+```
+
+## Non-Streaming Response
+
+Single JSON object with all fields combined (same structure as final streaming line).
--- a/doc/proxy-analysis.md
+++ b/doc/proxy-analysis.md
@@ -0,0 +1,131 @@
+# Proxy Implementierungsanalyse
+
+## Was der Proxy macht
+
+Übersetzt **Anthropic API** (`POST /v1/messages`) → **Ollama API** (`POST /api/chat`)
+
+- Empfängt Anthropic SSE-Format
+- Gibt Anthropic SSE-Format zurück
+- Routing: `localhost:11435` → `https://ollama.aquantico.de/api/chat`
+
+---
+
+## Korrekte Implementierungen ✓
+
+### 1. Model-Substitution (korrekt)
+```js
+if (anthropicBody.model?.startsWith('claude-')) {
+  anthropicBody.model = 'qwen3.6:35b-a3b-q4_K_M';
+}
+```
+Alle `claude-*` Modelle werden durch das lokale Modell ersetzt.
+
+### 2. Think-Modus deaktiviert (korrekt)
+```js
+think: false
+```
+Hardcoded in `convertAnthropicToOllama()`.
+
+### 3. Tool-Schema-Konvertierung (korrekt)
+Anthropic `input_schema` → Ollama `function.parameters`:
+```js
+{ type: 'function', function: { name, description, parameters: sanitizeToolSchema(tool.input_schema) } }
+```
+
+### 4. Tool-Call-Parsing in Response (korrekt)
+Ollama gibt `tc.function.name` und `tc.function.arguments` zurück — genau das liest der Proxy:
+```js
+const toolName  = tc.function?.name;
+const toolInput = parseToolArguments(tc.function?.arguments);
+```
+
+### 5. SSE-Event-Sequenz (korrekt)
+Ausgabe entspricht Anthropic-Spec:
+`message_start` → `content_block_start` → `content_block_delta` → `content_block_stop` → `message_delta` → `message_stop`
+
+### 6. stop_reason (korrekt)
+```js
+stop_reason: emittedToolUse ? 'tool_use' : 'end_turn'
+```
+
+### 7. Tool-Deduplizierung (korrekt)
+Verhindert doppelte Tool-Calls via `seenToolCalls` Set mit Key `name:args`.
+
+---
+
+## Bekannte Bugs / Schwachstellen ⚠️
+
+### BUG 1: Leerer finaler Buffer-Handler (app.js:350-358)
+
+```js
+if (buffer.trim()) {
+  try {
+    const data = JSON.parse(buffer.trim());
+    // gleichen Handling-Code wie oben ausführen  ← LEER, nie ausgeführt!
+  } catch (e) { ... }
+}
+```
+
+**Problem**: Wenn das letzte NDJSON-Chunk von Ollama nicht mit `\n` endet (was bei einigen Ollama-Versionen vorkommt), bleibt die finale `done: true`-Zeile im Buffer und wird nicht verarbeitet.
+
+**Auswirkung**: `messageFinished` bleibt `false`, Fallback-Code (Zeile 360-381) sendet die Abschluss-Events ohne `eval_count` (output_tokens=0).
+
+**Fix**: Den gleichen Parsing-Code aus der while-Schleife in den finalen Buffer-Handler kopieren.
+
+### BUG 2: message_start ohne usage.input_tokens (app.js:200-209)
+
+```js
+res.write(`event: message_start\ndata: ${JSON.stringify({
+  type: 'message_start',
+  message: {
+    id: messageId, type: 'message', role: 'assistant', content: [],
+    model: anthropicBody.model
+    // fehlt: stop_reason: null, usage: { input_tokens: 0, output_tokens: 0 }
+  }
+})}\n\n`);
+```
+
+**Auswirkung**: Anthropic-kompatible Clients erwarten `usage.input_tokens` in `message_start`. Kann bei strikten Clients zu Parse-Fehlern führen.
+
+### BUG 3: tool_use/tool_result als Text im Nachrichten-Verlauf
+
+Wenn Anthropic-Clients `tool_use` (in Assistant-Nachrichten) und `tool_result` (in User-Nachrichten) im History senden, werden diese als Text-Strings in den Ollama-Messages eingebettet:
+
+```
+"Previous assistant tool call already made.\nTool name: ...\n..."
+```
+
+**Korrekt wäre**: Assistant-Nachrichten mit `tool_calls` senden, Tool-Results als `role: "tool"` Nachricht.
+
+**Auswirkung**: Das Modell versteht den Tool-Call-Verlauf semantisch nicht korrekt. Die bestehende Deduplizierungs-Logik kompensiert dies teilweise.
+
+---
+
+## Architektur-Übersicht
+
+```
+Client (Claude SDK)
+    │  POST /v1/messages (Anthropic Format)
+    ▼
+noThinkProxy :11435
+    │  convertAnthropicToOllama()
+    │  - system → messages[0] role:system
+    │  - tool_use → text string
+    │  - tool_result → text string
+    │  - model: claude-* → qwen3.6:35b-a3b-q4_K_M
+    │  - think: false
+    │  - options: { num_ctx:131072, num_predict, temperature:0.7 }
+    │
+    │  POST /api/chat (Ollama NDJSON)
+    ▼
+Ollama https://ollama.aquantico.de
+    │  NDJSON stream: {message:{content, tool_calls}, done}
+    ▼
+noThinkProxy
+    │  handleResponse()
+    │  - text → content_block_delta (text_delta)
+    │  - tool_calls → content_block_start/delta/stop (tool_use)
+    │  - done → message_delta + message_stop
+    ▼
+Client (Anthropic SSE)
+```
--- a/package-lock.json
+++ b/package-lock.json
@@ -0,0 +1,844 @@
+{
+  "name": "noThinkProxy",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "dependencies": {
+        "express": "^5.2.1",
+        "node-fetch": "^3.3.2"
+      }
+    },
+    "node_modules/accepts": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/accepts/-/accepts-2.0.0.tgz",
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+      "dependencies": {
+        "mime-types": "^3.0.0",
+        "negotiator": "^1.0.0"
+      },
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
+    "node_modules/body-parser": {
+      "version": "2.2.2",
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+      "dependencies": {
+        "bytes": "^3.1.2",
+        "content-type": "^1.0.5",
+        "debug": "^4.4.3",
+        "http-errors": "^2.0.0",
+        "iconv-lite": "^0.7.0",
+        "on-finished": "^2.4.1",
+        "qs": "^6.14.1",
+        "raw-body": "^3.0.1",
+        "type-is": "^2.0.1"
+      },
+      "engines": {
+        "node": ">=18"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/express"
+      }
+    },
+    "node_modules/bytes": {
+      "version": "3.1.2",
+      "resolved": "https://registry.npmjs.org/bytes/-/bytes-3.1.2.tgz",
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+      "engines": {
+        "node": ">= 0.8"
+      }
+    },
+    "node_modules/call-bind-apply-helpers": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/call-bind-apply-helpers/-/call-bind-apply-helpers-1.0.2.tgz",
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+      "dependencies": {
+        "es-errors": "^1.3.0",
+        "function-bind": "^1.1.2"
+      },
+      "engines": {
+        "node": ">= 0.4"
+      }
+    },
+    "node_modules/call-bound": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/call-bound/-/call-bound-1.0.4.tgz",
+      "integrity": "sha512-+ys997U96po4Kx/ABpBCqhA9EuxJaQWDQg7295H4hBphv3IZg0boBKuwYpt4YXp6MZ5AmZQnU/tyMTlRpaSejg==",
+      "dependencies": {
+        "call-bind-apply-helpers": "^1.0.2",
+        "get-intrinsic": "^1.3.0"
+      },
+      "engines": {
+        "node": ">= 0.4"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/ljharb"
+      }
+    },
+    "node_modules/content-disposition": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/content-disposition/-/content-disposition-1.1.0.tgz",
+      "integrity": "sha512-5jRCH9Z/+DRP7rkvY83B+yGIGX96OYdJmzngqnw2SBSxqCFPd0w2km3s5iawpGX8krnwSGmF0FW5Nhr0Hfai3g==",
+      "engines": {
+        "node": ">=18"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/express"
+      }
+    },
+    "node_modules/content-type": {
+      "version": "1.0.5",
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+      "engines": {
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+    "node_modules/cookie-signature": {
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+      "resolved": "https://registry.npmjs.org/cookie-signature/-/cookie-signature-1.2.2.tgz",
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+      "engines": {
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+}
--- a/package.json
+++ b/package.json
@@ -0,0 +1,6 @@
+{
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+    "express": "^5.2.1",
+    "node-fetch": "^3.3.2"
+  }
+}