commit deb0d5de9d72a1cee75093aed75affa9b5caa34c Author: Wolf G. Beckmann Date: Sun May 10 10:46:41 2026 +0200 initiale version diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..c2658d7 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +node_modules/ diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000..006524b --- /dev/null +++ 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`. diff --git a/app.js b/app.js new file mode 100644 index 0000000..185c213 --- /dev/null +++ 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`); +}); diff --git a/app.js.v10 b/app.js.v10 new file mode 100644 index 0000000..1bcfcd6 --- /dev/null +++ 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`); +}); \ No newline at end of file diff --git a/claude-via-proxy.sh b/claude-via-proxy.sh new file mode 100755 index 0000000..1c219cb --- /dev/null +++ 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 "$@" diff --git a/doc/anthropic-api.md b/doc/anthropic-api.md new file mode 100644 index 0000000..09195d6 --- /dev/null +++ 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: \ndata: ` 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"` diff --git a/doc/ollama-api.md b/doc/ollama-api.md new file mode 100644 index 0000000..a5f966a --- /dev/null +++ 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). diff --git a/doc/proxy-analysis.md b/doc/proxy-analysis.md new file mode 100644 index 0000000..3598f3e --- /dev/null +++ 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) +``` diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000..f6529bc --- /dev/null +++ b/package-lock.json @@ -0,0 +1,844 @@ +{ + "name": "noThinkProxy", + 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