MCP Puppet Pipeline

import axios from 'axios'; import { CONFIG } from '../config.js'; import { LocalLLMInput, ToolResponse } from '../validation.js'; export async function executeOllamaLLM(input: LocalLLMInput): Promise<ToolResponse> { const { model, prompt, temperature = 0.7, stream = false } = input; try { // Use /api/chat endpoint by default, can be configured via environment const endpoint = process.env.OLLAMA_USE_CHAT === 'false' ? '/api/generate' : '/api/chat'; const url = `${CONFIG.OLLAMA_BASE_URL}${endpoint}`; let requestBody: any; if (endpoint === '/api/chat') { requestBody = { model, messages: [{ role: 'user', content: prompt }], stream, options: { temperature } }; } else { requestBody = { model, prompt, stream, options: { temperature } }; } const startTime = Date.now(); const response = await axios.post(url, requestBody, { timeout: 60000, headers: { 'Content-Type': 'application/json' } }); const latencyMs = Date.now() - startTime; let text: string; if (endpoint === '/api/chat' && response.data.message) { text = response.data.message.content; } else if (response.data.response) { text = response.data.response; } else { throw new Error('Unexpected response format from Ollama'); } const result = { text, model, latencyMs, tokens: response.data.eval_count || 0 }; return { content: [{ type: 'text' as const, text: JSON.stringify(result, null, 2) }] }; } catch (error: any) { const errorMessage = error.response?.data?.error || error.message || 'Unknown error'; return { content: [{ type: 'text' as const, text: `Error calling Ollama: ${errorMessage}` }] }; } }