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MCP-summarization-functions

by Braffolk
//evals.ts import { EvalConfig } from 'mcp-evals'; import { openai } from "@ai-sdk/openai"; import { grade, EvalFunction } from "mcp-evals"; const summarize_commandEval: EvalFunction = { name: 'summarize_command Evaluation', description: 'Evaluates command execution and output summarization', run: async () => { const result = await grade(openai("gpt-4"), "Please execute the command 'ls -l' in '/usr/bin' and summarize the output if there are too many lines to display."); return JSON.parse(result); } }; const summarize_filesEval: EvalFunction = { name: 'summarize_files Tool Evaluation', description: 'Evaluates the summarize_files tool by asking it to summarize multiple files', run: async () => { const result = await grade(openai("gpt-4"), "Please summarize the contents of README.md and LICENSE from the /usr/src/app directory."); return JSON.parse(result); } }; const summarize_directoryEval: EvalFunction = { name: 'summarize_directoryEval', description: 'Evaluates the directory summarization functionality', run: async () => { const result = await grade(openai("gpt-4"), "Please summarize the structure of the 'src' directory in /User/Documents, including subdirectories. Provide an overview of the folder hierarchy and file counts."); return JSON.parse(result); } }; const summarize_textEval: EvalFunction = { name: 'summarize_textEval', description: 'Evaluates the summarize_text tool by providing text to summarize', run: async () => { const result = await grade(openai("gpt-4"), "Please summarize the following text: 'User log indicates multiple errors in the code during deployment. The content type is log output.'"); return JSON.parse(result); } }; const get_full_contentEval: EvalFunction = { name: 'get_full_content Tool Evaluation', description: 'Evaluates the retrieval of the full content for a given summary ID', run: async () => { const result = await grade(openai("gpt-4"), "Retrieve the full content for summary ID: 12345"); return JSON.parse(result); } }; const config: EvalConfig = { model: openai("gpt-4"), evals: [summarize_commandEval, summarize_filesEval, summarize_directoryEval, summarize_textEval, get_full_contentEval] }; export default config; export const evals = [summarize_commandEval, summarize_filesEval, summarize_directoryEval, summarize_textEval, get_full_contentEval];

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