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4bb12e05ef |
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benchmarks/tool_call_benchmark.py
Executable file
461
benchmarks/tool_call_benchmark.py
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#!/usr/bin/env python3
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"""
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tool_call_benchmark.py — Benchmark Gemma 4 tool calling vs mimo-v2-pro.
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Runs 100 diverse tool calling prompts through each model and compares:
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- Schema parse success rate
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- Tool execution success rate
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- Parallel tool call success rate
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- Average latency
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- Token cost per call
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Usage:
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python3 benchmarks/tool_call_benchmark.py --model1 gemma3:27b --model2 xiaomi/mimo-v2-pro
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python3 benchmarks/tool_call_benchmark.py --model1 gemma3:27b --limit 10 # quick test
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python3 benchmarks/tool_call_benchmark.py --output benchmarks/results.json
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Requires:
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- Ollama running locally (or --endpoint for remote)
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- Models pulled: ollama pull gemma3:27b, etc.
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"""
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import json
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import os
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import sys
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import time
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import urllib.request
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import urllib.error
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from datetime import datetime, timezone
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from pathlib import Path
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from dataclasses import dataclass, field, asdict
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from typing import List, Dict, Optional
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ENDPOINT = os.environ.get("OPENAI_BASE_URL", "http://localhost:11434/v1")
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API_KEY = os.environ.get("OPENAI_API_KEY", "ollama")
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# ── Tool schemas (subset for benchmarking) ──────────────────────────────
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TOOL_SCHEMAS = [
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{
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"type": "function",
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"function": {
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"name": "read_file",
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"description": "Read a text file",
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"parameters": {
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "File path"},
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"offset": {"type": "integer", "description": "Start line"},
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"limit": {"type": "integer", "description": "Max lines"}
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},
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"required": ["path"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "terminal",
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"description": "Execute a shell command",
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"parameters": {
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"type": "object",
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"properties": {
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"command": {"type": "string", "description": "Shell command"}
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},
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"required": ["command"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "write_file",
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"description": "Write content to a file",
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"parameters": {
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"type": "object",
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"properties": {
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"path": {"type": "string"},
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"content": {"type": "string"}
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},
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"required": ["path", "content"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "search_files",
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"description": "Search for content in files",
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"parameters": {
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"type": "object",
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"properties": {
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"pattern": {"type": "string"},
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"path": {"type": "string"}
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},
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"required": ["pattern"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "web_search",
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"description": "Search the web",
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"parameters": {
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"type": "object",
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"properties": {
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"query": {"type": "string"}
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},
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"required": ["query"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "execute_code",
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"description": "Execute Python code",
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"parameters": {
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"type": "object",
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"properties": {
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"code": {"type": "string"}
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},
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"required": ["code"]
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}
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}
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},
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]
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SYSTEM_PROMPT = "You are a helpful assistant with access to tools. Use tools when needed."
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# ── Test prompts (100 diverse tool calling scenarios) ────────────────────
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TEST_PROMPTS = [
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# File operations (20)
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("Read the README.md file", "read_file", "file_ops"),
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("Show me the contents of config.yaml", "read_file", "file_ops"),
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("Read lines 10-20 of main.py", "read_file", "file_ops"),
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("Open the package.json", "read_file", "file_ops"),
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("Read the .gitignore file", "read_file", "file_ops"),
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("Save this to notes.txt: meeting at 3pm", "write_file", "file_ops"),
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("Create a new file hello.py with print hello", "write_file", "file_ops"),
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("Write the config to settings.json", "write_file", "file_ops"),
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("Save the output to results.txt", "write_file", "file_ops"),
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("Create TODO.md with my tasks", "write_file", "file_ops"),
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("Search for 'import os' in the codebase", "search_files", "file_ops"),
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("Find all Python files mentioning 'error'", "search_files", "file_ops"),
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("Search for TODO comments", "search_files", "file_ops"),
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("Find where 'authenticate' is defined", "search_files", "file_ops"),
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("Look for any hardcoded API keys", "search_files", "file_ops"),
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("Read the Makefile", "read_file", "file_ops"),
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("Show me the Dockerfile", "read_file", "file_ops"),
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("Read the docker-compose.yml", "read_file", "file_ops"),
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("Save the function to utils.py", "write_file", "file_ops"),
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("Create a backup of config.yaml", "write_file", "file_ops"),
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# Terminal commands (20)
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("List all files in the current directory", "terminal", "terminal"),
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("Show disk usage", "terminal", "terminal"),
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("Check what processes are running", "terminal", "terminal"),
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("Show the git log", "terminal", "terminal"),
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("Check the Python version", "terminal", "terminal"),
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("Run ls -la in the home directory", "terminal", "terminal"),
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("Show the current date and time", "terminal", "terminal"),
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("Check network connectivity with ping", "terminal", "terminal"),
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("Show environment variables", "terminal", "terminal"),
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("List running docker containers", "terminal", "terminal"),
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("Check system memory usage", "terminal", "terminal"),
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("Show the crontab", "terminal", "terminal"),
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("Check the firewall status", "terminal", "terminal"),
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("Show recent log entries", "terminal", "terminal"),
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("Check disk free space", "terminal", "terminal"),
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("Run a system update check", "terminal", "terminal"),
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("Show open network connections", "terminal", "terminal"),
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("Check the timezone", "terminal", "terminal"),
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("List tmux sessions", "terminal", "terminal"),
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("Check systemd service status", "terminal", "terminal"),
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# Web search (15)
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("Search for Python asyncio documentation", "web_search", "web"),
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("Look up the latest GPT-4 pricing", "web_search", "web"),
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("Find information about Gemma 4 benchmarks", "web_search", "web"),
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("Search for Rust vs Go performance comparison", "web_search", "web"),
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("Look up Docker best practices", "web_search", "web"),
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("Search for Kubernetes deployment tutorials", "web_search", "web"),
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("Find the latest AI safety research papers", "web_search", "web"),
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("Search for SQLite vs PostgreSQL comparison", "web_search", "web"),
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("Look up Linux kernel tuning parameters", "web_search", "web"),
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("Search for WebSocket protocol specification", "web_search", "web"),
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("Find information about Matrix protocol federation", "web_search", "web"),
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("Search for MCP protocol documentation", "web_search", "web"),
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("Look up A2A agent protocol spec", "web_search", "web"),
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("Search for quantization methods for LLMs", "web_search", "web"),
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("Find information about GRPO training", "web_search", "web"),
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# Code execution (15)
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("Calculate the factorial of 20", "execute_code", "code"),
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("Parse this JSON and extract keys", "execute_code", "code"),
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("Sort a list of numbers", "execute_code", "code"),
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("Calculate the fibonacci sequence", "execute_code", "code"),
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("Convert a CSV to JSON", "execute_code", "code"),
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("Parse an email address", "execute_code", "code"),
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("Calculate elapsed time between dates", "execute_code", "code"),
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("Generate a random password", "execute_code", "code"),
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("Hash a string with SHA256", "execute_code", "code"),
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("Parse a URL into components", "execute_code", "code"),
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("Calculate statistics on a dataset", "execute_code", "code"),
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("Convert epoch timestamp to human readable", "execute_code", "code"),
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("Validate an IPv4 address", "execute_code", "code"),
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("Calculate the distance between coordinates", "execute_code", "code"),
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("Generate a UUID", "execute_code", "code"),
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# Parallel tool calls (10)
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("Read config.yaml and show git status at the same time", "read_file|terminal", "parallel"),
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("Check disk usage and memory usage simultaneously", "terminal|terminal", "parallel"),
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("Read two files at once: README and CHANGELOG", "read_file|read_file", "parallel"),
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("Search for imports in both Python and JS files", "search_files|search_files", "parallel"),
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("Check git log and disk space in parallel", "terminal|terminal", "parallel"),
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("Read the Makefile and Dockerfile together", "read_file|read_file", "parallel"),
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("Search for TODO and FIXME at the same time", "search_files|search_files", "parallel"),
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("List files and check Python version simultaneously", "terminal|terminal", "parallel"),
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("Read package.json and requirements.txt together", "read_file|read_file", "parallel"),
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("Check system time and uptime in parallel", "terminal|terminal", "parallel"),
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]
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@dataclass
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class BenchmarkResult:
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model: str
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prompt: str
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expected_tool: str
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category: str
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success: bool = False
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tool_called: str = ""
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args_valid: bool = False
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latency_ms: float = 0.0
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prompt_tokens: int = 0
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completion_tokens: int = 0
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error: str = ""
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def call_model(model: str, prompt: str) -> dict:
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"""Call a model with tool schemas and return the response."""
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url = f"{ENDPOINT}/chat/completions"
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data = {
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"model": model,
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": prompt},
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],
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"tools": TOOL_SCHEMAS,
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"max_tokens": 512,
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"temperature": 0.0,
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}
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body = json.dumps(data).encode()
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req = urllib.request.Request(url, data=body, headers={
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"Content-Type": "application/json",
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"Authorization": f"Bearer {API_KEY}",
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}, method="POST")
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start = time.time()
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try:
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with urllib.request.urlopen(req, timeout=60) as resp:
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result = json.loads(resp.read())
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elapsed = time.time() - start
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return {"response": result, "elapsed": elapsed, "error": None}
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except Exception as e:
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elapsed = time.time() - start
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return {"response": None, "elapsed": elapsed, "error": str(e)}
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def evaluate_response(result: dict, expected_tool: str) -> BenchmarkResult:
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"""Evaluate a model response against expectations."""
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resp = result.get("response")
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error = result.get("error", "")
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elapsed = result.get("elapsed", 0)
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br = BenchmarkResult(
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model="",
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prompt="",
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expected_tool=expected_tool,
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category="",
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latency_ms=round(elapsed * 1000, 1),
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error=error or "",
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)
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if not resp:
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br.success = False
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return br
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usage = resp.get("usage", {})
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br.prompt_tokens = usage.get("prompt_tokens", 0)
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br.completion_tokens = usage.get("completion_tokens", 0)
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choice = resp.get("choices", [{}])[0]
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message = choice.get("message", {})
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tool_calls = message.get("tool_calls", [])
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if not tool_calls:
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br.success = False
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br.error = "no_tool_calls"
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return br
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# Check first tool call
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tc = tool_calls[0]
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fn = tc.get("function", {})
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br.tool_called = fn.get("name", "")
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# Parse args
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|
args_str = fn.get("arguments", "{}")
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|
try:
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|
json.loads(args_str)
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|
br.args_valid = True
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|
except json.JSONDecodeError:
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|
# Try normalization
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|
try:
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|
import re
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|
fixed = re.sub(r',\s*([}\]])', r'\1', args_str.strip())
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|
json.loads(fixed)
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|
br.args_valid = True
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|
except:
|
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|
br.args_valid = False
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||||||
|
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||||||
|
# Success = tool called matches expected (or contains it for parallel)
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|
expected = expected_tool.split("|")[0] # primary expected tool
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|
br.success = br.tool_called == expected and br.args_valid
|
||||||
|
|
||||||
|
return br
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|
|
||||||
|
|
||||||
|
def run_benchmark(model: str, prompts: list, limit: int = None) -> List[BenchmarkResult]:
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|
"""Run benchmark against a model."""
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|
if limit:
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|
prompts = prompts[:limit]
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|
|
||||||
|
results = []
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|
for i, (prompt, expected_tool, category) in enumerate(prompts):
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|
print(f" [{i+1}/{len(prompts)}] {model}: {prompt[:50]}...", end=" ", flush=True)
|
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|
|
||||||
|
raw = call_model(model, prompt)
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|
br = evaluate_response(raw, expected_tool)
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|
br.model = model
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|
br.prompt = prompt
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||||||
|
br.category = category
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|
|
||||||
|
status = "OK" if br.success else f"FAIL({br.error or br.tool_called})"
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|
print(f"{status} {br.latency_ms}ms")
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|
results.append(br)
|
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|
|
||||||
|
return results
|
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|
|
||||||
|
|
||||||
|
def generate_report(results: List[BenchmarkResult]) -> str:
|
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|
"""Generate markdown benchmark report."""
|
||||||
|
by_model = {}
|
||||||
|
for r in results:
|
||||||
|
if r.model not in by_model:
|
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|
by_model[r.model] = []
|
||||||
|
by_model[r.model].append(r)
|
||||||
|
|
||||||
|
lines = [
|
||||||
|
"# Gemma 4 Tool Calling Benchmark",
|
||||||
|
f"",
|
||||||
|
f"**Date:** {datetime.now().strftime('%Y-%m-%d %H:%M')}",
|
||||||
|
f"**Prompts:** {len(results) // len(by_model)} per model",
|
||||||
|
f"",
|
||||||
|
]
|
||||||
|
|
||||||
|
# Summary table
|
||||||
|
lines.append("| Metric | " + " | ".join(by_model.keys()) + " |")
|
||||||
|
lines.append("|--------|" + "|".join(["--------"] * len(by_model)) + "|")
|
||||||
|
|
||||||
|
metrics = ["schema_parse", "tool_execution", "avg_latency_ms", "total_prompt_tokens"]
|
||||||
|
for metric in ["success_rate", "args_valid_rate", "avg_latency_ms", "total_prompt_tokens"]:
|
||||||
|
vals = []
|
||||||
|
for model, rs in by_model.items():
|
||||||
|
if metric == "success_rate":
|
||||||
|
v = sum(1 for r in rs if r.success) / len(rs) * 100
|
||||||
|
vals.append(f"{v:.1f}%")
|
||||||
|
elif metric == "args_valid_rate":
|
||||||
|
v = sum(1 for r in rs if r.args_valid) / len(rs) * 100
|
||||||
|
vals.append(f"{v:.1f}%")
|
||||||
|
elif metric == "avg_latency_ms":
|
||||||
|
v = sum(r.latency_ms for r in rs) / len(rs)
|
||||||
|
vals.append(f"{v:.0f}ms")
|
||||||
|
elif metric == "total_prompt_tokens":
|
||||||
|
v = sum(r.prompt_tokens for r in rs)
|
||||||
|
vals.append(f"{v:,}")
|
||||||
|
label = metric.replace("_", " ").title()
|
||||||
|
lines.append(f"| {label} | " + " | ".join(vals) + " |")
|
||||||
|
|
||||||
|
lines.append("")
|
||||||
|
|
||||||
|
# By category
|
||||||
|
lines.append("## By Category")
|
||||||
|
lines.append("")
|
||||||
|
lines.append("| Category | " + " | ".join(f"{m} success" for m in by_model.keys()) + " |")
|
||||||
|
lines.append("|----------|" + "|".join(["--------"] * len(by_model)) + "|")
|
||||||
|
|
||||||
|
categories = sorted(set(r.category for r in results))
|
||||||
|
for cat in categories:
|
||||||
|
vals = []
|
||||||
|
for model, rs in by_model.items():
|
||||||
|
cat_results = [r for r in rs if r.category == cat]
|
||||||
|
if cat_results:
|
||||||
|
v = sum(1 for r in cat_results if r.success) / len(cat_results) * 100
|
||||||
|
vals.append(f"{v:.0f}%")
|
||||||
|
else:
|
||||||
|
vals.append("N/A")
|
||||||
|
lines.append(f"| {cat} | " + " | ".join(vals) + " |")
|
||||||
|
|
||||||
|
return "\n".join(lines)
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
import argparse
|
||||||
|
parser = argparse.ArgumentParser(description="Tool calling benchmark")
|
||||||
|
parser.add_argument("--model1", default="gemma3:27b")
|
||||||
|
parser.add_argument("--model2", default="xiaomi/mimo-v2-pro")
|
||||||
|
parser.add_argument("--endpoint", default=ENDPOINT)
|
||||||
|
parser.add_argument("--limit", type=int, default=None)
|
||||||
|
parser.add_argument("--output", default=None)
|
||||||
|
parser.add_argument("--markdown", action="store_true")
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
global ENDPOINT
|
||||||
|
ENDPOINT = args.endpoint
|
||||||
|
|
||||||
|
prompts = TEST_PROMPTS
|
||||||
|
if args.limit:
|
||||||
|
prompts = prompts[:args.limit]
|
||||||
|
|
||||||
|
print(f"Benchmark: {args.model1} vs {args.model2}")
|
||||||
|
print(f"Prompts: {len(prompts)}")
|
||||||
|
print()
|
||||||
|
|
||||||
|
print(f"--- {args.model1} ---")
|
||||||
|
results1 = run_benchmark(args.model1, prompts)
|
||||||
|
|
||||||
|
print(f"\n--- {args.model2} ---")
|
||||||
|
results2 = run_benchmark(args.model2, prompts)
|
||||||
|
|
||||||
|
all_results = results1 + results2
|
||||||
|
|
||||||
|
report = generate_report(all_results)
|
||||||
|
print(f"\n{report}")
|
||||||
|
|
||||||
|
if args.output:
|
||||||
|
with open(args.output, "w") as f:
|
||||||
|
json.dump([r.__dict__ for r in all_results], f, indent=2, default=str)
|
||||||
|
print(f"\nResults saved to {args.output}")
|
||||||
|
|
||||||
|
# Save markdown report
|
||||||
|
report_path = f"benchmarks/gemma4-tool-calling-{datetime.now().strftime('%Y-%m-%d')}.md"
|
||||||
|
Path("benchmarks").mkdir(exist_ok=True)
|
||||||
|
with open(report_path, "w") as f:
|
||||||
|
f.write(report)
|
||||||
|
print(f"Report saved to {report_path}")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
Reference in New Issue
Block a user