453 lines
14 KiB
Markdown
453 lines
14 KiB
Markdown
# ACEBench
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## Overview
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ACEBench is a tool-use benchmark for evaluating whether large language models can select APIs, fill
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arguments, handle abnormal requests, and complete realistic agent tasks.
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## Task Description
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- **Task Type**: Function calling and agentic tool use
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- **Input**: Conversation history, API specifications, optional time/profile context, and agent task context
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- **Output**: Function calls or diagnostic text for special cases
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- **Subsets**: normal, special, and agent
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## Evaluation Notes
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- The adapter passes ACEBench API specifications as EvalScope tools and also includes concise text
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instructions for text-only models.
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- Normal samples are scored by matching function names and arguments.
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- Special samples are scored against ACEBench's diagnostic text contract.
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- Agent samples report `process_acc` against ACEBench milestones. If a model returns a final-state JSON object,
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`end_state_acc` is also reported and used as `acc`; otherwise `acc` follows `process_acc`.
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `acebench` |
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| **Dataset ID** | [evalscope/acebench](https://modelscope.cn/datasets/evalscope/acebench/summary) |
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| **Paper** | N/A |
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| **Tags** | `Agent`, `FunctionCalling`, `MultiTurn` |
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| **Metrics** | `acc`, `process_acc`, `end_state_acc` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `normal` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 1,023 |
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| Prompt Length (Mean) | 4676.74 chars |
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| Prompt Length (Min/Max) | 1007 / 10555 chars |
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**Per-Subset Statistics:**
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| Subset | Samples | Prompt Mean | Prompt Min | Prompt Max |
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|--------|---------|-------------|------------|------------|
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| `normal` | 823 | 4859.68 | 1070 | 10555 |
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| `special` | 150 | 3449.69 | 1007 | 8692 |
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| `agent` | 50 | 5346.72 | 4454 | 5656 |
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## Sample Example
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**Subset**: `normal`
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```json
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{
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"input": [
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{
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"id": "134dd42a",
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"content": "You are evaluating ACEBench tool-use tasks.\n\nUse the available tool schemas when native function calling is supported.\n\nFor text-only output, return API calls as [ApiName(key1='value1', key2=2)]. Return only the call list and no extra explana ... [TRUNCATED 2553 chars] ... \"}, \"effects\": {\"description\": \"List of audio effects to apply.\", \"type\": \"array\", \"items\": {\"type\": \"string\", \"enum\": [\"reverb\", \"echo\", \"distortion\"]}}}, \"required\": [\"frequency\", \"gain\"]}}}, \"required\": [\"microphone\", \"performanceTime\"]}}]"
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},
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{
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"id": "da9681d9",
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"content": "I have been fascinated recently with total solar eclipses. I am planning my next travel and would like to know when the next total solar eclipse will be visible in Greece, specifically in Athens, over the next five years.",
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"role": "user"
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}
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],
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"target": "{\"ground_truth\": {\"NightSkyAnalysis_performEclipseAnalysis\": {\"dateRange\": {\"startDate\": \"2023-01-01\", \"endDate\": \"2028-01-01\"}, \"location\": {\"latitude\": 37.9838, \"longitude\": 23.7275}, \"eclipseType\": \"total\"}}, \"mile_stone\": []}",
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"id": 0,
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"group_id": 0,
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"tools": [
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{
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"name": "NightSkyAnalysis_performEclipseAnalysis",
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"description": "Analyzes the occurrence of solar eclipses, categorizes them into types, and predicts future occurrences based on historical data and celestial mechanics.",
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"parameters": {
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"type": "object",
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"properties": {
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"dateRange": {
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"type": "object",
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"description": "The range of dates for which to analyze solar eclipses.",
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"properties": {
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"startDate": {
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"type": "string",
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"description": "The starting date for the analysis in YYYY-MM-DD format."
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},
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"endDate": {
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"type": "string",
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"description": "The ending date for the analysis in YYYY-MM-DD format."
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}
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},
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"required": [
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"startDate",
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"endDate"
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]
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},
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"location": {
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"type": "object",
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"description": "Geographical coordinates to focus the eclipse analysis.",
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"properties": {
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"latitude": {
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"type": "number",
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"description": "Latitude of the location."
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},
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"longitude": {
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"type": "number",
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"description": "Longitude of the location."
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}
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},
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"required": [
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"latitude",
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"longitude"
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]
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},
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"eclipseType": {
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"type": "string",
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"description": "The type of solar eclipse to specifically analyze.",
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"enum": [
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"total",
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"annular",
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"partial"
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]
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}
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},
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"required": [
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"dateRange",
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"location"
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]
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}
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},
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{
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"name": "AudioPerformanceOptimizer_optimizeMicrophoneSettings",
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"description": "Optimizes microphone settings for live performances, focusing on dynamic microphones to enhance sound quality and reduce feedback.",
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"parameters": {
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"type": "object",
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"properties": {
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"microphone": {
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"type": "object",
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"description": "Details of the microphone used.",
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"properties": {
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"type": {
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"type": "string",
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"description": "Type of the microphone.",
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"enum": [
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"dynamic",
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"condenser",
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"ribbon"
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]
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},
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"model": {
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"type": "string",
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"description": "Model of the microphone."
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}
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},
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"required": [
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"type",
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"model"
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]
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},
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"performanceTime": {
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"type": "string",
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"description": "Scheduled time for the performance.",
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"enum": [
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"morning",
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"afternoon",
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"evening",
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"night"
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]
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},
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"environment": {
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"type": "object",
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"description": "Environmental conditions of the performance area.",
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"properties": {
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"humidity": {
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"type": "integer",
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"description": "Humidity level as a percentage."
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},
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"temperature": {
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"type": "integer",
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"description": "Temperature in Celsius."
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}
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}
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},
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"soundSettings": {
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"type": "array",
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"description": "Specific sound settings to apply.",
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"items": {
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"type": "object",
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"properties": {
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"frequency": {
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"type": "integer",
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"description": "Frequency adjustments in Hz."
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},
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"gain": {
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"type": "integer",
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"description": "Gain adjustments in dB."
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},
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"effects": {
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"type": "array",
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"description": "List of audio effects to apply.",
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"items": {
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"type": "string",
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"enum": [
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"reverb",
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"echo",
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"distortion"
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]
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}
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}
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},
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"required": [
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"frequency",
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"gain"
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]
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}
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}
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},
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"required": [
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"microphone",
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"performanceTime"
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]
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}
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}
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],
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"metadata": {
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"id": "normal_single_turn_single_function_0",
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"sub_category": "data_normal_single_turn_single_function",
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"question": "user: I have been fascinated recently with total solar eclipses. I am planning my next travel and would like to know when the next total solar eclipse will be visible in Greece, specifically in Athens, over the next five years.\n",
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"time": "",
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"profile": "",
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"functions": [
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{
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"name": "NightSkyAnalysis_performEclipseAnalysis",
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"description": "Analyzes the occurrence of solar eclipses, categorizes them into types, and predicts future occurrences based on historical data and celestial mechanics.",
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"parameters": {
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"type": "object",
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"properties": {
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"dateRange": {
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"description": "The range of dates for which to analyze solar eclipses.",
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"type": "object",
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"properties": {
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"startDate": {
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"description": "The starting date for the analysis in YYYY-MM-DD format.",
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"type": "string"
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},
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"endDate": {
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"description": "The ending date for the analysis in YYYY-MM-DD format.",
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"type": "string"
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}
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},
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"required": [
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"startDate",
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"endDate"
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]
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},
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"location": {
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"description": "Geographical coordinates to focus the eclipse analysis.",
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"type": "object",
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"properties": {
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"latitude": {
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"description": "Latitude of the location.",
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"type": "number",
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"minimum": -90,
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"maximum": 90
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},
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"longitude": {
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"description": "Longitude of the location.",
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"type": "number",
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"minimum": -180,
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"maximum": 180
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}
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},
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"required": [
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"latitude",
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"longitude"
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]
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},
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"eclipseType": {
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"description": "The type of solar eclipse to specifically analyze.",
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"type": "string",
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"enum": [
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"total",
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"annular",
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"partial"
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]
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}
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},
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"required": [
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"dateRange",
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"location"
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]
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}
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},
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{
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"name": "AudioPerformanceOptimizer_optimizeMicrophoneSettings",
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"description": "Optimizes microphone settings for live performances, focusing on dynamic microphones to enhance sound quality and reduce feedback.",
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"parameters": {
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"type": "object",
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"properties": {
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"microphone": {
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"description": "Details of the microphone used.",
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"type": "object",
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"properties": {
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"type": {
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"description": "Type of the microphone.",
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"type": "string",
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"enum": [
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"dynamic",
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"condenser",
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"ribbon"
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]
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},
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"model": {
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"description": "Model of the microphone.",
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"type": "string"
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}
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},
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"required": [
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"type",
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"model"
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]
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},
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"performanceTime": {
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"description": "Scheduled time for the performance.",
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"type": "string",
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"enum": [
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"morning",
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"afternoon",
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"evening",
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"night"
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]
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},
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"environment": {
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"description": "Environmental conditions of the performance area.",
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"type": "object",
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"properties": {
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"humidity": {
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"description": "Humidity level as a percentage.",
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"type": "integer",
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"minimum": 0,
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"maximum": 100
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},
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"temperature": {
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"description": "Temperature in Celsius.",
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"type": "integer"
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}
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}
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},
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"soundSettings": {
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"description": "Specific sound settings to apply.",
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"frequency": {
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"description": "Frequency adjustments in Hz.",
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"type": "integer"
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},
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"gain": {
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"description": "Gain adjustments in dB.",
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"type": "integer"
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},
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"effects": {
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"description": "List of audio effects to apply.",
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"type": "array",
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"items": {
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"type": "string",
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"enum": [
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"reverb",
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"echo",
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"distortion"
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]
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}
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}
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},
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"required": [
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"frequency",
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"gain"
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]
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}
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}
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},
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"required": [
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"microphone",
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"performanceTime"
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]
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}
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}
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],
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"ground_truth": {
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"NightSkyAnalysis_performEclipseAnalysis": {
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"dateRange": {
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"startDate": "2023-01-01",
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"endDate": "2028-01-01"
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},
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"location": {
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"latitude": 37.9838,
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"longitude": 23.7275
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},
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"eclipseType": "total"
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}
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},
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"mile_stone": [],
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"initial_config": {},
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"involved_classes": []
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}
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}
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```
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## Prompt Template
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*No prompt template defined.*
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets acebench \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['acebench'],
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dataset_args={
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'acebench': {
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# subset_list: ['normal', 'special', 'agent'] # optional, evaluate specific subsets
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}
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},
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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