File size: 12,838 Bytes
7feac49 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 |
import os
os.environ['SWIFT_DEBUG'] = '1'
system = 'You are a helpful assistant.'
tools = [{
'type': 'function',
'function': {
'name': 'get_current_weather',
'description': 'Get the current weather in a given location',
'parameters': {
'type': 'object',
'properties': {
'location': {
'type': 'string',
'description': 'The city and state, e.g. San Francisco, CA'
},
'unit': {
'type': 'string',
'enum': ['celsius', 'fahrenheit']
}
},
'required': ['location']
}
}
}, {
'name_for_model': 'tool2',
'name_for_human': '工具2',
'description': 'Tool2的描述',
}]
glm4_tools = [{
'type': 'function',
'function': {
'name': 'realtime_aqi',
'description': '天气预报。获取实时空气质量。当前空气质量，PM2.5，PM10信息',
'parameters': {
'type': 'object',
'properties': {
'city': {
'description': '城市名'
}
},
'required': ['city']
}
}
}]
glm4_tool_messasges = [
{
'role': 'tool',
'content': '{"city": "北京", "aqi": "10", "unit": "celsius"}'
},
{
'role': 'tool',
'content': '{"city": "上海", "aqi": "72", "unit": "fahrenheit"}'
},
]
glm4_query = '北京和上海今天的天气情况'
def _infer(engine, num_tools: int = 1, agent_tools=None, tool_messages=None, query=None):
if agent_tools is None:
agent_tools = tools
if tool_messages is None:
tool_messages = []
for _ in range(num_tools):
tool_messages.append({
'role': 'tool',
'content': '{"temperature": 32, "condition": "Sunny", "humidity": 50}'
})
stop = [engine.default_template.agent_template.keyword.observation]
query = query or "How's the weather in Beijing today?"
infer_request = InferRequest([{'role': 'user', 'content': query}], tools=agent_tools)
request_config = RequestConfig(max_tokens=512, stop=stop, temperature=0)
resp_list = engine.infer([infer_request], request_config=request_config)
response = resp_list[0].choices[0].message.content
toolcall = resp_list[0].choices[0].message.tool_calls[0].function
print(f'response: {response}')
print(f'toolcall: {toolcall}')
assert toolcall is not None
infer_request.messages.append({'role': 'assistant', 'content': response})
infer_request.messages += tool_messages
resp_list = engine.infer([infer_request], request_config=request_config)
response2 = resp_list[0].choices[0].message.content
print(f'response2: {response2}')
infer_request.messages.append({'role': 'assistant', 'content': response2})
return infer_request.messages
def test_react_en():
agent_template = agent_templates['react_en']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 1144
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine)
assert messages[-1]['content'] == (
'Thought: The current temperature in Beijing is 32 degrees Celsius, and the condition is sunny '
'with a humidity of 50%.\nFinal Answer: The current temperature in Beijing is 32 degrees Celsius,'
' and the condition is sunny with a humidity of 50%.')
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
def test_react_zh():
agent_template = agent_templates['react_zh']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 712
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
_infer(engine)
def test_qwen_en():
agent_template = agent_templates['qwen_en']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 879
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine)
assert messages[-1]['content'] == (
'✿RETURN✿: Today in Beijing, the temperature is 32°C with sunny conditions and the humidity '
'is at 50%. Enjoy the nice weather!')
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
def test_qwen_zh():
agent_template = agent_templates['qwen_zh']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 577
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
_infer(engine)
def test_qwen_en_parallel():
agent_template = agent_templates['qwen_en_parallel']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 1012
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine, num_tools=2)
assert messages[-1]['content'] == (
'✿RETURN✿: Today in Beijing, the temperature is 32 degrees Celsius with sunny conditions '
'and the humidity is at 50%. Enjoy the nice weather!')
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
def test_qwen_zh_parallel():
agent_template = agent_templates['qwen_zh_parallel']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 688
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
_infer(engine, num_tools=2)
def test_hermes():
agent_template = agent_templates['hermes']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 875
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine, num_tools=2)
template.template_backend = 'jinja'
messages2 = _infer(engine, num_tools=2)
assert messages[-1]['content'] == messages2[-1]['content'] == (
'Today in Beijing, the temperature is 32 degrees Celsius with sunny conditions '
'and the humidity is at 50%. Enjoy the nice weather!')
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
template.template_backend = 'jinja'
encoded2 = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded2["input_ids"])}')
print(f'labels: {template.safe_decode(encoded2["labels"])}')
assert encoded['input_ids'] == encoded2['input_ids'][:-1]
def test_toolbench():
agent_template = agent_templates['toolbench']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 1833
engine = PtEngine('Qwen/Qwen2.5-7B-Instruct')
template = engine.default_template
template.agent_template = agent_template
_infer(engine)
def test_glm4():
agent_template = agent_templates['glm4']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 846
engine = PtEngine('ZhipuAI/glm-4-9b-chat')
template = engine.default_template
template.agent_template = agent_template
_infer(engine, agent_tools=glm4_tools, tool_messages=glm4_tool_messasges, query=glm4_query)
def test_glm4_0414():
agent_template = agent_templates['glm4_0414']()
new_system = agent_template._format_tools(tools, system)
assert len(new_system) == 769
engine = PtEngine('ZhipuAI/GLM-4-9B-0414')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine, agent_tools=glm4_tools, tool_messages=glm4_tool_messasges, query=glm4_query)
assert messages[-1]['content'] == '根据天气预报工具，北京今天的空气质量指数为10，属于良好水平；上海今天的空气质量指数为72，属于轻度污染水平。'
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
def test_llama3():
agent_template = agent_templates['llama3']()
engine = PtEngine('LLM-Research/Llama-3.2-3B-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine)
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
data = dataset[6]
data['messages'].insert(1, data['messages'][1])
data['messages'].insert(3, data['messages'][3])
template.template_backend = 'swift'
encoded = template.encode(data)
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
def test_llama4():
agent_template = agent_templates['llama4']()
engine = PtEngine('LLM-Research/Llama-4-Scout-17B-16E-Instruct')
template = engine.default_template
template.agent_template = agent_template
messages = _infer(engine)
template.set_mode('train')
encoded = template.encode({'messages': messages})
print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
print(f'labels: {template.safe_decode(encoded["labels"])}')
if __name__ == '__main__':
from swift.plugin import agent_templates
from swift.llm import PtEngine, InferRequest, RequestConfig, load_dataset
# test_react_en()
# test_react_zh()
# test_qwen_en()
# test_qwen_zh()
# test_qwen_en_parallel()
# test_qwen_zh_parallel()
test_hermes()
# test_toolbench()
# test_glm4()
# test_glm4_0414()
# test_llama3()
# test_llama4()
|