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import asyncio
import json
import time
from datasets import load_dataset
from lagent.agents.stream import PLUGIN_CN, AsyncAgentForInternLM, AsyncMathCoder, get_plugin_prompt
from lagent.llms import INTERNLM2_META
from lagent.llms.lmdeploy_wrapper import AsyncLMDeployPipeline
from lagent.prompts.parsers import PluginParser
# set up the loop
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# initialize the model
model = AsyncLMDeployPipeline(
path='internlm/internlm2_5-7b-chat',
meta_template=INTERNLM2_META,
model_name='internlm-chat',
tp=1,
top_k=1,
temperature=1.0,
stop_words=['<|im_end|>', '<|action_end|>'],
max_new_tokens=1024,
)
# ----------------------- interpreter -----------------------
print('-' * 80, 'interpreter', '-' * 80)
ds = load_dataset('lighteval/MATH', split='test')
problems = [item['problem'] for item in ds.select(range(0, 5000, 2))]
coder = AsyncMathCoder(
llm=model,
interpreter=dict(
type='lagent.actions.AsyncIPythonInterpreter', max_kernels=300),
max_turn=11)
tic = time.time()
coros = [coder(query, session_id=i) for i, query in enumerate(problems)]
res = loop.run_until_complete(asyncio.gather(*coros))
# print([r.model_dump_json() for r in res])
print('-' * 120)
print(f'time elapsed: {time.time() - tic}')
with open('./tmp_1.json', 'w') as f:
json.dump([coder.get_steps(i) for i in range(len(res))],
f,
ensure_ascii=False,
indent=4)
# ----------------------- plugin -----------------------
print('-' * 80, 'plugin', '-' * 80)
plugins = [dict(type='lagent.actions.AsyncArxivSearch')]
agent = AsyncAgentForInternLM(
llm=model,
plugins=plugins,
output_format=dict(
type=PluginParser,
template=PLUGIN_CN,
prompt=get_plugin_prompt(plugins)))
tic = time.time()
coros = [
agent(query, session_id=i)
for i, query in enumerate(['LLM智能体方向的最新论文有哪些？'] * 50)
]
res = loop.run_until_complete(asyncio.gather(*coros))
# print([r.model_dump_json() for r in res])
print('-' * 120)
print(f'time elapsed: {time.time() - tic}')
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