Generate Text Asynchronously#
Source NVIDIA/TensorRT-LLM.
1### Generate Text Asynchronously
2import asyncio
3
4from tensorrt_llm import SamplingParams
5from tensorrt_llm._tensorrt_engine import LLM
6
7
8def main():
9 # model could accept HF model name or a path to local HF model.
10 llm = LLM(model="TinyLlama/TinyLlama-1.1B-Chat-v1.0")
11
12 # Sample prompts.
13 prompts = [
14 "Hello, my name is",
15 "The president of the United States is",
16 "The capital of France is",
17 "The future of AI is",
18 ]
19
20 # Create a sampling params.
21 sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
22
23 # Async based on Python coroutines
24 async def task(prompt: str):
25 output = await llm.generate_async(prompt, sampling_params)
26 print(
27 f"Prompt: {output.prompt!r}, Generated text: {output.outputs[0].text!r}"
28 )
29
30 async def main():
31 tasks = [task(prompt) for prompt in prompts]
32 await asyncio.gather(*tasks)
33
34 asyncio.run(main())
35
36 # Got output like follows:
37 # Prompt: 'Hello, my name is', Generated text: '\n\nJane Smith. I am a student pursuing my degree in Computer Science at [university]. I enjoy learning new things, especially technology and programming'
38 # Prompt: 'The president of the United States is', Generated text: 'likely to nominate a new Supreme Court justice to fill the seat vacated by the death of Antonin Scalia. The Senate should vote to confirm the'
39 # Prompt: 'The capital of France is', Generated text: 'Paris.'
40 # Prompt: 'The future of AI is', Generated text: 'an exciting time for us. We are constantly researching, developing, and improving our platform to create the most advanced and efficient model available. We are'
41
42
43if __name__ == '__main__':
44 main()