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92 lines
2.8 KiB
Markdown
92 lines
2.8 KiB
Markdown
# Apps examples with GenerationExecutor / High-level API
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## OpenAI API
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[openai_server.py](./openai_server.py) is an OpenAI compatible server which supports `v1/version`, `v1/completions` and `v1/chat/completions`. [openai_client.py](./openai_client.py) is a simple example using OpenAI client to query your model. To start the server, you can run
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```
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python3 ./openai_server.py <model_path>
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```
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Then you can use the following APIs by running our example client or by `curl`.
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### v1/completions
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Query by `curl`:
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```
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curl http://localhost:8000/v1/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": <model_name>,
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"prompt": "Where is New York?",
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"max_tokens": 16,
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"temperature": 0
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}'
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```
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Query by our example:
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```
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python3 ./openai_client.py --prompt "Where is New York?" --api completions
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```
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### v1/chat/completions
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Query by `curl`:
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```
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curl http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": <model_name>,
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"messages":[{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Where is New York?"}],
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"max_tokens": 16,
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"temperature": 0
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}'
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```
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Query by our example:
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```
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python3 ./openai_client.py --prompt "Where is New York?" --api chat
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```
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## Python chat
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[chat.py](./chat.py) provides a small examples to play around with your model. Before running, install additional requirements with ` pip install -r ./requirements.txt`. Then you can run it with
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```
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python3 ./chat.py --model <model_dir> --tokenizer <tokenizer_path> --tp_size <tp_size>
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```
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Please run `python3 ./chat.py --help` for more information on the arguments.
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Note that, the `model_dir` could accept the following formats:
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1. A path to a built TRT-LLM engine
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2. A path to a local HuggingFace model
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3. The name of a HuggingFace model such as "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
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## FastAPI server
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### Install the additional requirements
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```
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pip install -r ./requirements.txt
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```
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### Start the server
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Start the server with:
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```
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python3 ./fastapi_server.py <model_dir>&
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```
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Note that, the `model_dir` could accept same formats as in the chat example. If you are using an engine build with `trtllm-build`, remember to pass the tokenizer path:
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```
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python3 ./fastapi_server.py <model_dir> --tokenizer <tokenizer_dir>&
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```
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To get more information on all the arguments, please run `python3 ./fastapi_server.py --help`.
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### Send requests
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You can pass request arguments like "max_tokens", "top_p", "top_k" in your JSON dict:
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```
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curl http://localhost:8000/generate -d '{"prompt": "In this example,", "max_tokens": 8}'
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```
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You can also use the streaming interface with:
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```
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curl http://localhost:8000/generate -d '{"prompt": "In this example,", "max_tokens": 8, "streaming": true}'
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```
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