83 lines
2.0 KiB
Python
83 lines
2.0 KiB
Python
import sglang as sgl
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@sgl.function
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def tool_use(s, question):
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s += "To answer this question: " + question + ", "
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s += "I need to use a " + sgl.gen("tool", choices=["calculator", "web browser"]) + ". "
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if s["tool"] == "calculator":
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s += "The math expression is" + sgl.gen("expression")
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elif s["tool"] == "web browser":
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s += "The website url is" + sgl.gen("url")
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@sgl.function
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def tip_suggestion(s):
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s += (
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"Here are two tips for staying healthy: "
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"1. Balanced Diet. 2. Regular Exercise.\n\n"
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)
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forks = s.fork(2)
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for i, f in enumerate(forks):
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f += f"Now, expand tip {i+1} into a paragraph:\n"
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f += sgl.gen(f"detailed_tip", max_tokens=256, stop="\n\n")
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s += "Tip 1:" + forks[0]["detailed_tip"] + "\n"
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s += "Tip 2:" + forks[1]["detailed_tip"] + "\n"
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s += "In summary" + sgl.gen("summary")
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@sgl.function
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def text_qa(s, question):
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s += "Q: " + question + "\n"
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s += "A:" + sgl.gen("answer", stop="\n")
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def driver_tool_use():
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state = tool_use.run(question="What is the capital of the United States?")
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print(state.text())
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print("\n")
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def driver_tip_suggestion():
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state = tip_suggestion.run()
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print(state.text())
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print("\n")
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def driver_batching():
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states = text_qa.run_batch(
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[
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{"question": "What is the capital of the United Kingdom?"},
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{"question": "What is the capital of France?"},
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{"question": "What is the capital of Japan?"},
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],
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progress_bar=True
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)
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for s in states:
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print(s.text())
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print("\n")
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def driver_stream():
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state = text_qa.run(
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question="What is the capital of France?",
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temperature=0.1,
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stream=True
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)
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for out in state.text_iter():
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print(out, end="", flush=True)
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print("\n")
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if __name__ == "__main__":
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sgl.set_default_backend(sgl.OpenAI("gpt-3.5-turbo-instruct"))
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driver_tool_use()
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driver_tip_suggestion()
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driver_batching()
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driver_stream()
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