mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
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"""Integration tests for the langchain tracer module."""
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import asyncio
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import pytest
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from langchain.agents import AgentType, initialize_agent, load_tools
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from langchain.callbacks import get_openai_callback
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from langchain.llms import OpenAI
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@pytest.mark.asyncio
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async def test_openai_callback() -> None:
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llm = OpenAI(temperature=0)
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with get_openai_callback() as cb:
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llm("What is the square root of 4?")
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total_tokens = cb.total_tokens
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assert total_tokens > 0
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with get_openai_callback() as cb:
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llm("What is the square root of 4?")
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llm("What is the square root of 4?")
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assert cb.total_tokens == total_tokens * 2
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with get_openai_callback() as cb:
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await asyncio.gather(
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*[llm.agenerate(["What is the square root of 4?"]) for _ in range(3)]
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)
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assert cb.total_tokens == total_tokens * 3
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task = asyncio.create_task(llm.agenerate(["What is the square root of 4?"]))
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with get_openai_callback() as cb:
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await llm.agenerate(["What is the square root of 4?"])
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await task
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assert cb.total_tokens == total_tokens
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def test_openai_callback_agent() -> None:
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llm = OpenAI(temperature=0)
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tools = load_tools(["serpapi", "llm-math"], llm=llm)
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agent = initialize_agent(
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tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
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)
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with get_openai_callback() as cb:
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agent.run(
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"Who is Olivia Wilde's boyfriend? "
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"What is his current age raised to the 0.23 power?"
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)
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print(f"Total Tokens: {cb.total_tokens}")
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print(f"Prompt Tokens: {cb.prompt_tokens}")
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print(f"Completion Tokens: {cb.completion_tokens}")
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print(f"Total Cost (USD): ${cb.total_cost}")
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