mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
95dc90609e
Replaced `from langchain.prompts` with `from langchain_core.prompts` where it is appropriate. Most of the changes go to `langchain_experimental` Similar to #20348
121 lines
4.4 KiB
Python
121 lines
4.4 KiB
Python
"""Test SmartLLM."""
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from langchain_community.chat_models import FakeListChatModel
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from langchain_community.llms import FakeListLLM
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from langchain_core.prompts.prompt import PromptTemplate
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from langchain_experimental.smart_llm import SmartLLMChain
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def test_ideation() -> None:
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# test that correct responses are returned
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responses = ["Idea 1", "Idea 2", "Idea 3"]
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llm = FakeListLLM(responses=responses)
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prompt = PromptTemplate(
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input_variables=["product"],
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template="What is a good name for a company that makes {product}?",
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)
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chain = SmartLLMChain(llm=llm, prompt=prompt)
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prompt_value, _ = chain.prep_prompts({"product": "socks"})
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chain.history.question = prompt_value.to_string()
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results = chain._ideate()
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assert results == responses
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# test that correct number of responses are returned
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for i in range(1, 5):
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responses = [f"Idea {j+1}" for j in range(i)]
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llm = FakeListLLM(responses=responses)
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chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=i)
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prompt_value, _ = chain.prep_prompts({"product": "socks"})
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chain.history.question = prompt_value.to_string()
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results = chain._ideate()
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assert len(results) == i
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def test_critique() -> None:
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response = "Test Critique"
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llm = FakeListLLM(responses=[response])
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prompt = PromptTemplate(
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input_variables=["product"],
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template="What is a good name for a company that makes {product}?",
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)
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chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=2)
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prompt_value, _ = chain.prep_prompts({"product": "socks"})
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chain.history.question = prompt_value.to_string()
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chain.history.ideas = ["Test Idea 1", "Test Idea 2"]
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result = chain._critique()
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assert result == response
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def test_resolver() -> None:
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response = "Test resolution"
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llm = FakeListLLM(responses=[response])
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prompt = PromptTemplate(
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input_variables=["product"],
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template="What is a good name for a company that makes {product}?",
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)
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chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=2)
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prompt_value, _ = chain.prep_prompts({"product": "socks"})
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chain.history.question = prompt_value.to_string()
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chain.history.ideas = ["Test Idea 1", "Test Idea 2"]
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chain.history.critique = "Test Critique"
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result = chain._resolve()
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assert result == response
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def test_all_steps() -> None:
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joke = "Why did the chicken cross the Mobius strip?"
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response = "Resolution response"
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ideation_llm = FakeListLLM(responses=["Ideation response" for _ in range(20)])
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critique_llm = FakeListLLM(responses=["Critique response" for _ in range(20)])
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resolver_llm = FakeListLLM(responses=[response for _ in range(20)])
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prompt = PromptTemplate(
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input_variables=["joke"],
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template="Explain this joke to me: {joke}?",
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)
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chain = SmartLLMChain(
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ideation_llm=ideation_llm,
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critique_llm=critique_llm,
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resolver_llm=resolver_llm,
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prompt=prompt,
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)
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result = chain(joke)
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assert result["joke"] == joke
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assert result["resolution"] == response
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def test_intermediate_output() -> None:
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joke = "Why did the chicken cross the Mobius strip?"
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llm = FakeListLLM(responses=[f"Response {i+1}" for i in range(5)])
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prompt = PromptTemplate(
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input_variables=["joke"],
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template="Explain this joke to me: {joke}?",
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)
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chain = SmartLLMChain(llm=llm, prompt=prompt, return_intermediate_steps=True)
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result = chain(joke)
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assert result["joke"] == joke
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assert result["ideas"] == [f"Response {i+1}" for i in range(3)]
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assert result["critique"] == "Response 4"
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assert result["resolution"] == "Response 5"
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def test_all_steps_with_chat_model() -> None:
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joke = "Why did the chicken cross the Mobius strip?"
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response = "Resolution response"
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ideation_llm = FakeListChatModel(responses=["Ideation response" for _ in range(20)])
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critique_llm = FakeListChatModel(responses=["Critique response" for _ in range(20)])
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resolver_llm = FakeListChatModel(responses=[response for _ in range(20)])
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prompt = PromptTemplate(
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input_variables=["joke"],
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template="Explain this joke to me: {joke}?",
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)
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chain = SmartLLMChain(
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ideation_llm=ideation_llm,
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critique_llm=critique_llm,
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resolver_llm=resolver_llm,
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prompt=prompt,
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)
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result = chain(joke)
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assert result["joke"] == joke
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assert result["resolution"] == response
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