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"""Test SmartLLM."""
from langchain_community.chat_models import FakeListChatModel
from langchain_community.llms import FakeListLLM
from langchain_core.prompts.prompt import PromptTemplate
from langchain_experimental.smart_llm import SmartLLMChain
def test_ideation() -> None:
# test that correct responses are returned
responses = ["Idea 1", "Idea 2", "Idea 3"]
llm = FakeListLLM(responses=responses)
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}?",
)
chain = SmartLLMChain(llm=llm, prompt=prompt)
prompt_value, _ = chain.prep_prompts({"product": "socks"})
chain.history.question = prompt_value.to_string()
results = chain._ideate()
assert results == responses
# test that correct number of responses are returned
for i in range(1, 5):
responses = [f"Idea {j+1}" for j in range(i)]
llm = FakeListLLM(responses=responses)
chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=i)
prompt_value, _ = chain.prep_prompts({"product": "socks"})
chain.history.question = prompt_value.to_string()
results = chain._ideate()
assert len(results) == i
def test_critique() -> None:
response = "Test Critique"
llm = FakeListLLM(responses=[response])
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}?",
)
chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=2)
prompt_value, _ = chain.prep_prompts({"product": "socks"})
chain.history.question = prompt_value.to_string()
chain.history.ideas = ["Test Idea 1", "Test Idea 2"]
result = chain._critique()
assert result == response
def test_resolver() -> None:
response = "Test resolution"
llm = FakeListLLM(responses=[response])
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}?",
)
chain = SmartLLMChain(llm=llm, prompt=prompt, n_ideas=2)
prompt_value, _ = chain.prep_prompts({"product": "socks"})
chain.history.question = prompt_value.to_string()
chain.history.ideas = ["Test Idea 1", "Test Idea 2"]
chain.history.critique = "Test Critique"
result = chain._resolve()
assert result == response
def test_all_steps() -> None:
joke = "Why did the chicken cross the Mobius strip?"
response = "Resolution response"
ideation_llm = FakeListLLM(responses=["Ideation response" for _ in range(20)])
critique_llm = FakeListLLM(responses=["Critique response" for _ in range(20)])
resolver_llm = FakeListLLM(responses=[response for _ in range(20)])
prompt = PromptTemplate(
input_variables=["joke"],
template="Explain this joke to me: {joke}?",
)
chain = SmartLLMChain(
ideation_llm=ideation_llm,
critique_llm=critique_llm,
resolver_llm=resolver_llm,
prompt=prompt,
)
result = chain(joke)
assert result["joke"] == joke
assert result["resolution"] == response
def test_intermediate_output() -> None:
joke = "Why did the chicken cross the Mobius strip?"
llm = FakeListLLM(responses=[f"Response {i+1}" for i in range(5)])
prompt = PromptTemplate(
input_variables=["joke"],
template="Explain this joke to me: {joke}?",
)
chain = SmartLLMChain(llm=llm, prompt=prompt, return_intermediate_steps=True)
result = chain(joke)
assert result["joke"] == joke
assert result["ideas"] == [f"Response {i+1}" for i in range(3)]
assert result["critique"] == "Response 4"
assert result["resolution"] == "Response 5"
def test_all_steps_with_chat_model() -> None:
joke = "Why did the chicken cross the Mobius strip?"
response = "Resolution response"
ideation_llm = FakeListChatModel(responses=["Ideation response" for _ in range(20)])
critique_llm = FakeListChatModel(responses=["Critique response" for _ in range(20)])
resolver_llm = FakeListChatModel(responses=[response for _ in range(20)])
prompt = PromptTemplate(
input_variables=["joke"],
template="Explain this joke to me: {joke}?",
)
chain = SmartLLMChain(
ideation_llm=ideation_llm,
critique_llm=critique_llm,
resolver_llm=resolver_llm,
prompt=prompt,
)
result = chain(joke)
assert result["joke"] == joke
assert result["resolution"] == response
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