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| """Test LLM Bash functionality.""" | |
| import sys | |
| from typing import Type | |
| import pytest | |
| from langchain.evaluation.qa.eval_chain import ( | |
| ContextQAEvalChain, | |
| CotQAEvalChain, | |
| QAEvalChain, | |
| ) | |
| from tests.unit_tests.llms.fake_llm import FakeLLM | |
| def test_eval_chain() -> None: | |
| """Test a simple eval chain.""" | |
| example = {"query": "What's my name", "answer": "John Doe"} | |
| prediction = {"result": "John Doe"} | |
| fake_qa_eval_chain = QAEvalChain.from_llm(FakeLLM()) | |
| outputs = fake_qa_eval_chain.evaluate([example, example], [prediction, prediction]) | |
| assert outputs[0] == outputs[1] | |
| assert "text" in outputs[0] | |
| assert outputs[0]["text"] == "foo" | |
| def test_context_eval_chain(chain_cls: Type[ContextQAEvalChain]) -> None: | |
| """Test a simple eval chain.""" | |
| example = { | |
| "query": "What's my name", | |
| "context": "The name of this person is John Doe", | |
| } | |
| prediction = {"result": "John Doe"} | |
| fake_qa_eval_chain = chain_cls.from_llm(FakeLLM()) | |
| outputs = fake_qa_eval_chain.evaluate([example, example], [prediction, prediction]) | |
| assert outputs[0] == outputs[1] | |
| assert "text" in outputs[0] | |
| assert outputs[0]["text"] == "foo" | |