.....FF... [100%]
=========================================================================== FAILURES ===========================================================================
__________________________________________________________________ TestRAGPipeline.test_query __________________________________________________________________
self = <llmrag.tests.test_pipeline.TestRAGPipeline testMethod=test_query>
def test_query(self):
question = "What is photosynthesis?"
> answer = self.pipeline.query(question)
tests\test_pipeline.py:40:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <llmrag.pipelines.rag_pipeline.RAGPipeline object at 0x000002BFD39D9340>, question = 'What is photosynthesis?', top_k = 4, temperature = 0.3
def query(self, question: str, top_k=4, temperature=0.3) -> str:
docs = self.vector_store.retrieve(question, top_k=top_k)
# Deduplicate context to reduce redundancy
seen = set()
unique_docs = []
for doc in docs:
if doc.page_content not in seen:
seen.add(doc.page_content)
unique_docs.append(doc)
context = "\n".join(doc.page_content for doc in unique_docs)
# Clear instruction with delimiter to prevent multiple QA pairs
prompt = f"""You are a helpful assistant. Use ONLY the following context to answer the user's question.
If the answer is not in the context, say "I don't know."
Context:
{context}
Question: {question}
Answer:"""
> return self.model.generate(prompt, temperature=temperature)
E TypeError: TransformersModel.generate() got an unexpected keyword argument 'temperature'
llmrag\pipelines\rag_pipeline.py:49: TypeError
-------------------------------------------------------------------- Captured stderr setup ---------------------------------------------------------------------
Device set to use cpu
__________________________________________________________ TestRAGPipeline.test_retrieve_and_generate __________________________________________________________
self = <llmrag.tests.test_pipeline.TestRAGPipeline testMethod=test_retrieve_and_generate>
def test_retrieve_and_generate(self):
question = "What is AI?"
> response = self.pipeline.query(question)
tests\test_pipeline.py:34:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <llmrag.pipelines.rag_pipeline.RAGPipeline object at 0x000002BFD39D9340>, question = 'What is AI?', top_k = 4, temperature = 0.3
def query(self, question: str, top_k=4, temperature=0.3) -> str:
docs = self.vector_store.retrieve(question, top_k=top_k)
# Deduplicate context to reduce redundancy
seen = set()
unique_docs = []
for doc in docs:
if doc.page_content not in seen:
seen.add(doc.page_content)
unique_docs.append(doc)
context = "\n".join(doc.page_content for doc in unique_docs)
# Clear instruction with delimiter to prevent multiple QA pairs
prompt = f"""You are a helpful assistant. Use ONLY the following context to answer the user's question.
If the answer is not in the context, say "I don't know."
Context:
{context}
Question: {question}
Answer:"""
> return self.model.generate(prompt, temperature=temperature)
E TypeError: TransformersModel.generate() got an unexpected keyword argument 'temperature'
llmrag\pipelines\rag_pipeline.py:49: TypeError
=================================================================== short test summary info ====================================================================
FAILED tests/test_pipeline.py::TestRAGPipeline::test_query - TypeError: TransformersModel.generate() got an unexpected keyword argument 'temperature'
FAILED tests/test_pipeline.py::TestRAGPipeline::test_retrieve_and_generate - TypeError: TransformersModel.generate() got an unexpected keyword argument 'temperature'
2 failed, 8 passed in 64.88s (0:01:04)
