self.vector_storage_context = StorageContext.from_defaults(vector_store=SimpleVectorStore(), persist_dir="storage/vector")
<skip>
def _create_query_engine(self, product: str) -> RetrieverQueryEngine:
try:
vector_index = load_index_from_storage(storage_context=self.vector_storage_context, embed_model=Settings.embed_model)
print(vector_index.docstore.get_all_document_hashes())
vector_retriever = VectorIndexRetriever(
index=vector_index,
similarity_top_k=10,
)
vector_query_engine = RetrieverQueryEngine(
retriever=vector_retriever,
response_synthesizer=self.response_synthesizer,
node_postprocessors=[
SimilarityPostprocessor(similarity_cutoff=0.50),
self.cohere_rerank
],
)
vector_query_engine.update_prompts({"response_synthesizer:text_qa_template": self.qa_prompt_tmpl})
embedded_query = Settings.embed_model.get_text_embedding("Why is the sky blue?")
print(embedded_query[:5])
response = vector_query_engine.query(QueryBundle(query_str="Why is the sky blue?", embedding=embedded_query))
print(response)INFO:llama_index.core.indices.loading:Loading all indices.
{'5b1b644c50660b2eeb43bb629c2f462bcbdafd4cb4e27ca7501ddfc62bc97c53': 'd8a32ab1-7d70-4385-b2a7-01a5199d1cce', 'e0b24ce3b797398050dae22d27b2e2b24c93d370ef96c358352e38bd0151a97c': '6cccde43-92af-4702-889f-db29fcb45088', 'd2df971ab7a5100975e944a514f1f753d1d0b5156fed7135312444e199b93a93': '8bfa44c9-eeb6-4408-a7ef-c250c53dd88c', 'e9050cb40b3c654d3266997d42beb7fc8d1fd02255f5eeac0679d35df646d997': 'edf5382c-2328-470b-8ffd-b28c6f76c186'}
INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
[-0.026572242379188538, -0.02191539667546749, -0.02187306247651577, 0.015861498191952705, 0.04239140450954437]
Empty Response
storage_context = StorageContext.from_defaults(persist_dir="./storage/vector:) index = load_index_from_storage(storage_context)