I create a llamma2 model and could query with it with no problems and then i saved it like this.
index.storage_context.persist(persist_dir=“<persist_dir_xara>”)
After loading i encountered a weird error
rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir=“<persist_dir_xara>”)
load index
index = load_index_from_storage(storage_context)
query_engine = index.as_query_engine()
response = query_engine.query(“random message”)
ValueError Traceback (most recent call last)
Cell In[12], line 2
1 query_engine = index.as_query_engine()
----> 2 response = query_engine.query(“a”)
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/core/base_query_engine.py:30, in BaseQueryEngine.query(self, str_or_query_bundle)
28 if isinstance(str_or_query_bundle, str):
29 str_or_query_bundle = QueryBundle(str_or_query_bundle)
—> 30 return self._query(str_or_query_bundle)
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/query_engine/retriever_query_engine.py:170, in RetrieverQueryEngine._query(self, query_bundle)
166 “”“Answer a query.”“”
167 with self.callback_manager.event(
168 CBEventType.QUERY, payload={EventPayload.QUERY_STR: query_bundle.query_str}
169 ) as query_event:
→ 170 nodes = self.retrieve(query_bundle)
171 response = self._response_synthesizer.synthesize(
172 query=query_bundle,
173 nodes=nodes,
174 )
176 query_event.on_end(payload={EventPayload.RESPONSE: response})
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/query_engine/retriever_query_engine.py:126, in RetrieverQueryEngine.retrieve(self, query_bundle)
125 def retrieve(self, query_bundle: QueryBundle) → List[NodeWithScore]:
→ 126 nodes = self._retriever.retrieve(query_bundle)
127 return self._apply_node_postprocessors(nodes, query_bundle=query_bundle)
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/core/base_retriever.py:54, in BaseRetriever.retrieve(self, str_or_query_bundle)
49 with self.callback_manager.as_trace(“query”):
50 with self.callback_manager.event(
51 CBEventType.RETRIEVE,
52 payload={EventPayload.QUERY_STR: query_bundle.query_str},
53 ) as retrieve_event:
—> 54 nodes = self._retrieve(query_bundle)
55 retrieve_event.on_end(
56 payload={EventPayload.NODES: nodes},
57 )
58 return nodes
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/indices/vector_store/retrievers/retriever.py:88, in VectorIndexRetriever._retrieve(self, query_bundle)
82 if query_bundle.embedding is None and len(query_bundle.embedding_strs) > 0:
83 query_bundle.embedding = (
84 self._service_context.embed_model.get_agg_embedding_from_queries(
85 query_bundle.embedding_strs
86 )
87 )
—> 88 return self._get_nodes_with_embeddings(query_bundle)
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/indices/vector_store/retrievers/retriever.py:164, in VectorIndexRetriever._get_nodes_with_embeddings(self, query_bundle_with_embeddings)
160 def _get_nodes_with_embeddings(
161 self, query_bundle_with_embeddings: QueryBundle
162 ) → List[NodeWithScore]:
163 query = self._build_vector_store_query(query_bundle_with_embeddings)
→ 164 query_result = self._vector_store.query(query, **self._kwargs)
165 return self._build_node_list_from_query_result(query_result)
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/vector_stores/simple.py:274, in SimpleVectorStore.query(self, query, **kwargs)
266 top_similarities, top_ids = get_top_k_mmr_embeddings(
267 query_embedding,
268 embeddings,
(…)
271 mmr_threshold=mmr_threshold,
272 )
273 elif query.mode == VectorStoreQueryMode.DEFAULT:
→ 274 top_similarities, top_ids = get_top_k_embeddings(
275 query_embedding,
276 embeddings,
277 similarity_top_k=query.similarity_top_k,
278 embedding_ids=node_ids,
279 )
280 else:
281 raise ValueError(f"Invalid query mode: {query.mode}")
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/indices/query/embedding_utils.py:31, in get_top_k_embeddings(query_embedding, embeddings, similarity_fn, similarity_top_k, embedding_ids, similarity_cutoff)
29 similarity_heap: List[Tuple[float, Any]] =
30 for i, emb in enumerate(embeddings_np):
—> 31 similarity = similarity_fn(query_embedding_np, emb)
32 if similarity_cutoff is None or similarity > similarity_cutoff:
33 heapq.heappush(similarity_heap, (similarity, embedding_ids[i]))
File /srv/scratch3/zinonos/zin/lib/python3.10/site-packages/llama_index/embeddings/base.py:47, in similarity(embedding1, embedding2, mode)
45 return np.dot(embedding1, embedding2)
46 else:
—> 47 product = np.dot(embedding1, embedding2)
48 norm = np.linalg.norm(embedding1) * np.linalg.norm(embedding2)
49 return product / norm
ValueError: shapes (1536,) and (768,) not aligned: 1536 (dim 0) != 768 (dim 0)