[Solved] What is wrong with this Pinecone query code? index = pinecone.Index('my-index') results = index.query(vector=[0.1, 0.2], top_k=3) print(results) | LangChain

LangChain - Embeddings and Vector Stores

What is wrong with this Pinecone query code?

index = pinecone.Index('my-index')
results = index.query(vector=[0.1, 0.2], top_k=3)
print(results)

AThe vector length is too short for the index dimension.

Bquery method requires a list of vectors, not a single vector.

Ctop_k must be 1 or 2, not 3.

Dprint cannot display query results directly.

Step-by-Step Solution

Solution:

Step 1: Check query vector dimension
Pinecone indices have fixed dimensions (typically 768 or 1536). A 2-element vector will cause a dimension mismatch error.
Step 2: Rule out other options
query accepts a single vector as list[float], top_k=3 is valid, print displays results fine.
Final Answer:
The vector length is too short for the index dimension. -> Option A
Quick Check:
Vector dim mismatch = A [OK]

Quick Trick: Vector dimension must match index dimension [OK]

Common Mistakes:

Master "Embeddings and Vector Stores" in LangChain

9 interactive learning modes - each teaches the same concept differently

More LangChain Quizzes

What is wrong with this Pinecone query code?