Vector database operations (CRUD) in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to insert a vector into the database.

Prompt Engineering / GenAI

db.[1](vector_id='vec1', vector=[0.1, 0.2, 0.3])

Drag options to blanks, or click blank then click option'

Aupdate

Bdelete

Cinsert

Dsearch

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'delete' instead of 'insert' will remove data instead of adding.

Using 'update' tries to change existing data, not add new.

Using 'search' is for finding vectors, not adding.

The 'insert' method is used to add a new vector to the database.

2fill in blank

medium

Complete the code to retrieve a vector by its ID.

Prompt Engineering / GenAI

result = db.[1](vector_id='vec1')

Drag options to blanks, or click blank then click option'

Aget

Bupdate

Cdelete

Dinsert

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'insert' tries to add data instead of retrieving.

Using 'delete' removes data instead of fetching.

Using 'update' modifies data instead of fetching.

The 'get' method retrieves a vector by its ID from the database.

3fill in blank

hard

Fix the error in the code to update a vector's values.

Prompt Engineering / GenAI

db.[1](vector_id='vec1', vector=[0.4, 0.5, 0.6])

Drag options to blanks, or click blank then click option'

Ainsert

Bupdate

Cget

Dsearch

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'insert' will add a new vector instead of updating.

Using 'get' only retrieves data, does not change it.

Using 'search' finds vectors but does not update.

The 'update' method changes the vector data for the given ID.

4fill in blank

hard

Fill both blanks to delete a vector and confirm its removal.

Prompt Engineering / GenAI

db.[1](vector_id='vec2')
exists = db.[2](vector_id='vec2')

Drag options to blanks, or click blank then click option'

Adelete

Binsert

Cget

Dupdate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'insert' instead of 'delete' will add data instead of removing.

Using 'update' does not remove data.

Using 'insert' or 'update' to check existence is incorrect.

Use 'delete' to remove the vector and 'get' to check if it still exists (should return None or similar).

5fill in blank

hard

Fill all three blanks to perform a search, update a vector, and then retrieve it.

Prompt Engineering / GenAI

results = db.[1](query_vector=[0.1, 0.2, 0.3], top_k=5)
db.[2](vector_id='vec3', vector=[0.7, 0.8, 0.9])
updated_vector = db.[3](vector_id='vec3')

Drag options to blanks, or click blank then click option'

Ainsert

Bupdate

Cget

Dsearch

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'insert' instead of 'search' will add data instead of finding.

Using 'get' instead of 'update' will not change the vector.

Using 'delete' in any step will remove data unexpectedly.

First, 'search' finds similar vectors; then 'update' changes the vector; finally, 'get' retrieves the updated vector.

Practice

1. What does the CRUD acronym stand for in vector database operations?

easy

A. Connect, Run, Undo, Deploy

B. Compute, Retrieve, Upload, Download

C. Create, Read, Update, Delete

D. Cache, Refresh, Use, Drop

Solution

1. Step 1: Understand CRUD basics

   CRUD is a common term in databases meaning the four basic operations you can do with data.

2. Step 2: Match each letter to its meaning

   C stands for Create (add new data), R for Read (get data), U for Update (change data), and D for Delete (remove data).

3. Final Answer:

   Create, Read, Update, Delete -> Option C

4. Quick Check:

   CRUD = Create, Read, Update, Delete [OK]

Hint: Remember CRUD as basic data actions: add, get, change, remove [OK]

Common Mistakes:

• Confusing CRUD with unrelated terms
• Mixing up the order of operations
• Thinking CRUD only applies to files, not vectors

2. Which of the following is the correct syntax to add a vector with ID 'vec1' and values [0.1, 0.2, 0.3] to a vector database named db?

easy

A. db.push_vector(['vec1', 0.1, 0.2, 0.3])

B. db.insert('vec1', [0.1, 0.2, 0.3])

C. db.create_vector('vec1', 0.1, 0.2, 0.3)

D. db.add_vector('vec1', [0.1, 0.2, 0.3])

Solution

1. Step 1: Identify the common method for adding vectors

   Most vector databases use a method like add_vector with an ID and a list of numbers.

2. Step 2: Check method parameters

   The method should take the vector ID as a string and the vector values as a list or array.

3. Final Answer:

   db.add_vector('vec1', [0.1, 0.2, 0.3]) -> Option D

4. Quick Check:

   Add vector syntax = db.add_vector(id, vector) [OK]

Hint: Add vectors with add_vector(id, vector_list) method [OK]

Common Mistakes:

• Using wrong method names like insert or push_vector
• Passing vector values as separate arguments instead of a list
• Mixing ID and vector in one list

3. Given the following code snippet, what will be the output?

db = VectorDB()
db.add_vector('v1', [1, 0, 0])
db.add_vector('v2', [0, 1, 0])
results = db.search([0.9, 0.1, 0], top_k=1)
print(results)

medium

A. [('v1', 0.9)]

B. [('v2', 0.9)]

C. [('v1', 0.1)]

D. [('v2', 0.1)]

Solution

1. Step 1: Understand the vectors and query

   Vectors 'v1' = [1,0,0], 'v2' = [0,1,0], query = [0.9,0.1,0].

2. Step 2: Calculate similarity or distance

   Assuming cosine similarity, 'v1' is closer to query (dot product ~0.9), 'v2' is less similar (~0.1).

3. Final Answer:

   [('v1', 0.9)] -> Option A

4. Quick Check:

   Closest vector = v1 with similarity 0.9 [OK]

Hint: Closest vector has highest dot product with query [OK]

Common Mistakes:

• Confusing similarity with distance
• Mixing up vector IDs in output
• Assuming lower score means closer

4. The following code tries to update a vector but throws an error. What is the likely cause?

db = VectorDB()
db.add_vector('v1', [0.5, 0.5, 0.5])
db.update_vector('v2', [0.1, 0.1, 0.1])

medium

A. Vector 'v2' does not exist, so update fails

B. The update_vector method requires 4 arguments

C. Vector values must be integers, not floats

D. The add_vector method was not called before update_vector

Solution

1. Step 1: Check vector existence before update

   Updating a vector requires it to exist in the database first.

2. Step 2: Identify the error cause

   Since 'v2' was never added, trying to update it causes an error.

3. Final Answer:

   Vector 'v2' does not exist, so update fails -> Option A

4. Quick Check:

   Update needs existing vector [OK]

Hint: Update only existing vectors, else error occurs [OK]

Common Mistakes:

• Assuming update creates new vectors
• Thinking data type mismatch causes error
• Ignoring vector existence check

5. You want to delete vectors with similarity less than 0.5 to a query vector [0, 1, 0] from your vector database. Which sequence of operations correctly achieves this?

hard

A. Delete all vectors, then add only those with similarity >= 0.5

B. Search vectors with similarity < 0.5, then delete each by ID

C. Update vectors with similarity < 0.5 to zero vectors

D. Add new vectors with similarity >= 0.5, ignoring deletion

Solution

1. Step 1: Find vectors below similarity threshold

   Use a search or filter operation to get IDs of vectors with similarity less than 0.5.

2. Step 2: Delete vectors by their IDs

   Use the delete operation on each vector ID found to remove them from the database.

3. Final Answer:

   Search vectors with similarity < 0.5, then delete each by ID -> Option B

4. Quick Check:

   Filter then delete unwanted vectors [OK]

Hint: Filter vectors first, then delete by ID [OK]

Common Mistakes:

• Deleting all vectors instead of selective ones
• Trying to update instead of delete
• Ignoring the similarity filter step