Hybrid search (keyword + semantic) in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the LangChain vector store for hybrid search.

LangChain

from langchain.vectorstores import [1]

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AChroma

BPinecone

CFAISS

DWeaviate

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a vector store not typically used for hybrid search.

Confusing the import path or name.

The FAISS vector store is commonly used for hybrid search combining keyword and semantic search in LangChain.

2fill in blank

medium

Complete the code to initialize the FAISS vector store with embeddings.

LangChain

vector_store = FAISS.from_texts(texts, [1])

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Aembeddings

Bembedding_model

Cembedding_function

Dembedding

Attempts:

3 left

💡 Hint

Common Mistakes

Using a singular form like 'embedding' instead of 'embeddings'.

Passing an incorrect variable name.

The parameter 'embeddings' is used to pass the embedding model or function to FAISS for vectorizing texts.

3fill in blank

hard

Fix the error in the hybrid search query combining keyword and semantic search.

LangChain

results = vector_store.hybrid_search(query=[1], keyword_weight=0.5, semantic_weight=0.5)

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Atext_query

Bquery_text

Csearch_query

Dquery

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect parameter names like 'query_text' or 'search_query'.

Passing the query as a positional argument instead of keyword argument.

The method expects the parameter named 'query' to receive the search string.

4fill in blank

hard

Fill both blanks to set weights for keyword and semantic parts in hybrid search.

LangChain

results = vector_store.hybrid_search(query='example', keyword_weight=[1], semantic_weight=[2])

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A0.7

B0.3

C1.0

D0.5

Attempts:

3 left

💡 Hint

Common Mistakes

Setting weights that do not sum up or are out of range.

Confusing which weight corresponds to keyword or semantic.

Commonly, keyword_weight is set to 0.5 and semantic_weight to 0.3 or similar to balance the search.

5fill in blank

hard

Fill all three blanks to create a hybrid search function combining keyword and semantic queries.

LangChain

def hybrid_search_function(query):
    keyword_results = vector_store.keyword_search(query=[1])
    semantic_results = vector_store.semantic_search(query=[2])
    combined = keyword_results[:[3]] + semantic_results[:5]
    return combined

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

Aquery

C3

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names for query in keyword and semantic search.

Not slicing the results to limit combined output.

Both keyword and semantic search use the same 'query' parameter. Limiting keyword results to 3 and semantic to 5 balances the combined output.

Practice

1. What is the main advantage of using hybrid search (keyword + semantic) in Langchain?

easy

A. It combines exact word matching with understanding related meanings for better results.

B. It only uses keyword matching for faster searches.

C. It replaces semantic search completely with keyword search.

D. It ignores the meaning of words and focuses on spelling.

Solution

1. Step 1: Understand keyword search

   Keyword search finds exact matches of words typed by the user.

2. Step 2: Understand semantic search

   Semantic search finds results related in meaning, even if words differ.

3. Final Answer:

   It combines exact word matching with understanding related meanings for better results. -> Option A

4. Quick Check:

   Hybrid search = keyword + semantic [OK]

Hint: Remember hybrid means mixing two methods for best results [OK]

Common Mistakes:

• Thinking hybrid search only uses keywords
• Believing semantic search ignores meaning
• Confusing hybrid search with only semantic search

2. Which of the following is the correct way to initialize a hybrid search in Langchain combining keyword and semantic search?

easy

A. HybridSearch(semantic_searcher, keyword_searcher)

B. HybridSearch(keyword_searcher, semantic_searcher)

C. HybridSearch(keyword_searcher + semantic_searcher)

D. HybridSearch(keyword_searcher * semantic_searcher)

Solution

1. Step 1: Check constructor parameters

   HybridSearch expects two separate searcher objects as arguments.

2. Step 2: Confirm order and syntax

   The correct syntax is HybridSearch(keyword_searcher, semantic_searcher) with comma separation.

3. Final Answer:

   HybridSearch(keyword_searcher, semantic_searcher) -> Option B

4. Quick Check:

   Correct syntax uses comma-separated searchers [OK]

Hint: Use commas to separate searchers, not operators [OK]

Common Mistakes:

• Using + or * instead of comma to combine searchers
• Swapping the order of keyword and semantic searchers
• Passing a single combined object instead of two

3. Given the following code snippet in Langchain, what will be the output type of results?

hybrid_search = HybridSearch(keyword_searcher, semantic_searcher)
results = hybrid_search.search('apple')

medium

A. A single document matching the keyword exactly

B. A boolean indicating if 'apple' exists in the database

C. A list of documents ranked by combined keyword and semantic relevance

D. An error because HybridSearch has no search method

Solution

1. Step 1: Understand HybridSearch.search()

   The search method returns multiple documents ranked by relevance.

2. Step 2: Combine keyword and semantic results

   Hybrid search merges keyword and semantic scores to rank documents.

3. Final Answer:

   A list of documents ranked by combined keyword and semantic relevance -> Option C

4. Quick Check:

   Hybrid search returns ranked document list [OK]

Hint: Hybrid search returns ranked lists, not single items [OK]

Common Mistakes:

• Expecting a single document instead of a list
• Thinking it returns a boolean
• Assuming HybridSearch lacks a search method

4. You wrote this code but get an error:

hybrid_search = HybridSearch(keyword_searcher semantic_searcher)
results = hybrid_search.search('banana')

What is the error and how to fix it?

medium

A. Missing comma between keyword_searcher and semantic_searcher; add a comma.

B. search method does not exist; rename to find.

C. HybridSearch cannot take two arguments; combine them first.

D. The string 'banana' should be a list; change to ['banana'].

Solution

1. Step 1: Identify syntax error in constructor

   There is no comma between keyword_searcher and semantic_searcher, causing a syntax error.

2. Step 2: Fix by adding comma

   Insert a comma to separate the two arguments correctly.

3. Final Answer:

   Missing comma between keyword_searcher and semantic_searcher; add a comma. -> Option A

4. Quick Check:

   Arguments must be comma-separated [OK]

Hint: Check commas between arguments to avoid syntax errors [OK]

Common Mistakes:

• Forgetting commas between function arguments
• Assuming method name is wrong
• Changing input type unnecessarily

5. You want to improve search results by weighting keyword matches twice as much as semantic similarity in Langchain's hybrid search. Which approach correctly applies this weighting?

hard

A. Use only keyword_searcher to get stronger keyword matches.

B. Multiply semantic_searcher results by 2 before combining.

C. Swap keyword_searcher and semantic_searcher order in HybridSearch constructor.

D. Use HybridSearch(keyword_searcher, semantic_searcher, weights=[2,1]) to set weights.

Solution

1. Step 1: Understand weighting in hybrid search

   HybridSearch can accept weights to prioritize one search type over another.

2. Step 2: Apply weights parameter correctly

   Passing weights=[2,1] gives keyword search double importance compared to semantic search.

3. Final Answer:

   Use HybridSearch(keyword_searcher, semantic_searcher, weights=[2,1]) to set weights. -> Option D

4. Quick Check:

   Weights parameter controls search importance [OK]

Hint: Use weights parameter to prioritize keyword or semantic search [OK]

Common Mistakes:

• Trying to multiply results manually before combining
• Swapping searchers without weighting
• Using only one searcher loses hybrid benefits