Debugging Dynamic Few Shot Langchain Code

# Import necessary modules and classes from langchain_community and langchain_core
from langchain_community.vectorstores import Chroma
from langchain_core.example_selectors import SemanticSimilarityExampleSelector
from langchain_openai import OpenAIEmbeddings   ## paid
from langchain.embeddings import HuggingFaceEmbeddings   #free


## setup vector db
# Create an instance of Chroma vector store
vectorstore = Chroma()

# Delete any existing collection in the vector store
# vectorstore.delete_collection()

# Create a SemanticSimilarityExampleSelector instance using examples, OpenAI embeddings, and the vector store
example_selector = SemanticSimilarityExampleSelector.from_examples(
    examples,  # List of example queries and inputs
    HuggingFaceEmbeddings(), #HuggingFaceEmbeddings() OpenAIEmbeddings() # OpenAI Embeddings for generating vector representations
    vectorstore,  # Chroma vector store for storing and querying vector representations
    k=2,  # Number of similar examples to retrieve
    input_keys=["input"],  # Define the input keys to consider for semantic similarity
)

This is my code, its showing an error "name 'examples' is not defined". How to solve it ?

I tried to debug, but i failed. Could anyone hepl me out.

Does examples get defined? Here's an example of SemanticSimilarityExampleSelector.from_examples

example_prompt = PromptTemplate(
    input_variables=["input", "output"],
    template="Input: {input}\nOutput: {output}",
)

# Examples of a pretend task of creating antonyms.
examples = [
    {"input": "happy", "output": "sad"},
    {"input": "tall", "output": "short"},
    {"input": "energetic", "output": "lethargic"},
    {"input": "sunny", "output": "gloomy"},
    {"input": "windy", "output": "calm"},
]

example_selector = SemanticSimilarityExampleSelector.from_examples(
    # The list of examples available to select from.
    examples,
    # The embedding class used to produce embeddings which are used to measure semantic similarity.
    OpenAIEmbeddings(),
    # The VectorStore class that is used to store the embeddings and do a similarity search over.
    Chroma,
    # The number of examples to produce.
    k=1,
)
similar_prompt = FewShotPromptTemplate(
    # We provide an ExampleSelector instead of examples.
    example_selector=example_selector,
    example_prompt=example_prompt,
    prefix="Give the antonym of every input",
    suffix="Input: {adjective}\nOutput:",
    input_variables=["adjective"],
)

Take a look at the reference > https://python.langchain.com/v0.2/docs/how_to/example_selectors_mmr/