[Python] Retrying...

I am using langchain to embed with google palm embedding. I worked on this project around 6 months ago, but when I'm trying to run it now it keeps generating this error

" Retrying langchain_community.embeddings.google_palm.embed_with_retry.._embed_with_retry in 8.0 seconds as it raised NotFound: 404 Requested entity was not found.. "
​

what I have deducted it the main issue arise from this part of the code:

llm = GoogleGenerativeAI(model="gemini-1.5-pro")
​

Here is the following code which is responsible for it:

def get_chain(db, question):

os.environ['LANGCHAIN_TRACING_V2']='true'
os.environ["LANGCHAIN_PROJECT"] = 'Sample Agent Trace'
os.environ['LANGCHAIN_API_KEY']='key'
os.environ['GOOGLE_API_KEY']='key'

llm = GoogleGenerativeAI(model="gemini-1.5-pro")


generate_query = create_sql_query_chain(llm, db) # converts natural language to sql query
execute_query=QuerySQLDataBaseTool(db=db)
answer_prompt = PromptTemplate.from_template(
"""Given the following user question, corresponding SQL query, and SQL result, Generate a full-fleged natural language sentence with as if you are telling someone containing the actual output.
Question: {question}
SQL Query: {query}
SQL Result: {result}
Answer: """
)

rephrase_answer = answer_prompt | llm | StrOutputParser()
chain = (
RunnablePassthrough.assign(query=generate_query).assign(
result=itemgetter("query") | execute_query
)
| rephrase_answer)

examples = [" ".join(example.values()) for example in few_shots]
embeddings=GooglePalmEmbeddings(google_api_key=os.getenv('GOOGLE_API_KEY'))
vectorstore=Chroma.from_texts(examples,embedding=embeddings,metadatas=few_shots)
example_selector=SemanticSimilarityExampleSelector(
vectorstore=vectorstore,
k=1
)

mysql_prompt = """
prompt
"""
example_prompt = PromptTemplate(
input_variables=["Question", "SQLQuery", "SQLResult","Answer",],
template="\nQuestion: {Question}\nSQLQuery: {SQLQuery}\nSQLResult: {SQLResult}\nAnswer: {Answer}",
)
few_shot_prompt = FewShotPromptTemplate(
example_selector=example_selector,
example_prompt=example_prompt,
prefix=mysql_prompt,
suffix=PROMPT_SUFFIX,
input_variables=["input", "table_info", "top_k"], #These variables are used in the prefix and suffix
)
generate_query = create_sql_query_chain(llm, db,few_shot_prompt)
chain = (
RunnablePassthrough.assign(query=generate_query).assign(
result=itemgetter("query") | execute_query
)
| rephrase_answer
)

return chain.invoke({"question": question})


here are the imports I have used for the solution:

from langchain_google_genai import GoogleGenerativeAI
from langchain_community.utilities.sql_database import SQLDatabase
from langchain.chains import create_sql_query_chain
from langchain_community.tools import QuerySQLDataBaseTool
from operator import itemgetter
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import RunnablePassthrough
from server.few_shorts import few_shots
from langchain_community.embeddings import GooglePalmEmbeddings
from langchain_community.vectorstores import Chroma
from langchain.prompts import SemanticSimilarityExampleSelector
from langchain.prompts import FewShotPromptTemplate
from langchain.chains.sql_database.prompt import PROMPT_SUFFIX
from langchain.prompts.prompt import PromptTemplate
from langchain.prompts import FewShotPromptTemplate

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