Rate Limit Errors (+2)
Rate Limit Errors
from langchain_openai import ChatOpenAI
from tenacity import retry, wait_exponential, stop_after_attempt
llm = ChatOpenAI(
model="gpt-4",
max_retries=3,
request_timeout=60
)
@retry(wait=wait_exponential(min=1, max=60), stop=stop_after_attempt(5))
def invoke_with_retry(chain, input_data):
return chain.invoke(input_data)
Memory Issues with Large Documents
# Process documents in batches
def batch_process_documents(documents, batch_size=100):
for i in range(0, len(documents), batch_size):
batch = documents[i:i + batch_size]
yield process_batch(batch)
Vector Store Performance
# Use FAISS for larger collections
from langchain_community.vectorstores import FAISS
vectorstore = FAISS.from_documents(
documents,
embeddings,
distance_strategy="COSINE"
)
# Add index for faster retrieval
vectorstore.save_local("faiss_index")
vamseeachanta