# Langchain Rate Limit Errors

> Sub-skill of langchain: Rate Limit Errors (+2).

- Skill: `vamseeachanta/langchain-rate-limit-errors` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vamseeachanta/langchain-rate-limit-errors`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vamseeachanta/langchain-rate-limit-errors/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: vamseeachanta (https://skillmd.com/u/vamseeachanta)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vamseeachanta/langchain-rate-limit-errors

---


# Rate Limit Errors (+2)

## Rate Limit Errors


```python
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


```python
# 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


```python
# 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")
```