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Async API

LangChain provides async support for Chains by leveraging the asyncio library.

Async methods are currently supported in LLMChain (through arun, apredict, acall) and LLMMathChain (through arun and acall), ChatVectorDBChain, and QA chains. Async support for other chains is on the roadmap.

import asyncio
import time

from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain


def generate_serially():
llm = OpenAI(temperature=0.9)
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}?",
)
chain = LLMChain(llm=llm, prompt=prompt)
for _ in range(5):
resp = chain.run(product="toothpaste")
print(resp)


async def async_generate(chain):
resp = await chain.arun(product="toothpaste")
print(resp)


async def generate_concurrently():
llm = OpenAI(temperature=0.9)
prompt = PromptTemplate(
input_variables=["product"],
template="What is a good name for a company that makes {product}?",
)
chain = LLMChain(llm=llm, prompt=prompt)
tasks = [async_generate(chain) for _ in range(5)]
await asyncio.gather(*tasks)


s = time.perf_counter()
# If running this outside of Jupyter, use asyncio.run(generate_concurrently())
await generate_concurrently()
elapsed = time.perf_counter() - s
print("\033[1m" + f"Concurrent executed in {elapsed:0.2f} seconds." + "\033[0m")

s = time.perf_counter()
generate_serially()
elapsed = time.perf_counter() - s
print("\033[1m" + f"Serial executed in {elapsed:0.2f} seconds." + "\033[0m")

API Reference:

    

BrightSmile Toothpaste Company


BrightSmile Toothpaste Co.


BrightSmile Toothpaste


Gleaming Smile Inc.


SparkleSmile Toothpaste
Concurrent executed in 1.54 seconds.


BrightSmile Toothpaste Co.


MintyFresh Toothpaste Co.


SparkleSmile Toothpaste.


Pearly Whites Toothpaste Co.


BrightSmile Toothpaste.
Serial executed in 6.38 seconds.