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2f12302 c6d3d04 2f12302 c6d3d04 2f12302 229f176 2f12302 229f176 2f12302 c6d3d04 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | from langchain.chains.llm import LLMChain
from langchain.chat_models import ChatOpenAI
from langchain.docstore.document import Document
import time
from typing import List
from langchain.chains.summarize import load_summarize_chain
async def async_generate_llmchain(
llm: ChatOpenAI, docs: List[Document], llm_kwargs: dict, k: str
) -> dict:
"""Asyncronous LLMChain function.
Args:
llm (ChatOpenAI): Language model to use.
docs (List[Document]): List of documents.
llm_kwargs (dict): Keyword arguments for the LLMChain.
k (str): Key for a dictionary under which the output is returned.
Returns:
dict: Dictionary with the summarization.
"""
print(f"Starting summarization for {k}")
now = time.time()
chain = load_summarize_chain(
llm=llm,
**llm_kwargs,
)
resp = await chain.arun(docs)
print(f"Time taken for {k}: ", time.time() - now)
return {k: resp}
async def async_generate_summary_chain(
llm: ChatOpenAI, docs: List[Document], summarization_kwargs: dict, k: str
) -> dict:
"""Asyncronous LLMChain function.
Args:
llm (ChatOpenAI): Language model to use.
docs (List[Document]): List of documents.
summarization_kwargs (dict): Keyword arguments for the load_summarize_chain.
k (str): Key for a dictionary under which the output is returned.
Returns:
dict: Dictionary with the summarization.
"""
print(f"Starting summarization for {k}")
now = time.time()
chain = load_summarize_chain(
llm=llm,
**summarization_kwargs,
)
resp = await chain.arun(docs)
print(f"Time taken for {k}: ", time.time() - now)
return {k: resp}
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