loader = TextLoader("static/faq/ecommerce_faq.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
texts = text_splitter.split_documents(documents)
docsearch = Chroma.from_documents(texts, embeddings)
faq_chain = RetrievalQA.from_chain_type(
llm,
chain_type="stuff",
retriever=docsearch.as_retriever()
)
@tool("FAQ")
def faq(intput: str) -> str:
""""useful for when you need to answer questions about shopping policies, like return policy, shipping policy, etc."""
return faq_chain.acall(intput)
async def call_openai(question):
callback = AsyncIteratorCallbackHandler()
# coroutine = wait_done(model.agenerate(messages=[[HumanMessage(content=question)]]), callback.done)
coroutine = wait_done(faq(question), callback.done)
task = asyncio.create_task(coroutine)
print('coroutine', callback.aiter())
# <async_generator object AsyncIteratorCallbackHandler.aiter at 0x11e4ffa40>
async for token in callback.aiter():
yield f"{token}"
await task
