Ragie (https://ragie.ai) integration for LangChain
pip install langchain-ragieIf you need asyncio, see this example..
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnablePassthrough
import langchain_ragie
template = """Answer the question based only on the following context:
{context}
Question: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
model = ChatOpenAI()
retriever = langchain_ragie.RagieRetriever()
def format_docs(docs):
return "\n\n".join([d.page_content for d in docs])
chain = (
{"context": retriever | format_docs, "question": RunnablePassthrough()}
| prompt
| model
| StrOutputParser()
)
response = chain.invoke("What do the besties think about Davos?")
print(response)Distributed under the MIT License. See LICENSE.txt for more information.